The Startup Ideas Podcast

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP In this solo episode, I break down how to make money with Meta Muse by mining Facebook groups, Marketplace, and Instagram to match buyers with sellers. The idea came after my wife and I had a baby and the agency we hired for a night nurse admitted it found candidates in Facebook groups. I demo Muse finding night nurses at $30 an hour in Montreal, show how to give it a phone number through Bland AI, and share the Marketplace and Instagram tactics I'd use. I close with my four-level framework for growing a matching side business into a trusted list, a community, and a vertical software company. Timestamps 00:00 – Intro 01:19 – Sponsor: Brex 03:22 – Meta Muse 03:52 – Why this is a big opportunity 04:33 – Picking a Niche, City, and Rules 05:44 – Owning the asset and data 06:51 – Cleaning Data You Own 08:27 – Lessons From eBay 10:37 – A Phone Number With Bland AI 11:30 – Undervalued Facebook Groups 12:55 – Business Pages and IG Niche Pages 13:46 – Prompting Muse Into Facebook Groups 15:19 – Mining FB Marketplace and Instagram 17:20 – Four Levels of Personal Agent Arbitrage 20:38 – Results From Montreal Groups 21:40– Goods vs. Services 22:15 – Muse vs. Dots and Instinct 24:09 – Closing Thoughts Key Points Muse mines public Facebook groups, Marketplace, and Instagram to match buyers and sellers in any niche and city. A clean list of names, needs, prices, and trust signals is an asset I own and can sell later. Facebook groups, business pages, and IG niche pages look undervalued as Muse agents start crawling them. I tell Muse where to look, and Facebook groups gave me the highest quality data. My four levels: mine the data, own the list, own the room, then build technology. A lean cost structure lets me charge a success fee of a few hundred dollars and keep high margins. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Gemini 4 Argon is LIVE, Google's most advanced AI model, try it for yourself: https://startup-ideas-pod.link/gemini4-argon In this solo episode, I share what I learned after a week with Gemini 4 Argon, Google's new frontier model. I show three places it shines: marketing with AI, physical AI, and complex engineering, with a real build for each. You'll see Argon rebuild my holding company's website, write a post in my voice, design a Shopify product customizer that exports STL files, and build a free quoting app for commercial cleaning companies. I close with six techniques that raise Argon's output quality and the Google AI plan I'd pick for building. Timestamps 00:00 – Intro 01:35 – What Gemini 4 Argon Does Well 03:09 – Rebuilding the Late Checkout Website 07:49 – Justine Moore's Apple Computer Museum 09:20 – Using Argon for writing 13:03 – Physical AI and Vibe Manufacturing 17:41 – Made-to-Order Shopify Store 19:01 – Building Boring SaaS 21:59 – Commercial Cleaning Quote App 25:12 – 6 techniques to get the most out of Argon 28:39 – Closing Thoughts Key Points Argon produces premium creative work once I give it reference images and a clear direction. A skill built from my posts, newsletters, and videos lets Argon write in my voice. Argon builds Shopify product customizers that export print-ready STL files. Free, focused rebuilds of boring legacy SaaS put me in front of likely buyers. Argon gets the engineering right on prompt one, and design takes a few more rounds. /plan, /subagents, and /goal give me the biggest jumps in output quality. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through eight GitHub repos and AI skills that I test at night and on weekends. The list covers launch videos, social research, local voice and dubbing, editable decks, agent teams, lead-magnet tools, idea stress-testing, and design guidance. For each one, I explain what it does, how I'd set it up, and one concrete way to use it to make money or run a business more easily. Most are free to download, and you pay for the model you run them with. Timestamps 00:00 – Intro 01:25 – Brag: Launch Videos From a Link 04:50 – Agent Reach for Customer Research 07:46 – Voice Studio: Local AI Voice and Dubbing 10:41 – PPT Master: Editable Decks From Notes 12:59 – OpenRig: Coding Agents as a Team 14:57 – Free Tools Skill by Corey Haynes 17:25 – Grill Me Skill by Matt Pocock 19:31 – Impeccable: Design Guidance for Agents 23:03 – My Top Picks: Brag and Agent Reach 24:07 – Closing Thoughts GitHub Repo Links: Brag (launch video skill): https://startup-ideas-pod.link/brag Agent Reach: https://startup-ideas-pod.link/agent-reach Voice Studio: https://startup-ideas-pod.link/voice-studio PPT Master: https://startup-ideas-pod.link/ppt-master OpenRig: https://startup-ideas-pod.link/openrig Free Tool: https://startup-ideas-pod.link/marketing-skills Grill Me Skill: https://startup-ideas-pod.link/grill-me Impeccable Skill: https://startup-ideas-pod.link/impeccable Key Points Most of these tools are free to download, and the main cost is the model you run them with. Work I do for someone up front, like a launch video or a design fix, starts a conversation in place of a cold email. Posts on Reddit, X, and YouTube show tasks people still do by hand, and a small tool can fix them. Translated onboarding videos make a recurring monthly service for other companies. Grill Me logs my assumptions so I check them with a real customer before I build. Ten clients at $1,000 a month is $10,000 a month, and that cash flow funds the move from services to technology. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I walk through the 13 businesses I think are left to build in the agentic era. I believe that in a world of agents and abundance, owning the right assets puts you in a better position. For each business, I explain what it is, why it holds up in a world of agents, and one or two examples, from Othership's sauna clubs to Osmo's window-cleaning robots. This episode gives you a map of where to build next, at any age. Timestamps 00:00 – Intro 01:15 – AI-Native Service Firms 02:57 – Offline Businesses 05:41 – Distribution and Organic Audiences 07:34 – Proprietary Data Sets 09:08 – Domain-Specific Harnesses 12:16 – Robotics and Physical AI 14:01 – Physical Products With a Fan Following 16:34 – Compute and Energy 17:31 – Health, Longevity, and Care 19:30 – Marketplaces and Social Networks 21:04 – Real Assets 21:46 – Vertical Agents 22:18 – Security 24:08 – Closing Thoughts Key Points In an AI-native service firm, agents do most of the delivery and a human reviews the exceptions. Ad clicks went from about five cents in 2009 to $1–5 today, so I start with organic audiences. Proprietary data and domain-specific harnesses are the two gold rushes I see right now. Offline businesses, niche hardware, and robotics sell rooms, objects, and labor that agents only support. Compute, energy, and security are the scarce inputs every agent depends on. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Google's most advanced audio models are LIVE, try them for yourself: Gemini 3.8 Live: https://startup-ideas-pod.link/gemini-3.8-live Gemini 3.5 Transcribe https://startup-ideas-pod.link/gemini-3.5-transcribe Gemini 3.5 Live Translate: https://startup-ideas-pod.link/gemini-3.5-live-translate In this episode, I talk with Vas from Varick about what it takes to put AI to work inside a real company. Vas makes the case that AI pays off through process reengineering, and he walks me through the exact method his forward deployed engineers (FDEs) use: interviews, process mining, step sorting, and agents built inside existing systems of record. We go through real engagements, including a $5B public software company and an accounts payable overhaul that cut the cost per invoice from $31 to $6. By the end, you get a clear picture of the FDE role, the business opportunity behind AI roll-ups, and a five-day plan to start on your own. Links Mentioned: FDE Presentation: https://startup-ideas-pod.link/FDE-slides Vas’s Article: https://startup-ideas-pod.link/vas-fde Timestamps 00:00 – Intro 01:31 – Sponsor: Google 03:58 – FDE Overview 05:02 – AI Roll-Ups and Process Reengineering 08:04 – The Personal Systems Analogy 09:55 – Understanding a company’s process (step-by-step) 14:11 – Case Study: $5B Software Company 18:11 – 4 Buckets for Every Step 19:04 – Build Inside Systems of Record 21:36 – Case Study: PE Portfolio 23:43 – Selling to C-Suite Executives 27:07 – Process of Mapping Five NetSuite Companies 28:39 – Example: Accounts Payable Process Map 32:54 – Case Study: 60-Person Accounting Firm 34:51 – When to Use Code, Agents, or Humans 36:00 – Choosing AI Models 38:16 – Sidekick vs Background Agents 40:29 – The 3 Skills of a Top FDE 42:25 – Why FDEs Earn So Much 45:26 – Five-Day Starter Plan 47:39 – On-Premise Hardware Demand 48:36 – OpenAI Private Intelligence 50:20 – The Full Playbook 52:01 – Closing Thoughts Key Points AI pays off when you re-engineer the process first, then build agents into it. Map the real process with interviews, system-of-record mining, and existing docs. Sort every step into four buckets: delete, plain code, agent, or human decision. Build agents inside the tools clients already use, like Salesforce, NetSuite, and Slack. Sell the outcome each buyer cares about, and prove it with before-and-after KPIs. Top FDEs combine domain knowledge, production engineering, AI judgment, and strong communication. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VAS ON SOCIAL Varick Agents: https://www.varickagents.com/#hero-section X/Twitter: https://x.com/vasuman AI Forward Deployed Engineers: https://learn.varickagents.com/fde-in-30-days

I watched almost 60 minutes of Sam Altman on stage at OpenAI Dev Day 2026. Out of 20-plus launches, I pick the three or four that I think can make people billions of dollars in aggregate. I break down Dots, OpenAI's personal agent platform, plus the Decisions API, the Agents API with computer use, and Sign in with ChatGPT. I also share my four-step framework for building in this world and two business ideas I hope someone takes. If you want to build a business and make money around AI, this episode is for you. Timestamps 00:00 – Intro 01:48 – Dots, the Personal Agent Platform 03:29 – OpenAI Doubles Down on Plugins 05:02 – Decisions API 06:43 – Agents API With Computer Use 08:01 – Sign In With ChatGPT 12:36 – Where should you build? 13:46 – Idea: Real-World Work APIs 15:04 – Idea: Analytics for Agent Discovery 17:05 –Closing Thoughts Key Points Dots gives plugin builders a front door to 1.2 billion weekly active users. OpenAI is doubling down on plugins to make ChatGPT the app ecosystem for AI. Sign in with ChatGPT lets users bring their current plan, so a free core app with paid upsells now works. Workflows too niche for OpenAI to build become viable businesses. The strongest businesses in this world own the trigger, the action, and the feedback. Two open opportunities: real-world work APIs and an analytics layer for agent discovery The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I break down the $5 trillion wave of small businesses set to change hands as their owners retire, and why AI agents make this wave a real opening for solo founders. I walk through how Thrive Holdings and General Catalyst buy accounting firms, property managers, and support centers, then run AI agents inside them to lift margins. Then I show how I'd run a one-person holding company: the folder structure, the agent files, the human approval rule, and my average week. I close with the strongest arguments against AI roll-ups, including the one I take most seriously. Timestamps 00:00 – Intro 01:52 – Why the $5 Trillion Shift Is Happening Now 04:52 – Examples: Thrive Holdings& General Catalyst 08:38 – The Fund Playbook 10:07 – The Small-Deal Gap 10:51 – The One-Person Holdco 14:23 – The Folder Structure 16:47 – The Agent Pipeline 18:38 – Inside a Reviewer Agent File 19:41 – My Week Running the Holdco 21:49 – How to Land the First Business 22:24 – Arguments Against AI Roll-Ups 27:43 – Closing Thoughts Key Points About a million small businesses, part of a $5 trillion shift, are set to sell by 2035 as owners retire (McKinsey). AI agents now handle the work these firms run on: data entry, document chasing, status updates, and first drafts. The big funds chase bigger deals, which leaves the small firms open for solo founders and small teams. A one-person holdco runs on shared agents and rules, plus a GM with real upside at each business. A person approves all agent work before it reaches a client. The corrections log, turned into rules every week, becomes the most valuable asset in the holdco. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I break down the huge business opportunity because Meta has opened Muse, its personal AI agent, to developers. You can now submit a connector, which lets Muse use your service when someone asks it for help, and I think this could be the app store moment for AI. I explain how a connector works, share four startup ideas you can build on one, and cover how to get customers beyond Meta's directory. I also show how I'd build a first version with a coding agent like Claude Code or Codex, and what I'd test before submitting it to Meta for review. Timestamps 00:00 – Intro 01:35 – The App Store Parallel 04:55 – How a Muse Connector Works 07:29 – Startup Idea 1: Lead Gen for Business Suppliers 09:28 – Startup Idea 2: Home Repair Dispatch 11:07 – Startup Idea 3: Paddle Match and Court Finder 12:47 – Startup Idea 4: Family Dinner Planning 14:10 – How to pick an idea? 14:56 – How People Find Your Connector 15:32 – Growth Idea 1: Partner With Creators 16:17 – Growth Idea 2: Product-Led Sharing 17:46 – Growth Idea 3: Connected Marketplaces and Directory Placement 19:34 – Building the First Version 21:38 – Custom Connectors and Meta Approval 23:56 – Where to Start This Week 25:31 – Closing thoughts Muse Connector Prompt: https://startup-ideas-pod.link/muse-connector-prompt Key Points Meta has opened Muse to developers, and a connector lets Muse use your service when someone asks it for help. I look closely at the step in a request where someone needs a business that can deliver and money changes hands. With a small budget, I'd start with lead generation, because I can show a customer a sample before writing much software. I plan distribution around channels I can reach, such as creators, product-led sharing, and connected marketplaces. A coding agent can build the first version, and I still inspect the results and test the awkward requests myself. To start this week, I'd talk to one type of customer about the last time they dealt with the task. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP In this episode I speak with Nicholas Cole about the real value of everything you write on the internet. Cole has 15 years of experience as a nonfiction writer and ghostwriter, and he runs the SaaS platform Typeshare. He gives me a simple model with three tiers of content: commodity, personality, and original. He also explains the digital brain, which he calls your personal language model, and he shows how AI repeats your approved language at scale. By the end, you know how to judge the short, medium, and long-term value of a piece before you write it. Start Writing Online In 30 Days: https://startup-ideas-pod.link/ship30 Timestamps 00:00:00 – Intro 00:03:36 – POV is the Moat 00:05:40 – Language As Open Source 00:11:24 – Value Is Relative To The Reader 00:14:26 – Approved Language 00:17:43 – The Value of AI in Writing 00:22:09 – Commodity Ideas 00:24:23 – How To Set Up The System 00:27:58 – Ownership IS Association 00:33:56 – Build your Personal Data Set 00:39:53 – Branded Content vs Founder-Led Content 00:45:17 – What is Original Content? 00:46:35 – Writing Versus Short-Form Video 00:48:58 – Three Types of Hooks 00:49:50 – Timely Content vs Timeless Content 00:53:27 – Voice is 3 dialed settings 00:56:32 – Finding your Voice 01:00:49 – The Company Brain As The Moat 01:07:30 – Closing Thoughts Key Points A point of view creates the moat, because copycats must wait for your next idea. Content sits in three tiers: commodity, personality, and original. Each tier adds different leverage. Ownership equals association. Volume builds it, and personality details make it strong. Your life story is the unmade data set, so AI learns it only from your own writing. Every piece sits on a spectrum from timely to timeless, so match your expectations to the type. Humans do the thinking and the writing. Robots do the repeating and the remixing. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND COLE ON SOCIAL X: https://x.com/Nicolascole77 Youtube: https://www.youtube.com/@nicolascole77 Ship 30 for 30: https://startup-ideas-pod.link/ship30

In this episode, I talk with Ryan Vogel about Jev, a new type of AI built for classification. Ryan shows how Jev takes an input plus an output schema and returns a probability for each choice in about 200 milliseconds. He demos Jev sorting 1,700 emails for 18 cents total, then covers lead scoring, support routing, video clipping, and browser control. I push him on the startup angle: find a business with an expensive queue of incoming information and put Jev at the front of it. You leave with a clear mental model, real use cases, and a simple way to try it today. Links Mentioned: Jev/Typeface AI: https://typesafe.ai AI Gateway: https://vercel.com/ai-gateway Timestamps 00:00 – Intro 02:27 – What Jev Is and Why It Matters 04:32 – Email Triage Demo 07:19 – Jev as an AI Decision Maker 15:46 – How to Use Jev in a Business 20:48 – Startup Idea: Local Services Matching and Instant Quotes 22:51 – Use Case 1: Bitcoin Signal Test and Limits 24:03 – Use Case 2: Auto-Clipping Long Videos 25:27 – Use Case 3: Browser Control: Flight Pick in 7.1 Seconds 26:18 – How to Get Access 27:25 – Closing Thoughts Key Points Jev is a classifier: an input and an output schema go in, and a probability for each choice comes out. Ryan's demo scores 1,700 emails for 18 cents total. Each Jev query takes about 200 milliseconds, whatever the input and output structure. Use Jev at any point where a business makes fast, repeatable decisions on incoming data. Keep Jev in an advisory role, and save frontier models for high-intelligence tasks like trading. Instant access runs through the Vercel Gateway, and a waitlist covers direct access. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND RYAN ON SOCIAL X: https://x.com/ryanvogel Youtube: https://www.youtube.com/@vogeldev/videos

I sit down with Remy to go through Instinct, the new invite-only personal agent that runs inside iMessage. Remy shares his raw chat history on screen: a haircut booking in Copenhagen, a restaurant reservation, a Bali visa on arrival, and an Emirates Skywards sign-up. We cover the parts that impress us, the points where the agent hits a wall, and the privacy questions that stay open. By the end of this episode you understand what Instinct does today, and you get fresh ideas for personal agents in general. Timestamps 00:00 – Intro 02:08 – Instinct Pros 11:18 – Instinct Cons 13:16 – Simple Onboarding 15:19 – Tools and Connectors 17:43 – Example 1: Booking a Haircut in Copenhagen 20:24 – Example 2: Restaurant Booking and Calendar Entry 23:03 – Example 3: Bali Visa on Arrival and Emirates Skywards 26:00 – Closing Thoughts Key Points Instinct hides the agent complexity behind a phone number and iMessage, so a first-time user starts in seconds. Remy gets it to book a haircut, hold a restaurant table, file a Bali visa on arrival, and open an Emirates Skywards account. A spend-limited virtual card keeps the blast radius small when the agent pays for things. The agent stalls when a task needs a phone app or an Indonesian checkout page. Users report that Instinct keeps copies of email after they disconnect Google, so treat privacy as an open risk. The trusted person network lets one Instinct talk to another, which builds network effects into the agentic era. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND REMY ON SOCIAL X: https://x.com/remy_gaskell Youtube: https://www.youtube.com/@aiwithremy AI with Remy: https://www.aiwithremy.com/

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP I welcome Ras Mic back to the pod to explain the phrase "software factory." Mic shares his screen and walks through the exact system that he runs today. His factory has four steps: isolate, build, prove, and ship. He keeps the whole system in five or six markdown files, so it works with any model and any harness. By the end of this episode, you can boot up your own factory, run many agents in parallel, and trust the code that comes back. Create your own Software Factory: https://startup-ideas-pod.link/ras-software-factory Timestamps 00:00 – Intro 02:17 – Software Factory Definition 03:44 – Why the Software Factory Matters 05:23 – Step 1: Isolate With Git Work Trees 11:34 – Step 2: Build With the Code Structure Skill 14:48 – Step 3: Prove With Evidence-Driven Testing 22:25 – Step 4: Ship With Grep Loop and Greptile 26:52 – The Physical Factory Analogy 29:21 – A Software Factory Is Markdown Files 30:02 – Closing Thoughts Key Points A software factory is a workflow of skills and domain knowledge, so it runs with any model and any harness. Isolate: every feature starts in a fresh git work tree branched from origin main, so each agent keeps its own station. Build: a code structure skill makes the agent write service layer code that a human developer can read. Prove: the agent records a before state and an after state as video, screenshots, or numbers. Ship: Greptile scores the PR, and the agent loops back to build until it earns five out of five. Mic runs up to 15 features in parallel and reviews the visual proof instead of the raw code. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

I talk with Ras Mic about GPT-6 Astra. We skip the game demos and the 3D toys, and we focus on use cases to earn money or improve products. I share 9 Astra prompts that I posted publicly, and Greg Brockman reposted. Ras then shows his hardware project: he moved from a speaker idea to a parts list, a Blender layout, and merged code in about 30 minutes. The takeaway is simple: use this model for the ideas that felt too large for you last year. Timestamps 00:00 – Intro 01:53 – Astra Overview 04:14 – 9 Astra Prompts 11:48 – Jarvis Speaker Idea 16:21 – Think Bigger with Astra 18:29 – Vibe Coding to Vibe Manufacturing 21:16 – Closing Thoughts Key Points Astra costs more per task, and it uses fewer steps, so the value per dollar stays high. A performance audit moved one of Ras’s apps from 800 ms to 20–30 ms. A security audit on his live payments app found real risks in production. Ras went from a speaker idea to a $561 parts order and a merged pull request in about 30 minutes. Ras’s point: intelligence keeps climbing, and bravery stays flat. Ask for bigger things. The shift that vibe coding brought to software now reaches physical products. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

I run this episode solo. I explain local AI in plain terms: the model runs on hardware I control, and a cloud model runs somewhere else. I map the four pieces of the local AI landscape — the model, the warehouse, the software, and the workflow — and I define the words that beginners meet first: parameters, tokens, context window, quantization, and GGUF. I walk through the Google open model stack (Gemma 4, Google AI Edge, LiteRT-LM, AI Edge Gallery), compare the other open model families, and show three ways to run a model today. I close with a first workflow you can copy and three startup ideas that use local AI as the wedge. And a special thank you to Google for supporting the podcast. Timestamps 00:00 – Intro 01:35 – The Open Model the Landscape 03:09 – Vocab Decoder 06:48 – Google Gemma Clearly Explained 10:29 – Other Open Model Families 14:20 – Path 1: Run Gemma in LM Studio 18:17 – Path 2: Ollama 20:15 – Path 3: Google AI Edge 21:07 – Hardware Cheat Sheet 21:52 – First Workflow to Build 22:47 – Workflows Before Fine-Tuning 25:06 – Local vs Cloud vs Hybrid Eval 26:33 – Framework for Local AI Startup Ideas 27:22 – Startup Idea 1: Home Health QA Reviewer 29:24 – Startup Idea 2: Offline Field Report Copilot 32:10 – Startup Idea 3: Pre-Send Reviewer for Professional Services 34:47 – Build Your Local AI Lab 37:55 – Closing Thoughts Key Points Ask whether the model is good enough for the job, and the business opportunities become clear. Local AI has four pieces: the model, the warehouse (Hugging Face), the software (LM Studio or Ollama), and the workflow you build around them. Gemma 4 E4B is my practical starting point; E2B fits phones and older machines. Hybrid architecture wins: local does the private first pass, cloud does the heavy reasoning, and a human approves anything important. Start with one repeated workflow — one folder, one model, one output — and run it 10 times. I see a 24-month window to build local-AI-native software for verticals that still run early-2000s tools. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

On this solo episode, I review five free, open source GitHub repos that help you build products, make money, or save time: Peter Yang's No AI Slop Skill, the CRM by TryComp AI, Video Use by browser use, SkillSpector by NVIDIA, and Phone Harness. For each repo I explain what it does, why it matters, how to install it, and the first small workflow to try. I close with a simple three-step method: install the repo, make one small workflow work, then decide to productize it or keep it as your own leverage. Timestamps 00:00 – Intro 01:44 – Repo 1: No AI Slop 05:20 – Repo 2: Agentic-first CRM 10:52 – Repo 3: Video Use 15:15 – Repo 4: SkillSpector 18:49 – Repo 5: Phone Harness 22:25 – Closing Thoughts Links to repos: petergyang/no-ai-slop — https://github.com/petergyang/no-ai-slop trycompai/crm — https://github.com/trycompai/crm browser-use/video-use — https://github.com/browser-use/video-use NVIDIA SkillSpector — https://github.com/NVIDIA/SkillSpector phone-harness — https://github.com/ShawnPana/phone-harness The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode I explain a role that I call the marketing engineer. I believe this person becomes one of the most valuable hires in tech in the next 18 to 24 months. I define the job, I show the four eras of marketing that lead to it, and I give the tool stack that makes it work. I use a commercial HVAC software company as a worked example, and I list six systems that a marketing engineer builds. I close with four ways to earn money from this skill and a 30-day plan to learn it. Timestamps: 00:00 – Intro 01:46 – The Evolution of Marketing 04:29 – What is a marketing engineer 07:19 – Build the Growth OS 10:18 – Marketing Engineer Tool stack 13:23 – Live Data Workflow 14:32 – Agent Job Description 16:56 – Example: vertical SaaS for HVAC contractors 18:27 – System 1: Customer Truth 20:20 – System 2 - 4: Founder content, Outbound signal and Creative Testing 23:31 – System 5: AI search visibility and the growth cockpit 24:19 – System 6: Eval Loop 25:06 – Ways to Monetize 29:41 – The 30-day plan 32:24 – Closing Thoughts Key Points I expect the marketing engineer to command salaries from 250K to more than 1 million dollars. I build the growth repo first, because it holds the marketing memory of the whole company. I write a job spec for each agent, in the same way that I write a job description for a person. I measure qualified replies and pipeline, because business results show the true signal. I treat taste and judgment as the moat, because agents become a commodity. I recommend one working system over five half-built ones. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Vinny is back on the pod, and he explains WebMCP. WebMCP puts MCP tools inside the browser UI, so any agent that you bring can read a page and act on it. Vinny demos an espresso gear store where his agent compares two machines, checks the counter width, matches accessories, adds an item to the cart, and applies a coupon. Together we map the agent-native options, from headless APIs to in-app agents, and we place WebMCP in the middle of that map. I close the episode with two cash-flowing business ideas that a semi-technical founder can start today. Timestamps 00:00 – Intro 02:28 – WebMCP Clearly Explained 07:22 – Demo: Conditional Tools And Browser Session Login 09:11 – The Agent-Native Paradigm 12:12 – How Agents Interact with Apps 16:05 – Demo: Accessories, Cart, And Coupons 18:42 – Where WebMCP fits 21:03 – Startup Idea 1: WebMCP Conversion Agency 24:27 – Startup Idea 2: Agent Mystery Shopper 26:11 – Closing Thoughts Key Points WebMCP makes a website agent-readable and agent-actionable through a short, clear list of tools. The browser session carries the login, so tools stay conditional and the setup stays simple. The live store demo compares machines, matches accessories, adds to the cart, and applies a coupon. WebMCP sits between headless APIs and in-app agents, and it keeps the visual UI that most people prefer. Vince says WebMCP launched in February as a joint Microsoft and Google experiment in Chrome. The first markets: complex commerce, SaaS admin consoles, read-only flows in regulated industries, and internal tools. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VINNY ON SOCIAL: X/Twitter: https://x.com/hot_town Youtube: https://www.youtube.com/channel/UCHP5Hdx0X-sM0uv2bl_OOqg

On this week’s SIP Live we dive deep on the X timeline to give each post a sip or a skip, and we answer questions from the chat. This episode covers AI-native operations, a baby food app that earns a million dollars a month, iMessage agents, human customer support as a brand advantage, small teams, reading habits, and sales advice for builders. Listeners get concrete first steps, business ideas they can copy today, and two clear opinions on each take. Timestamps 00:00 – Intro 00:59 – Where an AI-Native Company Starts 04:48 – The $1M-a-Month Baby Food App 10:31 – An App Store for iMessage Agents 16:32 – Customer Support Is Eating Engineering 23:38 – RIP to the 2-Pizza Team 26:36 – Paul Graham on Reading as an Advantage 33:31 – The Worst Moves for 2026 37:01 – From Designer to Salesperson Key Points Make the company legible first: keep meeting notes and SOPs in files that an LLM can read. Let the team explore AI tools freely, then ask one department, such as admin, to lead. A million-dollar-a-month app leaves room for niche copies that earn 10K to 30K a month. Build loops that turn daily support transcripts into prototypes and measurable goals. Human support works as a marketing advantage, and premium buyers pay for it. Sales stays part of the owner's job, so learn the frameworks and start cold calling. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JONATHAN ON SOCIAL Unscheduled CEO Podcast: https://www.unscheduledceo.com/ X/Twitter: https://twitter.com/Jicecream LinkedIn: https://www.linkedin.com/in/jonathan-courtney-4510644b/

I sit down with Billy Howell for an inside look at a real business that runs on Grok Bot agent teams. Billy tests hundreds of tools for The Rundown, and he uses Grok Bot to run his local newsletter, The Arlington Bagel, which goes to 6,000 readers every Thursday. He walks me through his chief of staff bot, his research and sales agents, and the routines that move work forward while he sleeps. We cover the token math, the four-week plan he follows, and the business models that fit this tool best: newsletters, directories, and Shopify stores. You leave with a setup you can copy for one project this month. Timestamps 00:00 – Intro 02:22 – Grok Bot Overview 03:12 – What makes GrokBot special 06:09 – Pick one project 08:09 – Creating your initial agent team 11:19 – First week sprint with Grok Bot 13:06 – Automated Routines within Grok Bot 15:51 – Agent Org Structure 17:35 – Best Practices for building Agents 19:45 – Newsletter playbook 21:12 – Plugins 22:24 – Newsletter playbook pt 2 25:43 – Sales agent 29:06 – Iterating and Improving Agents 33:34 – Grok Bot business ideas 36:45 – Site stack builder 38:36 – Directories and landing pages 41:42 – One project for a month 42:50 – Closing Thoughts Key Points Keep one project per Grok Bot account, so context stays clean and tokens stay available. Start with a chief of staff bot, and let it audit your business and name the first three agents. Follow the four weeks: build the team, execute, hire and fire, then automate. Ask each agent for a five-line brief: what shipped, what is stuck, what needs you. Move repeatable steps into scripts or make com, and keep agent tokens for high value work. Newsletters and directories give the easiest entry, and the two models feed each other. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND BILLY ON SOCIAL: X/Twitter: https://x.com/billyjhowell Instagram: https://www.instagram.com/billyjhowell Tiktok: https://www.tiktok.com/@saasfatigue Youtube: https://www.youtube.com/@billyjhowell

Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP I talk with Remy, known online as AI with Remy, about agent skills and how to share them across a whole team. Remy explains that a skill is an SOP for AI: a markdown file that teaches Claude your exact way to do a task. He then shows his system. He keeps his team skills in one GitHub repository, and he installs that repository as a plugin in Claude Code and Codex. The result is one source of truth, automatic updates for everyone, version control, and company ownership of the work. Listen to this episode if you run daily tasks with agents and you want your whole team to get the same quality of output. Remy’s prompt + skill setup: https://startup-ideas-pod.link/Remy-skills Timestamps 00:00 – Intro 02:33 – Skills as SOPs for AI 04:27 – How the agent uses skills 05:13 – AI is single player 06:21 – Example Skills: Notion, Brand Voice, Email 08:07 – How to share skills 11:40 – What is a Plugin? 14:58 – Anatomy of a Plugin 15:30 – Version Control and Rollback 16:58 – A Second Repo for Personal Skills 18:29 – The Day Claude Deleted 150 Skills 20:02 – Skills as Company Assets 21:00 – A Web App on Top of the Repo 24:46 – How Many Skills to Build 27:00 – The Self-Improvement Loop 28:15 – Skill Maxxing 30:40 – Closing Thoughts Key Points A skill is a markdown SOP that teaches an agent your exact way to do a task. Most skills sit on one laptop, so a great process stays with one person. A GitHub repo plus a plugin gives the team one source of truth for every skill. Auto-update sends each skill edit to every teammate in Claude Code and Codex. A company-owned repo keeps the skills when a teammate moves on. Remy builds thin agents and thick skills, so any harness can run the same process. LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND REMY ON SOCIAL X: https://x.com/remy_gaskell Youtube: https://www.youtube.com/@aiwithremy AI with Remy: https://www.aiwithremy.com/

Get Claude Code: https://startup-ideas-pod.link/claude-greg In this solo episode I lay out the exact system I use to turn Claude Code into what I call an AI employee. My premise is simple: give Claude the same things you would give a person joining your company (a workspace, memory, a brief, a clear ticket, eyes, review, a schedule, and permissions). I build the whole setup live around a real idea I found on ideabrowser.com , a missed-lead responder for med spas, and I share the specific prompts I use at each step. By the end, the product, the customer feedback, the docs, the demos, the reviews, and the recurring work all live inside one operating loop. I close with a seven-day plan you can run at your own pace. And thank you to Claude and Anthropic for supporting the podcast. Setup Claude Code to be your 24/7 employee: https://startup-ideas-pod.link/Claude-code Timestamps 00:00 – Intro: The AI Employee Map 05:47 – Step 1: Creating The Workspace In Claude Desktop 14:53 – Step 2: The Brief And Plan Mode 18:08 – Step 3: The Ticket And Defining Done 22:15 – Step 4: The Eyes And Desktop Preview 26:13 – Step 5: Review In Layers And The Diff View 29:34 – Step 6: The Schedule And Routines 34:32 – Step 7: Parallel Agents And Worktree Isolation 39:14 – Step 8: Permissions: Safe, Ask First, Human-Owned 41:15 – Step 9: Skills, Connectors, And Hooks 44:28 – The Seven-Day Plan 47:42 – Closing Thoughts Key Points I treat Claude Code like a new hire: workspace, memory, brief, ticket, eyes, review, schedule, permissions. The repo brain teaches Claude how I work and what good looks like. Plan mode comes first: Claude reads the context, proposes an approach, and waits for my approval. One ticket at a time means one task, one finish line, and one reviewable change. The eyes matter: Claude opens the app in desktop preview, clicks the flow, checks the console, and reports what a buyer experiences. Routines and permissions turn a chat tool into a 24/7 operator with clear boundaries. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Allie K. Miller to talk about the shift from managing AI agents to enabling them. Allie runs a workforce of 34 AI agents led by an AI chief of staff named Simon, plus six directors named after Friends characters. She shares her three-word prompt, her daily AI diary, her AI watchdogs, and her rule to build the factory before the product. We then debate the future of software: why enterprises still want a vendor to call, and why consumer software now rewards taste and distribution. Listeners leave with one mindset shift and a first step they can finish in under three hours. Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP Timestamps 00:00 – Intro 02:29 – Become a Great Agent Manager 04:49 – The Three-Word Prompt 08:12 – The Pyramid of Proactivity 12:23 – Making the Company Queryable 19:14 – How to Design an AI Workforce 22:25 – AI as a Watchdog 24:56 – Startup Opportunities 26:29 – Build the Factory, Then the Product 30:09 – The SaaS Question 34:53 – Consumer Software as Art 37:12 – High-Value Bottlenecks 44:56 – Closing Thoughts Key Points Allie sits three rungs above her 34 agents. She sets the infrastructure and waits for escalations. Her strongest prompt runs three words on top of full business context: do smart things. She holds the risk tier steady and expands only the breadth and scope of agent work. A dictated daily diary captures the context that lives outside meetings, email, and Slack. AI watchdogs remain wide open: duplicate work, calendar conflicts, and meeting disagreements. The bigger play is a software factory. Build the primitives once, then ship each product faster. I see opportunity on both sides of software: enterprises want a vendor to call, and consumers reward taste. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ALLIE ON SOCIAL X/Twitter: https://x.com/alliekmiller Instagram: https://www.instagram.com/alliekmiller/ LinkedIn: https://www.linkedin.com/in/alliekmiller/

In this solo episode I break down Cloudflare's AI agent announcement in plain English and explain why I see it as the new business model for the internet. I walk through AI crawl control, pay per crawl, the monetization gateway, and the x402 payment rail, and I show how a single request turns into a transaction. From there I give three startup ideas built directly on top of this shift: a niche data refinery, agent readiness for businesses, and expert archives turned into agent tools. For each idea I lay out the wedge, the first customer, the first version, and how I would sell it. My core claim: the internet is moving from pages humans visit to resources agents use, and the builders who move now own the doors. Timestamps 00:00 – Intro 01:01 – The Old Paradigm of the Internet 02:57 – The New Paradigm of the Internet 03:41 – What Cloudflare is actually doing 06:33 – An AI Index for all our customers 07:34 – The Agent Internet Stack 09:09 – Why Now Is the Best Time to Build 10:29 – Startup Idea 1: The Niche Data Refinery 17:10 – Startup Idea 2: Agent Readiness for Businesses 23:43 – Startup Idea 3: Expert Archives as Agent Tools 30:36 – The Filter for Finding Ideas 32:33 – Closing Thoughts Key Points The human web monetized attention; the agent web monetizes useful resources, priced per request. Cloudflare's pay per crawl, monetization gateway, and x402 turn the HTTP 402 status code into a live checkout at the edge. Idea 1: refine one niche's messy data into clean fuel for agents, starting with 100 businesses in one city. Idea 2: sell agent readiness by showing a founder exactly what AI says about their company today. Idea 3: package an expert's archive into one job-specific agent tool the audience already wants. Every one of these works as a manual services business today and productizes as agent payments mature. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I bring Cody Schneider back on the show to build two marketing agents end to end, live. The first one monitors LinkedIn posts from creators in your category, scrapes everyone who engages, waterfalls those profiles into emails and phone numbers, and then runs cold email and LinkedIn DMs with an agent managing the replies. The second one turns internal conversations, sales calls, and podcast transcripts into a daily organic LinkedIn content engine across an entire team. Cody names every tool in the stack, shares the real infrastructure costs, and shows the actual terminal commands he runs in Claude Code. By the end you have two systems you can go set up today for your startup. Timestamps 00:00 – Intro 02:27 – Agent Number One: Cold Outbound Agent 04:26 – Finding Creators in Your Category on LinkedIn 09:09 – Apify Explained and the API Maestro Actors 10:59 – Extracting Engagers Live in Claude Code 12:59 – Agent Versus Automation 15:45 – Waterfall Enrichment: GitLeads, Apollo, Origami 17:13 – Compliance, Data Brokers, and What Stays Legal 21:40 – Waterfall Enrichment: Million Verifier and LeadMagic 25:38 – The Cold Outbound Infrastructure 28:33 – Software Factories and Marketing as Code 31:41 – Agent Number Two: The Organic LinkedIn Engine 39:34 – Earned Media Math at $22 CPM 42:31 – Closing Thoughts Key Points LinkedIn engagement is a hand raise, so it beats firmographics as a targeting signal. Ten to twenty source accounts give you roughly 80% surface area coverage of an industry. Waterfall enrichment moves cheapest to most expensive: GitLeads, then Apollo, then Origami or Prospeo. Roughly $200 a month covers sending software plus inboxes for about 10,000 cold emails. An agent here is plain code on a cron job with an LLM attached where judgment is needed. Organic content works best when it starts from real human source material like calls, Slack, and transcripts. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CODY ON SOCIAL: Cody’s startup: https://www.graphed.com/ X/Twitter: https://x.com/codyschneiderxx Youtube: https://www.youtube.com/@codyschneiderx

I go solo on this one to break down graph engineering, the term I keep seeing go viral on X. I define it in plain English: prompt engineering is how you ask AI a better question, context engineering is how you give AI better information, and graph engineering is how you design the work around the AI so it lives as a managed workflow instead of one giant chat. I walk through the vocabulary (jobs, arrows, state), separate knowledge graphs from agent graphs, and run a full worked example on whether to launch an AI bookkeeping product for Shopify merchants. Then I show three levels of implementation, from manual lanes on a whiteboard up to LangGraph and n8n, plus ready-made graphs for support, content, and code. You leave with a repeatable way to turn one AI workflow you already run into a map of steps, checks, handoffs, loops, and human approvals. Timestamps 00:00 – Intro 01:24 – Prompt Engineering, Context Engineering, Graph Engineering 02:50 – Chat vs Graph 03:35 – Defining Terms and Workflows 06:44 – Knowledge Graphs vs Agent Graphs 08:47 – When to use Graph Engineering 10:01 – Example: AI Bookkeeping For Shopify Merchants 13:22 – The Diamond Pattern Graph Visualized 15:10 – Three Levels of Implementation 17:14 – Customer Support Graph 18:45 – Content Creation Graph 19:30 – Coding Graph 20:42 – The Trap Of Oversized Graphs 22:22 – Building Your First Graph 24:53 – Closing Thoughts Key Points Graph engineering means designing the work around the AI: jobs connected by arrows, with shared state moving between them. Knowledge graphs help AI understand how information connects; agent graphs help AI understand how work should move. Reserve a graph for work with multiple steps, multiple sources, parallel paths, checks, risks, or approvals. Separate the writer from the checker, since a single model grading its own answer inflates confidence. Draw and run the graph manually first; add LangGraph, n8n, or Make com once the structure proves itself. Aim for the smallest graph that raises quality, and place the human gate where mistakes get expensive. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Vinny for a live tour of Buzz, an open source, agent-native chat app from Block built on an open protocol. Vinny makes the case that openness is the real story here: agents arrive as first-class teammates, the harness underneath each agent swaps freely between Claude Code, Codex, Goose, and open code, and your entire chat context travels with you through every swap. He demos real output, including a CRM app built with the Wasp full stack framework and deployed to Railway, plus a tweet leaderboard that pipes daily stats back into a channel through a public API. I press him for the honest state of the software and for the setup advice he actually uses day to day. By the end I share where I land on Buzz versus Slack, and why I think anyone building right now gains from putting their hands on tools like this. Timestamps 00:00 – Intro 02:57 – Agents as First-Class Team Members 03:49 – Swappable Harnesses Under Any Agent 06:55 – Audio Huddles With Agents 08:34 – Git, Feature Branches, and Parallel Worktrees 11:20 – Building a CRM App with Buzz and Agents 13:43 – Why This Matters 18:13 – Best way to engage with your Agents 23:53 – Shared Compute and Local Models 25:42 – Model Choice, Data Ownership, and Lock-In 27:36 – Context as the Foundation 29:39 – Setting Up Agents 31:21 – Skills and Speed 33:03 – Who Should Try Buzz Today 34:36 – My Take: Live in the Future 38:10– Closing Thoughts Key Points Buzz treats agents as members of your team, so one shared chat becomes the context layer for humans and agents together. The harness under any agent swaps freely, and every chat, project, and decision comes along for the ride. Globally installed agent skills stay available inside Buzz, so an existing Claude Code setup carries straight over. Agents branch, work in parallel worktrees, push to Git hosting on your own relay, and ship live apps end to end. Shared compute lets a small team run one local model on one machine and use it from many computers. Buzz sits in early preview today, which makes it a strong fit for solopreneurs and small teams iterating fast. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VINNY ON SOCIAL: X/Twitter: https://x.com/hot_town Youtube: https://www.youtube.com/channel/UCHP5Hdx0X-sM0uv2bl_OOqg

Cody Schneider is back on the podcast, and I ask him to lay out what a real marketing agent looks like once you get past the hype. He draws a hard line: an agent owns unified business data, runs on a cadence, and improves from the results it reads back. We use one concrete business as the sandbox — an AI-first product built on top of WordPress — and Cody walks the entire stack behind a Facebook ads agent that researches pain points, generates static and video creative, publishes through the Facebook Marketing API, kills the losers, and promotes the winners. You leave with a business idea, the exact infrastructure list, and the tools we use to run it today. Timestamps: 00:00 – Intro 01:54 – Defining a Marketing Agent 04:00 – Startup Idea: AI for WordPress 07:27 – AI-First Plugin Ideas: Yoast, WPForms, WooCommerce, Akismet 09:55 – The current state of Meta Ads 12:48 – Bundling the Stack and Choosing Channels 15:23 – Two creative pipelines: static and video 17:25 – The Data pipeline and warehouse 24:11 – Ad strategy 25:51 – Solving for Entropy 28:01 – Let the market pick the winner 34:26 – Closing Thoughts Key Points WordPress powers 43% of all indexed websites, which leaves a wide open lane for AI-first products built on that stack. A marketing agent earns the name when it owns live data, runs on a cadence, and learns from its own results. The infrastructure comes down to three pieces: a pipeline (Airbyte), a warehouse (ClickHouse), and cloud hosting (Heroku, Railway, or similar). Facebook's Andromeda algorithm reads your creative and your landing page, so the ad copy now carries the targeting. Fresh inputs — competitor ad libraries, YouTube transcripts, podcast transcripts — keep agent creative varied over time. Paid ads let you test a thousand angles and read the market's verdict inside 48 hours. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CODY ON SOCIAL: Cody’s startup: https://www.graphed.com/ X/Twitter: https://x.com/codyschneiderxx Youtube: https://www.youtube.com/@codyschneiderx

I welcome Ryan Carson back to the show to turn anyone into a world-class agent operator. Ryan spent 25 years founding companies, scaled Treehouse to around 110 employees and a million learners, and now runs Untangle, an AI divorce agent for family law firms, as a team of one while his revenue tracks toward 4x this month. He walks me through his full stack: running cloud agents in parallel, building automations that watch production and improve themselves, and shipping 22 to 40 PRs a day, often from his phone. We also get into keeping token costs sane through model routing and building a durable reputation by sharing your work on X. By the end, listeners hold a clear playbook to run agents, automate the busywork, and ship faster. Timestamps 00:00 – Intro 01:43 – The New Agent Paradigm 04:24 – Inside Ryan’s eight-screen desk setup 07:23 – Why Devin and cloud agents 10:00 – Everyone Is Now a Manager of Agents 13:15 – Local vs Virtual Development 14:50 – Agent Management System 24:22 – 3 Automations to build 32:54 – Self-improvement loop with Grace 34:38 – Token costs and model routing 40:33 – Building reputation on X 44:03 – Closing thoughts Key Points Ryan frames every knowledge worker as a manager of agents, and mastering that role is the new edge. Cloud VMs let Ryan run five to ten agents at once and ship 22 to 40 PRs a day. Roughly half of Ryan's work happens on his phone, which keeps his agents moving in real time. Automations like a production watchdog and a daily self-improvement loop hand Ryan a running summary of what matters. Model routing keeps costs in check: budget around $5k a month per employee and lean on cheaper fine-tuned models. Sharing your work publicly on X compounds into relationships and opportunities over time. Numbered Section Summaries Meet Ryan and Untangle Ryan Carson returns to walk me through his stack. He spent 25 years founding companies, scaled Treehouse to about 110 employees and a million learners, and now runs Untangle, an AI divorce agent for family law firms, solo, with revenue on track to 4x this month. The World-Class Agent Manager Ryan's core premise: everyone is now a manager of agents, and becoming the best in the world at it is the goal. He argues that managing agents makes you more technical over time, much like a skilled engineering manager. The Desk Setup and Key Security Ryan lays out eight screens, a 52-inch monitor, a UG Monk paper to-do system, a vertical mouse, and Whisperflow for voice. He stores all prod write keys in 1Password and hands them to agents only when a task truly calls for it, keeping production safe. Cloud Agents Over Local Machines Ryan explains cloud VMs: click a button, spin up a fresh environment, and run many agents in parallel while the code stays cleanly separated. He credits this shift for his 50x jump in output and urges builders to move work into the cloud as fast as they can. Staying Sane at 50x With 22 to 40 PRs a day, Ryan treats his job as making 10 to 20 high stakes decisions before lunch. He pins his most important threads, checks them on a roughly 25-minute cadence, and works from his phone so his agents keep moving. Automations That Run the Business Ryan shares three automations: an end-to-end signup test that browser-tests three times a week for about $60 in tokens, a 9am production watchdog that summarizes customer activity and links to real UI, and a daily self-improvement loop where an agent named Grace grades chats on a rubric and ships roughly three fixes a day. Token Costs and Model Routing After a $20k token month, Ryan settled on roughly $5k per employee plus heavy model routing, using cheaper fine-tuned models like SWE 1.7 for loop work. He favors independent agent labs such as Devin, AMP, Factory, and Cursor for affordable long-term engineering, while enjoying the subsidized Codex Mac app for everyday tasks. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND RYAN ON SOCIAL Ryan’s Website: https://www.ryancarson.com X/Twitter: https://x.com/ryancarson Untangle: https://untangle.us

I sit down with Vas from Varick Agents to map out exactly how to break into AI forward deployed engineering — and how to grow into a sharper FDE — in thirty days. We start from a single premise: every company can now buy the same frontier intelligence, so the real advantage moves to deployment. Vas traces the role back to Palantir, explains the judgment that decides where AI belongs, and lays out the audit → evals → deployment loop that turns raw models into measurable business value. He then hands over a full 30-day plan to build, harden, measure, and defend a production-grade agent, so you can do the job before you hold the title. The whole conversation stays tactical and grounded, with clear examples I can apply today. The FDE Blueprint: https://startup-ideas-pod.link/fde-starter Timestamps 00:00 – Intro 02:03 – What is an FDE 04:09 – How Palantir Popularized FDEs 06:16 – Deciding Where Intelligence Belongs  11:26 – What FDEs Earn 14:59 – Two Kinds of Judgment: Communication and Engineering 17:38 – How the Work Really Gets Done 20:40 – Audit, Evaluation, Deployment 22:56 – Which LLM to Choose 27:36 – Audit: Finding the Workflow Worth Rebuilding 31:47 – Evals: Turn non-determinism into evidence 32:57 – Deployment: Build on Existing Systems 38:59 – The 30-Day Plan Begins 49:13 – Final Thoughts Key Points Intelligence is now commoditized, so the real edge lives in deployment — the job of the AI forward deployed engineer. Vas traces the FDE role to Palantir, where engineers embed on-site, learn workflows, and customize the ontology per client. The strongest FDEs blend deep technical skill with consulting-grade communication — the rare "art plus science" combination worth up to a million dollars a year. The FDE loop runs audit → evals → deployment, and each improved workflow makes the next one clearer. Vas condenses a year of learning into a 30-day plan: build an agent, harden it, make it measurable, then defend it like an FDE The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VAS ON SOCIAL Varick Agents: https://www.varickagents.com/#hero-section X/Twitter: https://x.com/vasuman AI Forward Deployed Engineers: https://learn.varickagents.com/fde-in-30-days

In this episode I sit down with Corey Ganim to unpack what he calls the simplest way to earn money with AI in 2026: a $999 AI Tools Assessment for small business owners. Corey lays out his entire four-phase system, from a probing discovery call through an AI-assisted analysis in Claude, a stupid-simple client report, and a review call that turns roughly half of clients into implementation buyers. We walk through his full upsell menu, seven client-acquisition methods that run on zero capital and zero audience, and his AI Concierge retainer that earns him about $1,000 an hour. Anyone listening leaves with a copy-and-paste playbook they can adapt to their own city or industry. Checkout Corey’s AI Audit Template: https://startup-ideas-pod.link/ai_audit Timestamps 00:00 – Intro and the episode promise 03:48 – The full playbook preview 06:39 – Phase 1: the discovery call 08:27 – Phase 2: AI Analysis 12:11 – Phase 3: The Report 22:24 – Tool and Model Selection 23:39 – Phase 4: The Review Call 26:15 – The Upsell Services 35:52 – Finding Customers 49:16 – The AI Concierge retainer 58:46 – Final Thoughts Key Points The core offer is a $999, 45-minute AI Tools Assessment that prescribes 3–7 off-the-shelf tools, backed by a full-refund guarantee tied to finding at least five reclaimed hours per week. Fulfillment runs in four phases: discovery call, AI analysis in Claude, a templatized report, and a review call that converts about half of clients into implementation work. The report stays deliberately simple, with an executive summary, an effort-versus-impact matrix, quick wins, a four-day quick-start plan, and a clear ROI slide. The upsell menu spans process redesign, automation builds, knowledge systems, custom workflows, and full implementation, with lifetime value reaching $3K–$10K or more. Seven client-acquisition methods run on zero capital and zero audience, from local meetups and door knocking to agency partnerships and office hours. The AI Concierge retainer ($1,200–$2,000/month for two calls) creates recurring revenue at roughly a $1,000 hourly rate. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND COREY ON SOCIAL Youtube: https://www.youtube.com/@coreyganim X/Twitter: https://x.com/coreyganim

I sit down with Elie Steinbock to unpack loop engineering and how to run a business on loops. We start with the roots of the idea in the lean startup and Toyota's manufacturing, then move into practical, copy-ready workflows for SEO, Facebook ads, and product feedback. Elie walks through a live Google Search Console example on Draft Fantasy and shows how to set up an SEO loop that runs once a month for years. The core promise for listeners: hand repeatable business work to an AI agent that measures an objective metric and improves over time. By the end, you know how loops work and how to launch your first one today. Timestamps 00:00 – Intro and episode promise 02:54 – What is Loop Engineering 06:51 – Loops with AI agents: build and verify 11:17 – Example of Loop: SEO as an objective-metric loop 15:29 – Setting up the SEO loop and tools 25:27 – Cost and token economics 29:05 – The Paid ads loop 33:10 – The product feedback loop 36:25 – A minimal viable loop for every channel 39:21 – Closing Thoughts Key Points Loop engineering means giving an agent a task, an objective metric, and a stop condition so it improves on a schedule. The lean startup and Toyota's build-measure-learn cycle map directly onto AI agents. An SEO loop connects to Google Search Console and Data for SEO, then pushes rankings up month over month. These loops run cheaply — often a few dollars per monthly run — which beats the cost of an agency. The same pattern extends to Facebook ads, and a product feedback loop stands as the ultimate version. Start small with a minimal viable loop tied to a clear metric like impressions or ten likes. Numbered Section Summaries The Promise of Running a Business on Loops I open by asking Elie what listeners will walk away with, and he frames the whole episode: use loops to automate SEO, ads, and more. We agree the aim is clear, copyable workflows people can launch today. Where Loop Engineering Comes From Elie traces the recent buzz to Boris from Claude Code and Peter Steinberger, plus a joking tweet from his friend Dimitro about software that builds itself. He grounds it in the lean startup's build-measure-learn cycle, which itself grew from Toyota's lean manufacturing. Loops With AI Agents: Build and Verify Elie explains the agent version: a build step paired with a verify step and a clear stop condition. He uses Inbox Zero's evals as an example, where the agent keeps adjusting the prompt or model until accuracy passes 90%. The SEO Loop We dig into SEO as the flagship example, where Google ranking serves as a clean, objective metric. Elie describes a loop that runs once a month, learns from the last run via a markdown memory file, and steadily climbs the rankings. Setting It Up on Real Data Elie shows his Draft Fantasy Search Console, connects the agent to Google Search Console and Data for SEO, and runs the loop live in Codex. He shares the Atom Eve prompt as a deeper template people can copy. Cost and Token Economics I raise Ross Mike's skepticism about loop buzz and token spend, and Elie makes the case that an SEO loop stays cheap — often under five dollars per monthly run. He adds that Max-plan users have plenty of headroom, while tight budgets suit cheaper open models like GLM 5.2. Ads, Product Feedback, and the Ultimate Loop We move to a Facebook ads loop that tests copy and creative variants, favoring a mix of human hooks and AI optimization. Then Elie describes the product feedback loop — reading customer feedback, analytics, and logs to prioritize and ship — as the closest thing to a business that builds itself. Starting Small We close on the minimal viable loop: begin with one channel and a modest, verifiable metric like impressions or ten likes, then let it compound. Elie and I agree that every part of a business could sit on a loop, and starting one today makes for a low-risk experiment. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ELIE ON SOCIAL Youtube: https://www.youtube.com/elie2222 X/Twitter: https://x.com/elie2222

In this episode I bring Nick Vasilescu, co-founder of Orgo, back on the show to unpack the buzz around Grok 4.5. Nick makes the case for treating Grok 4.5 as a genuine AI co-founder inside harnesses like Hermes and OpenClaw, and he proves it live: spinning up cloud computers, wiring in tools, and building a full startup from idea to landing page to outreach. We race Grok 4.5 against GPT 5.6 Sol, tour Nick's agent stack, and talk through the cost paradox of a model this fast and cheap. Listeners walk away with a concrete playbook for standing up their own always-on agent today. Get Nick’s Agent Template Stack: https://startup-ideas-pod.link/nicks-stack Timestamps 00:00 – Intro 01:40 – Why Grok 4.5 release matters 03:39 – Automation versus a co-founder 05:16 – Setting up Hermes and Grok 4.5 on Orgo 09:01 – Why Orgo to manage Agents 11:23 – Grok 4.5 Cost discussion 14:02 – Grok 4.5 Fast Execution and Unlock 16:20 – The Agent tool belt 19:13 – X MCP for trends 20:37 – vidIQ for outliers and thumbnails 22:11 – Finding new startup ideas 26:15 – Grok 4.5 versus GPT 5.6 Sol 30:56 – Ranking and Reviewing the startup ideas 34:06 – The AI agency opportunity 38:46 – Thumbnails over Telegram 40:10 – Reviewing AI Agency Landing Page 41:58 – Vertical MCPs and agent startups 43:36 – Skill graph and the offer 45:25 – Reviewing the Thumbnail Generated 46:42 – Email Outreach Campaign 48:07 – Reviewing Market Insight 1-Pager 50:45 – From a Camry to a Ferrari 52:12 – Reviewing Cold Email Outreach Sequence 53:22 – Closing thoughts Key Points Grok 4.5 delivers Opus 4.8-level intelligence at a fraction of the cost and roughly 10-15x the speed of Fable. I learn to treat the model as a co-founder by handing it email, a phone number, a debit card, memory, and every connector that matters. Nick runs agents on Orgo cloud computers so they stay online, textable, and ready around the clock. Live, Grok 4.5 builds a landing page in about 40 seconds and wins on design and copy for me over GPT 5.6 Sol. The stack ships from idea to website, offer, thumbnail, and cold-email sequence in a single session. Nick's take: costs keep dropping while speed and intelligence keep climbing, so building your agent now compounds overnight. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com/

In this episode I sit down with Dan Shipper to see how he runs his work and personal life on OpenAI's Codex Desktop with the 5.6 model. He walks through his card-based email setup, daily feeds for his company and Slack, and the in-app browser that lets his agent collaborate with him inside tools like Proof. We build a small SaaS app live, called Turnaround, and use it to explore why maintenance is the real product in the AI era and where Codex-native software heads next. Along the way Dan shares his pirates-versus-architects framing, his approach to fine-tuning a copy-editing model, and the patterns — pulses, Mailroom, and router threads — that hold his system together. The throughline: pick one simple win, let context do the heavy lifting, and manage the system instead of running every task by hand. Learn how to get customers with AI Agents: https://startup-ideas-pod.link/GTM-agents-IB Timestamps 00:00 – Intro 01:16 – Codex and GPT-5.6 Overview 03:40 – Training your own model: the step after skills 04:49 – Automating Email, Slack, Meeting Notes with GPT-5.6 08:53 – Why GPT-5.6 sharpens the results 10:26 – The light bulb moment with Codex 15:05 – Building Turnaround live: a maintenance badge 18:00 – GPT-5.6 vs. Fable: A tier and S-plus tier 19:34 – LFG and goal: looping toward a finished build 24:28 – Huge Opportunity: Codex-native apps 29:33 – The design checkpoint and the "warm paper" quirk 31:32 – Local models 34:04 – From 70% to 100%: pirates and architects 37:22 – Mailroom: giving Codex its own email address 40:58 – Getting started: download, grant access, explore 43:07 – Record and Replay: turning tasks into skills 44:37 – Closing Thoughts: Start small and build over time Key Points Codex Desktop plus the 5.6 model runs as a full operating system for knowledge work — email, research, and building software from one surface. Context is the multiplier: an agent wired into your computer and the web turns every inbox and feed into cards with a clear next action. Maintenance is the real product in the AI era, now that anyone can one-shot a first version. Codex-native SaaS — software you and your agent share inside the in-app browser — opens a fresh category with healthier margins. A live build of Turnaround, a maintenance-status badge, reaches about 70% in one pass; an architect carries it the rest of the way. Start with one simple win, grow the system over time, and let curiosity lead the way in. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND DAN ON SOCIAL X/Twitter: https://x.com/danshipper Youtube: https://www.youtube.com/@EveryInc/videos Every: https://every.to/

In this solo episode I lay out why I believe building agents is the new SaaS: software is shifting from helping you do the work to doing the work with you. I walk through a full playbook — find a niche, pick a workflow with a paycheck attached, shadow the human, spec the agent, build the minimum useful version, sell a pilot like labor, then productize the repeatable parts. I share live market examples like Slang AI for restaurants and Same Day for home services, plus pricing models and a distribution strategy built on workflow teardowns. I close with a 30-day, zero-to-100 plan for launching an agent-first business. This one is for anyone eager to build with AI or simply become more productive. Timestamps 00:00 – Intro 01:38 – Building Agents is the new SaaS 04:11 – Pick a valuable workflow 06:12 – Shadow the Human First 09:34 – Build the Minimum Useful Agent 12:50 – The wrapper makes it SaaS 15:50 – Sell the Pilot Like Labor (and Pricing) 18:37 – Own the workflow 21:45 – The Zero-to-100 Plan in 30 Days 24:14 – Closing Thoughts Key Points Agent SaaS sells work as a service; the product is the job itself, priced like labor. Start with a workflow that already carries a paycheck: high frequency, clear finish line, existing software, learnable edge cases, and felt pain. Shadow a human across 10–20 real jobs before you write a single prompt — the detail is the product. Ship the minimum useful agent — draft-and-approve, triage, coordinator, or bounded action — and earn autonomy over time. The wrapper (logs, approvals, evals, analytics) creates trust and turns automation into real SaaS. Win distribution with workflow teardowns: show the old way, show the agent way, sell the painkiller. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I lay out the six skills I believe stay valuable as AI grows more capable. I chose these six because each one is open to anyone, each one starts this weekend, and each one rises in value as AI improves. I walk through agents and local models, distribution, robotics, curation, the builder distributor, and IRL community building, with one concrete first rep for every skill. My goal is to hand you one simple, clear map of where the world is heading and exactly how to begin. Timestamps 00:00 – Intro 00:57 – Skill 1: Running AI Agents and Local Models 04:51 – Skill 2: Marketers Who Build Distribution 09:03 – Skill 3: Robotics Engineers Who Build and Source Hardware 14:29 – Skill 4: Curators Who Yap and Make Short-Form Video 19:05 – Skill 5: The Builder Distributor 23:11 – Skill 6: IRL Community Builders 27:34 – Build Your Skill Stack Key Points I chose these six skills because each one rises in value as AI improves. Skill 1 is the grown-up version of prompt engineering: I design an AI worker with context, tools, memory, permissions, and a goal. Distribution beats posting, so I learn where attention already lives and turn it into trust before I sell. Hardware is the new frontier: cheap arms, open-source robot learning, and supplier sourcing put robotics within my reach. As the builder distributor, I ship the product and win the attention in one loop, which makes the one-person company real. Real rooms grow scarce and valuable, so I build belonging, trust, and context as my edge. Numbered Section Summaries The Premise: What Stays Valuable as AI Improves I open by picturing a near future where AI builds and writes almost anything, then ask which skills hold their value. I narrow it to six skills that anyone can start this weekend, each one climbing in value as AI gets better. Skill 1 — Agents and Local Models I describe the move from typing prompts to designing a small AI employee with context, tools, permissions, memory, a goal, and a way to check its own work. I add local models with tools like Ollama and LM Studio so you learn which jobs want a giant brain and which jobs want a reliable worker, and I suggest building a daily briefing agent with three sources as your first rep. Skill 2 — Marketers Who Build Distribution I explain that distribution runs far deeper than posting: it means knowing where attention already lives and the exact words people use to describe their problem. The winning marketer becomes part researcher, storyteller, media operator, and community builder, and the first rep is a distribution map plus 20 hooks for a single idea. Skill 3 — Robotics Engineers Who Build and Source Hardware I share my big insight: the last decade rewarded moving pixels, and the next decade rewards moving atoms too. With cheap cameras, low-cost arms like the SO-100 / SO-101, open-source work like Hugging Face LeRobot, and small VLA models, I suggest assembling a low-cost arm, teaching it one boring task, documenting every failure, and learning supplier sourcing on Alibaba. Skill 4 — Curators Who Yap and Make Short-Form Video I cover the curator who watches the timeline and says "this matters because…," translating new models, launches, and news for a specific niche. The algorithms reward raw, authentic yapping that carries a real take, and my rep is a seven-day curation sprint paired with a taste file of hooks, analogies, and titles you love. Skill 5 — The Builder Distributor I make the case that AI compresses the old build-versus-sell split into one person who prototypes the product, writes the launch thread, records the demo, DMs the first users, and iterates. The loop is the whole game, and my rep is a 48-hour loop: build the smallest version of one problem, then create 10 pieces of distribution before you feel ready. Skill 6 — IRL Community Builders I close with the old-school skill that grows more valuable as work moves to agents and feeds: real rooms full of ambitious people. Scarcity moves toward belonging, trust, and context, so I suggest hosting six to eight people around one sharp question and sending a recap that turns the room into a network The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this episode I sit down with Amir to get tactical about running local AI models as part of a daily workflow. We center on GLM 5.2 from ZAI, how it stacks up against frontier models like Opus 4.8, and how a fusion approach lets you sequence a heavy thinking model with a lighter execution model for the best output at the lowest cost. Amir walks through setup in Cursor and Codex via OpenRouter, shares real token-cost math, and demos GLM 5.2 refining a live app. By the end you will know how to start today, where local models shine, and how model chaining keeps spend in check. Timestamps 00:00 – Intro 02:09 – GLM 5.2 and Z AI 04:01 – Specs: 1M context and Terminal Bench 2.1 05:22 – Making sense of benchmark scores 06:42 – Setup in Cursor or Codex with OpenRouter 10:18 – Local model upside: buy a machine, run tasks 11:42 – Token cost: 44 cents versus $2.38 13:36 – Future-proofing with an upfront hardware bet & The Uber subsidy analogy 16:49 – Model chaining and the vision workaround 19:23 – Token maxing vs routing tasks to the right model 20:54 – Answering the "cost is irrelevant" crowd 21:59 – Closing thoughts Key Points GLM 5.2 ships with a 1M-token context window and scores 81 on Terminal Bench 2.1, landing about four points behind Opus 4.8. A fusion approach (a term OpenRouter coined) sequences models: plan with Opus, execute with GLM 5.2, review with Composer 2.5 or Codex 5.5. Running GLM 5.2 in the cloud through OpenRouter costs roughly 44 cents for a task that runs about $2.38 on Opus 4.8 — close to a 5X saving. You can start today with credit-based access: load $20 in OpenRouter and route tasks to the right model. For images, Amir uses Opus 4.8 to read screenshots and describe them, then hands the layout to GLM 5.2 to act on. Teams are shifting from token-maxing to output-maxing, making model governance and chaining the smart play The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND AMIR ON SOCIAL Humblytics: https://humblytics.com/?via=community X/Twitter: https://x.com/amirmxt Youtube: https://www.youtube.com/@amirmxt

In this episode I sit down with George Lampropoulos, a 19-year-old founder who turns AI-built mobile apps into real revenue. George walks through his framework for reaching $10K a month—roughly $333 a day—starting with a simple, sellable idea you actually care about and ending with a distribution plan anyone can run. He shares the numbers behind WrestleAI (100K-plus downloads and close to $200K in revenue) and explains why a sharp "gotcha feature" and a clean Instagram funnel do most of the heavy lifting. We also dig into closing influencers, hiring a VA, running paid ads, and reading the metrics that decide whether you grow. If you want a practical, founder-tested playbook for building apps with AI, this one delivers. George’s $10K/mo app playbook: https://startup-ideas-pod.link/George-app-playbook Timestamps 00:00 – Intro 01:54 – George's track record with WrestleAI 02:36 – How AI unlocks fresh app ideas 06:29 – Reverse-engineering a viral idea from your feed 16:16 – Designing the UI/UX of the app 17:49 – The gotcha feature that sells the app 21:25 – Onboarding that converts 23:04 – Actionable Plan to $10k/mo 28:55 – Outreach as a numbers game 33:35 – Paid ads clearly explained 36:20 – Reading metrics: conversion, ARPU, retention 38:30 – TLDR: a great product earns inbound creators 39:51 – Answering the vibe-coding skeptics 39:51 – Scaling with vibe-coded app 43:35 – Why now is the app-building boom 46:05 – Closing Thoughts Key Points I learn why a simple, sellable idea you're passionate about beats pure distribution every time George breaks down the "gotcha feature"—one feature so clear that five seconds explains the whole app We cover a clean Instagram page that doubles as a sales funnel and as social proof for recruiting creators George shares his influencer playbook: lead with relationships, close on a call, and aim for a $2 CPM I get his paid-ads starter method—5 to 15 creatives, $100 a day, then keep the winners. George explains the metrics that matter early: conversion rate, a $2 ARPU target, and retention The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND GEORGE ON SOCIAL X/Twitter: https://x.com/GeorgeLampro20

In this solo episode, I walk through the implications of the ban of Claude Fable 5 — the most powerful model on the planet and the one I planned to build with — after the US government sent Anthropic a letter. I make the case for local AI by walking through the benefits: intelligence that lives on your own hardware, stays private, runs free after the hardware cost, and keeps working through bans, outages, and price hikes. I lay out the exact order I'd learn it in — runtimes, model-to-hardware matching, quantization, and agents — and I name the specific tools and models I reach for. Then I hand you five startup ideas that exist precisely because intelligence now sits on your desk. The payoff for you is a clear plan to own a resilient layer of your stack starting this week. Timestamps 00:00 – Intro 01:20 – The Fable 5 Ban 02:31 – Renting Access vs. Owning Intelligence 03:41 – How a Local Model Works 07:19 – The Local Model Stack 08:45 – Match Model to Machine 10:45 – Pick Your Model (Qwen 3, DeepSeek, Gemma, Llama) 13:09 – Quantization Explained 14:36 –The Local Agent Loop 17:45 – Model Routing (The Real Skill) 18:44 – Five Startup Ideas for the Local-AI Era 22:17 – Closing Thoughts Key Points One government letter took Fable 5 offline overnight, which is why I now own a private layer of my stack. Local models already handle roughly 80% of everyday ChatGPT or Claude tasks, fully offline and free after hardware. I'd learn it in order: runtime first (LM Studio or Ollama), then match model size to your RAM. A 12-billion-parameter model on 16 GB of RAM is the sweet spot where most people should live. Quantization (look for Q4) roughly halves the memory a model needs while keeping quality high. Pointing an agent like Hermes at a local model turns your desk into a private, always-on mini data center. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Get my Fable 5 prompt pack: https://startup-ideas-pod.link/fable5-prompt-pack In this episode I break down how to get the most out of Fable 5, the most powerful model I've ever used. I move past the benchmarks and go straight into tactical use cases, copy-and-paste prompts, and startup ideas you can build today. I walk through tournaments for copy and landing pages, an interview-before-build workflow that hunts for product-market fit, and ways to point Fable at contracts, churn data, and years of your own notes. I close with three of my favorite startup ideas — a synthetic focus group firm, 48-hour custom software, and a contract refund firm — plus the exact prompts behind each. My goal here stays simple: leave you ready to build and earn with Fable 5 while it remains included in your plan. Timestamps 00:00 – Intro 02:22 – Anthropic Employee Edits a Launch Video With Fable 05:50 – Building an AI Content Engine 07:30 – Best way to configure Fable 5 08:42 – Prompt 1: Copywriting Tournament for Landing Pages 13:18 – Prompt 2: The Interview-Before-Build Prompt 18:34 – Prompt 3: Hire Fable to Kill Your Company 20:18 – Prompt 4: Your One-Page Operating Manual 21:20 – Prompt 5: Find the Gaps Worth Filling 22:06 – Prompt 6: Negotiation Simulator 23:11 – Prompt 7: The 80-Page Second Opinion on Contracts 24:56 – Prompt 8: Make Fable Build Its Own Tools 25:47 – Startup Ideas 31:23 – Closing Thoughts Key Points I show why low effort is the alpha, since Fable Low beats Opus High on routine work. I run tournaments — landing pages and ad copy scored by AI judge panels — to ship far stronger output. I use an interview-before-build prompt so Fable pushes back and writes specs with real product-market-fit odds. I point Fable at big datasets — contracts, churn data, support tickets, years of notes — to surface money and patterns. I share startup ideas Fable 5 makes viable today, including a synthetic focus group firm and a contract refund firm. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

S/o Coderabbit for sponsoring today’s vid: https://startup-ideas-pod.link/code-rabbit On this episode I sit down with Professor Ras Mic to break down agentic loops. We define what a loop is, explain why well-known builders like Boris and Peter swear by them, and stay honest about who they truly serve. Mic argues that human-in-the-loop remains the strongest setup today, and he walks through the one loop he runs every day for code review using Cursor, GitHub, and Greptile. By the end you will know when a loop earns its place and when your own hand belongs on the wheel. Timestamps 00:00 – Intro 01:23 – What is a Loop 07:59 – /goal Explained 11:32 – The Slop Machine 12:42 – Code Review as a use case for Agentic Loop 18:19 – Honest Take for Builders 20:42 – The Future of Loops 21:50 – Closing Thoughts Key Points A loop fires once from a human, then the agent generates, reviews its own result, and feeds it back to keep building. Human-in-the-loop keeps you directing, governing, and approving each step while the agent builds. Wide-open loops make heavy assumptions and burn serious tokens; Michael cites Peter's tweet about $1.3 million worth of tokens in one month. Reserve slash goal and similar loops for the $200/month plan, since the $20 and $100 tiers burn through fast. Loops shine in confined, fixed-feedback work: code review, SEO pages, and other binary tasks. Mic’s daily win is a closed code-review loop with Cursor, GitHub, and Greptile that chases a 5/5 score. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

Become an AI Native Organization: https://startup-ideas-pod.link/ai-native-org In this episode I sit down with Theo to unpack what becoming AI native truly means. We define an AI native org as people managing agents, agents reading and writing to the company, and the company growing smarter over time. Theo opens his actual workflows, walking through a working prototype, an auto-generated client proposal microsite, and a live usability test that synthesizes feedback into a V2 in one session. We close with service-business startup ideas built on this same system, plus a free consultation offer for larger companies. For founders and operators, the value lands as a concrete playbook for turning speed into customer signal and a durable moat. Timestamps: 00:00 – Intro 04:09 – The Demis Hassabis origin story 06:53 – Defining AI Native Organization 08:19 – Mapping the system: people, agents, context 09:18 – Why people lead: strategy, taste, trust 13:23 – Agents: models using tools in a loop 16:12 – Evals and defining "good" 17:34 – Skill chains explained 20:06 – Proposal skill-chain demo setup 25:48 – Proposal microsite walkthrough 30:46 – Building the Daily Blitz feature demo 32:50 – Context as the foundational layer 41:07 – Daily Blitz ships and the labs page 43:47 – Bootstrapping context with a small team 46:21 – Usability test and live feedback 51:18 – Startup ideas: productize the system 54:28 – Closing Thoughts Key Points An AI native org runs on three layers: people for judgment, agents for execution, and context as the shared brain. Everyone becomes a manager, so I set each agent up with a clear goal, the right skills, tools, and context. Skill chains fire playbooks back to back, lifting quality and keeping outputs grounded in real data. A living context layer gives agents 2020 vision, letting a personalized proposal ship in minutes. Live prototypes plus built-in usability tests turn raw ideas into customer signal the same day. The fastest service play right now: niche down by industry, function, and company size, then sell this system. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND THEO ON SOCIAL X/Twitter: https://x.com/TheoTabah LinkedIn: https://www.linkedin.com/in/theotabah/ LCA: https://www.latecheckout.agency/

In this episode, I sit down with Alex Finn for a full, screen-shared walkthrough of Hermes Desktop, the new desktop home for the Hermes AI agent. I open with a clear challenge: by the end, sell me on installing Hermes Desktop, show me real ways to make money and stay productive, and explain his move from OpenClaw. Alex tours every major surface — sessions, profiles, artifacts, skills, cron jobs, and sub-agents — and shares money-saving tactics at each step. We close on the idea that matters most to me: aiming these agents at other people's challenges as the clearest path to real value. Timestamps 00:00 – Intro 04:04 – Sessions and Context Management 06:10 – Profiles Explained 08:49 – Model-Based vs Role-Based Profiles 12:58 – Artifacts as a Second Brain 14:32 – Why Alex Switched From OpenClaw 17:32 – Skills, Tools, and Tool Sets 19:19 – Messaging and Cron Setup 21:44 – Reverse Prompting and the Brain Dump 28:09 – Sub-Agents vs Profiles 32:12 – Putting It Together: Solving Challenges 32:38 – The Daily Business Opportunity Scan 37:05 – Local Models: Mac Studio vs DGX Spark 39:03 – Reframing Cost as Investment 41:59 – The Real Way to Make Money With Hermes 42:51 – Closing Thoughts Key Points Hermes Desktop pulls sessions, profiles, artifacts, skills, and cron jobs into one polished, Apple-style interface. Smart session and context management keeps each message slim and keeps monthly costs low. Profiles map to different models — Opus 4.8 for strategy, ChatGPT 5.5 for coding, a local Qwen model for free research — so each task runs on its best fit. Reverse prompting plus a personal brain dump produces far stronger prompts, cron jobs, and outputs. Sub-agents handle one skill across many parallel tasks; profiles handle work where each step needs a distinct skill set. The biggest opportunity: aim your agent at Reddit and X to surface real problems you are positioned to solve. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ALEX ON SOCIAL Youtube: https://www.youtube.com/@AlexFinnOfficial/videos X/Twitter: https://x.com/AlexFinnX Creator Buddy: https://www.creatorbuddy.io/

In this solo episode I walk through Codex Sites end to end, building a real internal tool live so you can copy the exact workflow. I open by comparing Codex Sites with one-prompt tools like Replit and Lovable, then construct a Startup Ideas OS board in six prompts. Along the way I cover memory and persistent storage, safe actions, Codex skills, save-gates, and proving the loop so the app updates autonomously. The core promise: by the end you know how to ship a Codex Site that an agent keeps operating for you. This one suits builders who already live in Codex and want self-updating products. Timestamps 00:00 – Intro and Episode Agenda 01:17 – Codex Sites vs Replit and Lovable 04:33 – The Build Plan: Startup Ideas OS 05:08 – Prompt 1: Build the Shell with Sites 07:02 – Plugins Worth Using and Game Studio 08:54 – First Board Review 09:21 – Prompt 2: Add Memory and Show the Data Model 10:56 – Prompt 3: Create Safe Actions 13:25 – Prompt 4: Create the Startup Ideas Admin Skill 14:51 – Prompt 5: Save-Gate and Checkpoints 16:29 – Prompt 6: Prove the Loop from a New Chat 18:10 – Publish, Auth, and Live Updates 20:28 – TLDR: Memory, Safe Actions, Skills 22:40 – The Real Unlock and Closing Thoughts Key Points Codex Sites rewards builders who already live in Codex by updating apps autonomously after launch. Replit, Lovable, and Bolt stay the simpler one-prompt choice; Codex Sites trades that for autonomy and self-updating products. Out of the box you prompt in auth, databases, payments, email, analytics, and a secrets vault yourself. I build a Startup Ideas OS board in six prompts: shell, memory, safe actions, a skill, a save-gate, and a proof loop. Safe actions let an agent call approved buttons and named mutations, so edits flow from any chat. The real payoff is autonomous products that Codex keeps operating and improving on a live URL. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this solo episode, I break down the shift from a human-first internet to an agent-first one, where AI agents become the customers that discover, evaluate, pay, and recommend. I map the agent buying journey and the new infrastructure agents need: identity, tools, an inbox, memory, a wallet, and receipts. I ground it with concrete examples like AgentMail and Stripe's agent wallet, then show how to make your website agent-readable through structured docs, schemas, MCP tools, and executable actions. I close with rapid-fire startup ideas and my big prediction for the next ten years: build startups for agents. Timestamps: 00:00 – Intro 00:49 – The tweet: build startups for agents 01:47 – Old web vs. agent web 02:24 – The agent buying journey 04:38 – What agents need: identity, tools, inbox, memory, wallet, receipts 05:30 – Examples: AgentMail, Stripe agent wallet, support, procurement, MCP, travel agent 08:24 – Building an agent-readable website 09:31 – What does this change for Startups 11:55 – Rapid-fire startup ideas for agents 13:07 – Closing Thoughts Key Points I explain that AI agents are becoming the primary customers online, with agent traffic set to outnumber human traffic. I lay out the agent buying journey: finding, evaluating, transacting, using tools, and recommending to other agents. I list what agents need beyond what humans need: identity, tools, an inbox, memory, a wallet, and receipts. I walk through real examples like AgentMail, Stripe's agent wallet, support, procurement, MCP servers, and a travel agent. I show how to make a site agent-readable with structured docs, schemas, MCP tools, SDKs, OAuth, checkout, sandboxes, and receipts. I share rapid-fire startup ideas for the agentic era and frame my big prediction: build startups for agents. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Live from Google I/O, I sit down with Logan Kilpatrick from the Google DeepMind team to unpack everything Google just announced and what it means for founders, developers, and anyone trying to build with AI right now. We dig into Gemini 3.5 Flash, the new Gemini Omni world model, the expanded Antigravity ecosystem, managed agents in the Gemini API, and the native Android app builder inside AI Studio. Logan breaks down how distillation is pushing Pro-level intelligence into Flash, where the biggest opportunities are for solo founders, and why the agentic era has finally moved from impressive demos to genuinely useful products. Thanks to Google for flying me out to Google I/O and making this conversation possible. Timestamps 00:00 – Intro 00:53 – Gemini 3.5 Flash: The New Workhorse Model 01:49 – How Flash 3.5 Stacks Up Against Sonnet 02:38 – Gemini Omni: A World Model for Any Input and Output 06:18 – Building a Content and Creator Layer on Omni 08:21 – What to look forward to 10:53 – Google Spark and Managed Agents 14:00 – The Agentic Era and Requests for Startups 17:17 – The Antigravity Ecosystem Overhaul 18:51 – AI Studio vs. Antigravity: Vibe Coding vs. Agentic Engineering 21:31 – Native Android Apps Built Inside AI Studio 23:44 – Closing Thoughts Key Points Gemini 3.5 Flash ships as a Sonnet-level workhorse model tuned for long-running agentic tasks, coding, and tool use, available on day one to 900M+ Gemini app users. Gemini Omni is a single model that takes any input and produces any output across video, image, audio, and music, fusing Veo, Nano Banana, Lyria, and TTS into one system. Managed agents in the Gemini API let builders ship agentic products with a single API call, using skills and markdown instead of writing orchestration code. The Antigravity suite now spans an IDE, agent manager, CLI, SDK, and API surface, all sharing the same agent harness that powers Gemini Spark. AI Studio targets vibe coding and now builds native Android apps for free, while Antigravity targets production-quality, million-line-codebase engineering. The cost of intelligence keeps dropping thanks to distillation, opening up smaller markets that previously needed a 40-person team and venture funding to address. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND LOGAN ON SOCIAL X/Twitter: https://x.com/OfficialLoganK Youtube: https://www.youtube.com/@LoganKilpatrickYT LinkedIn: https://www.linkedin.com/in/logankilpatrick/

I sit down with my friend Jonathan Courtney, a.k.a. Jicecream, to dig into the 9 biggest startup opportunities I see right now across B2C, AI, mobile, and IRL. We each pick ideas, trade reactions, and pressure-test them live. The conversation ranges from agent-first "action apps" to elder tech, third spaces, hobby retreats, pet health, AI-native media, and the case for selling AI "junior employees" to small businesses. Listeners walk away with a concrete map of where to build in 2026, plus the framing I use to decide which niche is worth marrying. Timestamps: 00:00 – Intro 01:14 – Idea 1: Unscripted Creator Shows (Twitch model for tech) 07:50 – Idea 2: Action Apps: AI Agent Native Apps 16:39 – Idea 3: Loneliness and IRL Communities 26:47 – Idea 4: Elder Tech: Building for 65+ 33:21 – Idea 5: Adult Hobbies 38:17 – Idea 6: AI Employee and AI Agents 45:33 – Idea 7: Personalized Nutrition/Health 53:08 – Idea 8: Pet Health and AI for Animals 57:34 – Idea 9: AI-Native Media Companies Done Right 01:03:18 – Stacking Ideas: Live + Retreats + Entrepreneurs 01:07:22 – Final Thoughts The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JONATHAN ON SOCIAL Unscheduled CEO Podcast: https://www.unscheduledceo.com/ X/Twitter: https://twitter.com/Jicecream LinkedIn: https://www.linkedin.com/in/jonathan-courtney-4510644b/

Nick agreed to personally set up your Orgo in a 15 min call: https://startup-ideas-pod.link/orgo_ai I sit down with Nick from Orgo to break down exactly how to run a one-person AI agent business that can realistically clear a few million dollars a year. Nick walks through the offer, the verticals worth chasing, the full software stack, and the live setup of an agent that manages other agents. We focus on tactics over theory, with specific tools, pricing, and the playbook for landing customers as a solopreneur. By the end, anyone with solid AI fluency will have a clear path from offer design to fulfillment. Timestamps 00:00 – Intro 02:54 – Designing the AI Agent Business Offer 06:38– Selling an AI Employee, Not an Agent 07:26 – Industries to Target (and Two to Avoid) 14:54 – Content Is Overpowered and How to Get Customers 17:51 – The Customer-Facing Tool Stack 20:49 – Building Agents Stack 25:51 – Model Picks: GPT 5.5, GLM 5.1, Kimmy, Opus 4.7 27:08 – Nick’s Stack 28:14 – Why Obsidian Is the Second Brain Layer 30:22 – Live Walkthrough: Spinning Up a Cloud Computer in Orgo 33:53 – Cloud Computers vs. Mac Minis 38:37 – Building Agents and Structuring Workspaces for Customers 43:56 – Watchdogs, Observability, and Reliability 45:28 – Closing Thoughts on the Solopreneur Era Key Points Sell unlimited agents, unlimited usage, and unlimited support to remove friction; most customers actually use one to three agents. Avoid healthcare and finance to start; focus on legacy verticals like marketing, law, insurance, manufacturing, wholesale, and real estate. OpenClaw agents go for around 5K a month; Hermes agents can go for 10K a month. The full stack: Granola, Trello, Loom, Superhuman, Asana, Codex, Hermes, Orgo, Composio, Agent Mail, and Obsidian. GPT 5.5 is the recommended default model for tool calling; GLM 5.1 and Kimmy work for lighter tasks; Opus 4.7 fits long-horizon coding. Use agents to set up other agents — pair Cloud Code or Codex with MCPs like Perplexity, Context7, and X MCP for live docs. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com/

Get started building your tiny AI Agent business with Genspark Claw: https://www.genspark.ai/?utm_source=po&utm_campaign=GregIsenberg In this solo episode, I share seven tiny, cash-flowing startup ideas you can build with AI in just a few prompts. I walk through how to use Genspark Claw, Genspark's new in-the-cloud agent product running Sonnet 4.6, and demonstrate two ideas I have already built (a dead domain flipper and a local restaurant liquidation broker), build a third idea live on camera (a hiring-signal cold outreach machine), and hand you a five-step framework for generating your own ideas. The goal is simple: give you the creative juices, the framework, and the practical know-how to ship a $200-$1,500/day business with AI as your employee. Timestamps 00:00 – Intro 01:28 – Idea 1: The Dead Domain Flipper 06:19 – Idea 2: Local Restaurant Liquidation Broker 11:03 – Idea 3: Hiring-Signal Cold Outreach Machine (building live) 14:30 – Prevent Sleep, Heartbeat, and Treating Genspark Claw Like an Employee 15:52 – Skills, Local File Access, and What Else Genspark Claw Can Do 17:24 – Reviewing the 14 Personalized Cold Emails It Wrote 20:35 – More Ideas: Buy-or-Build Memos, Dead Product Hunt SEO, Forgotten Apps 24:18 – Framework for finding ideas: Public Data, Neglected Assets, Clear Buyer 26:33 – What Else Comes With Genspark AI Works Base 4.0 Key Points Tiny, boring, cash-flowing ideas beat billion-dollar ideas when you want to ship this month. GenClaw plus Slack turns Claude Sonnet 4.6 into an always-on AI employee for around $25/month. The repeatable pattern is: messy feed → mispriced asset → trigger event → obvious buyer → liquidity point. Three hunting lenses: places of constant change, things people ignore, and assets with clear urgency and spread. Talking to your agent in plain English ("strip the HTML entities, make the budget $2,500") replaces most engineering work. Selling agents with outcomes is the new SaaS, and shifts the model from per-seat pricing to outcome-based pricing. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ #Genspark and #WorkWithGenspark FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I'm joined again by Imran Muthuvappa to walk through how to build your own AI Chief of Staff using a tool called Nebula. Imran shows me how to spin up specialized agents that handle the work a real chief of staff would do — surfacing team blockers, tracking project status, holding people accountable to offsite vision goals, running daily agenda briefings, and prospecting ICP leads. We also get into mini apps, model selection for cost efficiency, and why personal software is becoming a real category. By the end, the takeaway is clear: every role now has a "work on the job" component where you supervise yourself and offload tasks to agents. Links Mentioned: Try Nebula: https://startup-ideas-pod.link/nebula Precall Agent: https://startup-ideas-pod.link/precall-agent Project Status Agent: https://startup-ideas-pod.link/project-status-agent Lead Gen Agent: https://startup-ideas-pod.link/lead-gen-agent Timestamps: 00:00 – Intro 02:13 – What is Nebula 02:54 – What an AI Chief of Staff Actually Does 4:26 – Nebula vs OpenClaw vs Hermes 06:09 – Building the Blockage Radar Agent 09:47 – Agent Features 12:04 – Choosing Cheaper Models for Simple Tasks 13:15 – Building Project Status Agent 13:53 – Connecting Tools to Agents 17:38 – Building Vision Tracker Agent 22:07 – Mini Apps and Personal Software as a New Paradigm 25:13 – Building a Daily Agenda Agent and Second Brain Integration 30:25 – Hours Saved vs. Anxiety Reduced for Founders 33:02 – Building the Lead Gen Prospector Agent 39:19 – Final Thoughts: Automate Three to Five Things Key Points An AI Chief of Staff handles the boring executive support work — calendar, email, LinkedIn, project status — so a human can focus on decisions. Nebula lets you build, deploy, and share custom agents through a Slack-like interface, where each agent has its own goals, tools, and system prompt. Voice input via SuperWhisper or WhisperFlow gets you to roughly 150 words per minute, which Imran calls the biggest productivity lift available right now. Cheaper models like the Nebula model handle most chief-of-staff tasks well — reserve frontier models like Opus or Sonnet for deep coding or reasoning work. Mini apps inside Nebula are spinnable web dashboards that connect back to your agents — a glimpse of personal software replacing off-the-shelf tools. The new skill is judgment: picking which three to five things to automate out of your week. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND IMRAN ON SOCIAL X/Twitter: https://x.com/imranye Alif: https://alif.build/

I sit down with Meng To for his second appearance on the pod to dig into design md, Google's newly open-sourced format for capturing the soul of a design and porting it across every medium and tool. Meng walks me through a live demo of how he uses design md alongside skills, HTML references, and tools like Aura, New Form, Codex, and OpenClaw to ship landing pages, motion design, slides, and mobile mocks that actually feel custom. We get into the design drift problem with one-shot prompts, why taste is the real moat for builders right now, and how he runs four products as effectively a team of one while iterating a thousand-plus prompts deep. If you build with agents and you want your work to stand out from the sea of purple-gradient lookalikes, this one is for you. Timestamps 00:00 – Intro 04:00 – What design md actually is 07:17 – Examples: one design DNA across slides, promo videos, motion 09:31 – How to create design system 14:05 – The importance of taste and design 18:28 – Variant, remixing, and skills as ingredients 21:36 – Live demo: creating a landing page with design md and HTML 24:36 – Thoughts on Google Stitch 25:41 – Being fast and at edges is an unfair advantage 29:29 – Midjourney parallels and the queuing flow state 31:44 – Walking through skills (skeuomorphic, 3D, lasers) 34:07 – Now everyone is a designer 36:47 – The full design workflow 38:50 – Iteration versus remix 39:24 – Judgment per minute as the new craft 41:06 – Solo building vs building a team 44:34 – Taste is the moat 48:25 – Building a second brain for design inspiration 50:41 – Closing thoughts Key Points Design md is a portable blueprint for typography, color, spacing, and effects that you attach to any prompt to keep design consistent across web, mobile, slides, and motion. One-shot prompts collapse on page two; a design system carries the soul across every medium and tool you switch into. Skills work like ingredients (lasers, skeuomorphic, 3D, copywriting), and stacking them on top of design md  is what separates custom work from generic vibe-coded output. Taste is the real moat right now, and you build it by surrounding yourself with great design and using every product in your niche. Iteration (90% of the time) keeps a product evolving; remix (10%) takes the same DNA into a new medium or category. The shift in craft is from moving pixels to making judgment calls per minute, with agents handling the mechanical work. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MENG ON SOCIAL Aura: https://aura.build X/Twitter: https://x.com/MengTo

Join me as I chat with Jack Friks, founder of PostBridge and marketer Gabe Fletcher about how to address PostBridge's 20% churn rate. Gabe provides a strategic framework for reducing churn, including creating a community around the product, embedding Jack's personality into the tool, collecting better user data, and developing a unique product metric. The conversation explores how positioning, pricing, and user experience can be optimized to increase retention. Timestamps: 00:00 - Introduction and purpose of the discussion 02:47 - PostBridge Overview 04:17 - Old Way vs New Way 11:15 - PostBridge Positioning 16:17 - Getting More User Data 19:05 - Email Marketing 22:32 - Onboarding Flow 24:57 - Indie Founder Trend 32:32 - Clear Positioning/Gamifying 39:34 - Importance of YouTube 47:39 -Creating A Unique Product Metric 54:23 - Market expansion strategies 01:02:08 - Data and Mission Drift 01:05:42 - The Team Around Jack 01:07:14 - World Building Explained Key Points: • Jack Friks' product PostBridge is making $20,000 MRR but facing significant churn issues • Gabe Fletcher provides a comprehensive analysis of how to reduce churn through multiple strategies • The importance of creating a unique product identity and embedding the founder's personality into the product • Strategies for data collection, user engagement, and expanding beyond a single platform The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ Boringmarketing - Vibe Marketing for Companies: boringmarketing.com The Vibe Marketer - Join the Community and Learn: thevibemarketer.com Startup Empire - a membership for builders who want to build cash-flowing businesses https://www.skool.com/startupempire/about FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg  Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JACK ON SOCIAL: PostBridge: https://www.post-bridge.com X/Twitter: https://x.com/jackfriks FIND GABE ON SOCIAL: X/Twitter: https://x.com/makershelpdesk

If you want more workflows and tactics to build a business with AI, check out this free workshop: https://www.ideabrowser.com/workshop I sit down with Andrew Wilkinson and we go deep on how he's restructured his work, his health, and his family office around AI agents. Andrew walks me through Deep Personality (an app he vibe-coded after running psychological screens on himself and his girlfriend), the autonomous SaaS business he runs through agent harnesses like Harbor, and the vector-database setup that lets him query Tiny and his personal holding company like an oracle. We cover where software is headed, why he's pouring capital into TSMC and data center stocks, and the daily AI workflows he's built around health, email triage, and a personalized morning podcast. Listeners walk away with concrete prompting tactics, agent architectures, and a frank read on where the moats are moving. Timestamps: 00:00 – Intro 01:50 – The OpenClaw and Claude Code Unlock 04:53 – Demo: Deep Personality App 10:38 – Harbor: An Agent Harness For Real Companies 12:30 – Autonomous Companies: Hype Vs. Reality 17:30 – Credibility As The Missing Layer For Vibe-Coded Products 20:14 – Centralizing Data Pipelines 21:35 – Vector Databases 23:22 – Transitioning Companies to Agentic Companies 25:22 – Where Andrew Would Build Today 27:10 – The New Interface 28:21 – Why build now 30:59 – Replacing Adapar: A Networth Wealth Platform 33:07 – Services As The New Software 35:24 – G-Brain Explained and Andrew’s OpenClaws 45:09 – Closing Thoughts Key Points Andrew runs a SaaS business called Deep Personality almost entirely through agents, generating roughly $20K of revenue while debugging eats half his time. Harbor (github.com/geekforbrains/Harbor) gives agents a GUI-style harness — dev, marketing, and support agents that can autonomously merge PRs and adjust ad budgets across PostHog, Meta, and Reddit. Andrew's family office swapped headcount for a $40K/month Claude bill; his CFO, who had zero coding background, vibe-coded a replacement for Adapar (priced at $50K–$100K/year) in about two weeks. Vector databases trained on Tiny and Andrew's holding company let him query 132 minority investments, P&Ls, and headcount data conversationally. For builders today, Andrew suggests aiming for a $1M–$2M product, then parking gains in TSMC and data center exposure given how fast software moats are eroding. His best prompting tip: ask the model to interview you with multiple-choice questions before generating any output. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ANDREW ON SOCIAL X/Twitter: https://x.com/awilkinson Deep Personality: https://deeppersonality.app Tiny: https://www.tiny.com

Limited BONUS: First 1,000 builders get $1,000. Claim yours while supplies lasts.: https://startup-ideas-pod.link/hyperagent I sit down with Howie Liu, co-founder and CEO of Airtable, to talk about the agent economy and the launch of HyperAgent. We walk through Sequoia's charts on AI agent deployment, the economics of token-based work versus human labor, and why frontier agents have crossed a threshold that changes how companies get built. Howie then does a live show-and-tell of HyperAgent, including a custom "Greg Isenberg contrarian AI" skill he spins up in real time. This one is for anyone building a solopreneur business, operating a fleet of agents, or trying to figure out where to place their bet in the agent ecosystem Timestamps 00:00 – Intro 02:22 – Sequoia's AI agent deployment chart reaction 04:41 – Copilot vs Autopilot territory and the $1T+ opportunity 08:13 – Agent economics vs human labor costs 11:12 – Fastest enterprise adoption curve in history 14:48 – The agent command center and fleet of 20 agents 18:03 – What is HyperAgent? 19:43 – Live demo: hyperlocal real estate market reports 22:38 – HyperAgent as the founder, not just the developer 23:21 – Street View, Zillow redesigns, and visual tool power 24:15 – Command center view across a fleet of agents 25:48 – Skills as the key primitive for frontier agents 26:30 – Building the Greg Isenberg contrarian AI skill live 32:31 – HyperAgent vs Perplexity Computer, Manus, OpenClaw, Codex 34:52 – Reviewing writing skill 36:55 – The arbitrage of persistence 41:31 – Confidence milestones: first dollar, $10K/month 35:27 – Reviewing contrarian tweet drafts live 45:05 – Giving the agent feedback and building rubrics 50:15 – Connectors, OAuth, and building custom API skills 53:03 – How to get started with HyperAgent 01:01:54 – Credit giveaway for listeners 01:03:31 – Closing Thoughts Key Points Frontier agents have crossed a threshold in the last 4–5 months where they function as true autonomous coworkers, not just chat assistants. Reframe agent cost by value delivered: a $150 token spend for a board memo beats hours of human time, so anchor on opportunity cost. The real arbitrage is persistence: 99% of people quit after one shot, while daily practice for 30/60/90 days produces top 1% operators. Skills are the most important primitive in frontier agents, turning generally intelligent models into domain experts through playbooks. HyperAgent's differentiation is a low floor plus a high ceiling, with rubrics, LLM-as-judge evals, and fleet-wide observability for scaling. Aim for $100B companies with under 5 employees, built on fleets of always-on agents mapped to human job roles. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND HOWIE ON SOCIAL X/Twitter: https://x.com/howietl Hyperagent: https://www.hyperagent.com Airtable: https://www.airtable.com-

I sit down with Riley Brown to get a hands-on tour of OpenAI's Codex, which he argues is the most powerful single interface for using AI agents today. Riley walks me through how Codex unifies vibe coding, knowledge work, browser use, computer use, and automations into one app, all running on GPT 5.5. I come in as a complete Codex skeptic who has spent most of my time in Claude Code, and Riley shows me skills, plugins, projects, Remotion, Chronicle, and the in-app browser to make his case. By the end, the question becomes whether the era of separate tools for documents, decks, code, and research is collapsing into a single super app. 00:00 – Intro 03:23 – What is Codex 06:46 – Why a GUI beats the terminal for most users 10:13 – Codex: the all in one platform 12:48 – Atlas browser inside Codex 14:21 – Remotion explained and motion graphics workflows 19:28 – Computer use and Chronicle 22:26 – Plugins, skills, MCPs, and integrations 31:57 – Evals, examples, and good outpu 38:43 – Hard questions: who Codex is built for 40:44 – Browser use plays itself in chess 43:20 – Running Claude Code inside Codex 45:58 – GPT 5.5 cost and effort settings 48:50 – GPT Images 2.0 54:09 – Why most people feel overwhelmed by AI tools 57:09 – Three projects to start with on day one and Closing thoughts Key Points Codex is positioned as a super app where coding, documents, decks, research, and automations live in one interface, with GPT 5.5 as the underlying model. The trend across Codex, Cursor, and the Claude Code desktop app is the same GUI pattern: chats on the left, agent in the middle, output on the right. Plugins offer official integrations like Slack, Notion, Sheets, Remotion, and Canva, while skills are user-created instructions stored as a SKILL.md file. Computer use and browser use have crossed a speed threshold; the chess demo runs at near-human pace, a leap from earlier "dial-up" feeling agents. Running Claude Code inside the Codex terminal lets you stack both subscriptions and use each model where it shines. The biggest unlock for companies is collecting good examples of finished work so agents can match the bar. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND RILEY ON SOCIAL X/Twitter: https://x.com/rileybrown Vibe Code App: https://www.vibecodeapp.com Youtube: https://www.youtube.com/@rileybrownai/videos

In this solo episode, I walk through ChatGPT Images 2.0 and show exactly how to use it to build creative assets that move a business forward, from brand visual directions to UI mockups to apparel mockups and editorial illustrations. I share the AI tool that surprised me this week (Noscroll), hand over a startup idea I want someone to steal (a learn-to-draw app with AI feedback on every sketch), and give you a five-step framework for finding and building a vertical AI business. I end with a Ralph Waldo Emerson quote that fired me up and a reminder to go conquer the day. Timestamps 00:00 – Intro 01:21 – What's New in ChatGPT Images 2.0 03:14 – Best Use Cases for Images 2.0 15:15 – Top Tips for Asset Generation 17:10 – Tool of the Week: Noscroll 20:17 – Startup Idea: Learn-to-Draw App with AI Feedback 24:58 – Framework: How to Find a Vertical AI Business to Build 29:45 – Closing Thoughts and Emerson Quote Key Points ChatGPT Images 2.0 delivers 2K resolution, eight images per prompt, thinking mode with web search, and dramatically better text rendering across languages. Specificity is the whole game with 2.0: dialed-in aesthetic, camera, lighting, palette, subjects, and output dimensions separate cinematic results from stock-looking ones. Every business has four creative bottlenecks: marketing content, internal decks and training, visual explanation, and testing before building. No Scroll is a glimpse into the future of AI agents: small, focused products that read the internet for you and text only what matters. Vertical AI beats horizontal AI for reaching seven and eight figures in ARR because niche workflows plus proprietary data equal defensibility. The Emerson mindset: own the day, finish it, forget the blunders, and begin tomorrow serenely. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Imran Muthuvappa to get a hands-on walkthrough of Hermes Agent, a personal AI agent that ships with built-in memory, 40+ tools, and pre-installed skills out of the box. Imran walks me through why he migrated from OpenClaw, how to install Hermes on a Mac or even an Android phone via Termux, and how he cut his token spend by roughly 90% using OpenRouter. We get into agent design (one agent vs. multiple), connecting Hermes to Telegram and Obsidian, and the kinds of prompts that turn a personal agent into a daily operating system. By the end, I have a practical roadmap to install Hermes, pick a model, and start automating real parts of my life and business Timestamps 00:00 – Intro 01:38 – Why Imran Left OpenClaw (Memory, Gateway, Tokens) 04:26 – Hermes Setup Tour and 40+ Built-In Tools 07:06 – Installing Hermes on Mac, Linux, and WSL 12:21 – Telegram and Android Agents 17:09 – Auditing Your Life With Your Agent 20:04 – Must-Know Hermes Tips: Updates, Tailscale, Telegram 21:07 – Should You Migrate From OpenClaw? 25:58 – Hermes + Obsidian as a Daily Dashboard 27:16 – Must-Use Prompts for a Personal Agent 31:29 – Must-Install Skills: Obsidian, Honcho Memory, G-Stack 33:04 – What G-Stack Is and Why It Matters 34:18 – Customization Is a Trap; Output Is the Skill 35:19 – Closing Thoughts Key Points Hermes Agent solves OpenClaw's three biggest pain points: built-in memory (writes to SQLite on successful tasks), gateway stability, and token visibility. Installation is a single command on Mac, Linux, or WSL, and Hermes ships with 40+ tools and popular skills (Apple Notes, Reminders, iMessage, Find My) pre-installed. Switching to Hermes with OpenRouter can cut token spend by roughly 90%, from about $130 per five days to around $10 per five days in Imran's case. You can run Hermes on a cheap Android phone via Termux + Termux API, unlocking SMS, sensors, and on-device social posting as a cheap alternative to a Mac Mini. The real skill is defaulting to your agent for work, then meta-prompting it nightly: "What am I procrastinating? What should I automate? What tool can you build me tonight?" Imran recommends pairing Hermes with Obsidian for a clean daily dashboard and installing G-Stack (a Y Combinator-style startup skill from Gary Tan) if you are building a product. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND IMRAN ON SOCIAL X/Twitter: https://x.com/imranye Alif: https://alif.build

I go live and get my hands dirty with Claude Design, Anthropic's new design tool in research preview. Across roughly an hour, I run a real workflow end-to-end: pulling a product idea from Idea Browser, generating wireframes, iterating into visual designs, building a pitch deck, and attempting a 30-second video ad. I share my first reactions in real time and take feedback from the chat. By the end, I land on a clear verdict — best-in-class for wireframes and visuals, weaker for video — and give you a practical sense of where this tool fits in your workflow. Timestamps 00:00 – Intro 00:50 – Claude Design walkthrough 03:48 – Picking a product idea from Idea Browser: Senior Brains 05:54 – Wire-framing Senior Brains 13:54 – Reacting to the generated wireframe 20:44 – Building a pitch deck for Senior Brains 30:39 – Reacting to a pitch deck 34:58 – Reacting to Hi-Fi wireframe 40:40 – Creating a 30-second animated video ad 48:58 – Reacting to animated video ad 58:10 – Final verdict and recommendations Key Points Claude Design's wireframing is the strongest capability I've seen in a design tool to date, especially the questionnaire that extrapolates like a product manager. The pitch deck generation nails roughly 90% of the output with minimal input, which saves hours. Visual design mockups come through clean and usable, ready to iterate with 30 minutes of back-and-forth. Video generation lands at about a 5/10 — workable as a social post, weaker as a real commercial. Start with wireframes first to conserve tokens and sharpen feature decisions before committing to high fidelity. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this episode I sit down with my friend Sirio, one of the most creative AI minds I know, to break down Seedance V2. Sirio walks us through the exact use cases, prompts, and tactics he's using to build on top of this model inside his platform Enhancor, covering multi-input generation, virtual try-ons, ad translation, AI influencers with lip sync, video extension, and 3D product template replacement. I wanted this to go beyond the "look how cool this is" tutorials and focus on how creators and founders can actually build businesses, run ads, and produce creative assets with it. By the end, you'll have a practical playbook for Seedance V2 and a clear view of where it fits alongside other models like Kling 3, Veo, and fine-tuned options. Timestamp 00:00 – Intro 02:22 – Demo 1: Replacing Characters and Background in a Green Screen Scene 08:03 – Prompting Tactics and Optimize Prompts 09:45 – Demo 2: Virtual Try-On in Montreal (Minus 30 Degrees) 13:05 – Demo 3: Ad Translation and Character Replacement (Chinese to English) 16:02 – Demo 4: 3D Product Template with Brand Texture Swap 18:40 – Demo 5: Video Extension and Filling in the Middle 20:55 – Demo 6: AI Influencers and Prompting Realistic Emotion 29:31 – What Happens to Adobe Over the Next Five Years Key Points Seedance V2 is the first widely available video model to support true multi-input generation — up to two images, two videos, and an audio file combined in a single prompt. Treat Seedance V2 as a video editor, not just a generator: character swap, background swap, text preservation, ad translation, and template population all work from natural-language prompts. Seedance rewards highly specific prompts; I pair my own draft with Claude Opus 4.6 to optimize prompts for vision models. Strong source reference images remain the single biggest quality lever — the model mimics taste from what you feed it. For AI influencers and lip sync, describe muscle movements and emotional transitions rather than simply labeling an emotion like "sad" or "happy." Seedance V2 is the current default for editing and generating video, yet other models (Kling 3 for cinematic feel, Enhancer V4 for talking-head realism) still win on specific use cases. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND SIRIO ON SOCIAL Enhancor AI: https://www.enhancor.ai Instagram: https://www.instagram.com/heysirio/ Youtube: https://www.youtube.com/@SirioBerati

I sit down with Amir, who's back on the pod, and we walk through the full stack of taking a business idea from zero to a validated, A/B-tested landing page in a single session. I use Idea Browser's new MCP integration with Claude Code to pull project context, generate a lead magnet concept, design a landing page in Paper, and then wire up analytics and live experiments through HumbleLytics — all without writing a single line of front-end code manually. We cover the tools, the workflow, and why this stack creates massive arbitrage for marketers and builders right now. Timestamps 00:00 – Intro and Episode Preview 02:30 – Building a Growth Strategy with Idea Browser 06:10 – Designing Landing Pages in Paper 08:38 – Refining Copy, Layout, and Components in Paper 20:06 – Deploying Landing Page and Adding HumbleLytics Analytics 28:38 – Running A/B Experiment on the Headline 32:44 – The Arbitrage Opportunity and Closing Thoughts Links Mentioned: Amir’s Agentic Marketing Skill: https://startup-ideas-pod.link/amir_marketing_skill Key Points Idea Browser now connects to Claude Code as an MCP, letting you pull project context, growth strategies, and skills directly into the terminal for building and iterating on business ideas. Paper replaces the traditional Figma-to-developer handoff by letting you design, iterate, and refine landing pages visually — all connected to Claude Code so changes stay in sync. HumbleLytics enables no-code A/B experiments that dynamically update page content without deploying new code, so you can test headlines, CTAs, and layouts in real time. Storing performance context (A/B results, revenue data, growth metrics) back into Idea Browser compounds your results over time because every future decision is informed by past data. This full stack — Idea Browser, Paper, Claude Code, HumbleLytics — creates a significant arbitrage opportunity right now because almost nobody is using it at this level. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND AMIR ON SOCIAL Humblytics: https://humblytics.com/?via=community X/Twitter: https://x.com/amirmxt Youtube: https://www.youtube.com/@amirmxt

I sit down with Ras Mic to break down how AI agents actually work and why most people are using them wrong. Ras Mic explains the mechanics of context windows, makes the case that agent md files are largely unnecessary, and shares his step-by-step methodology for building custom skills that make agents dramatically more productive. Whether you're coding with Claude Code or automating workflows with OpenClaw, this episode gives you the foundational knowledge to stop wasting tokens and start getting real results from your AI tools. Timestamps 00:00 – Intro 00:42 – The Models Are Good Now 01:20 – How Context Windows Actually Work 04:55 – The Power of Skills 09:17 – How to create Skills 16:35 – Skill Maxxing 19:05 – What you need too build a project 20:40 – Recursively Building and Improving Skills 29:23 – Context Window Management and Token Efficiency 33:02 – Closing Thoughts Key Points The models (Opus 4.6, GPT 5.4) are exceptionally good now — the differentiator is the context and harness you build around them. Agent md and claude md files get loaded into context on every single turn, burning tokens and degrading performance as the context window fills up. 95% of users can skip them entirely. Skills use progressive disclosure: only the name and description sit in context until the agent determines it needs the full file, saving thousands of tokens per conversation. The best way to create a skill is to walk through the workflow with the agent step by step, achieve a successful run, and then have the agent write the skill based on that real context. Recursively refine skills by feeding failures back into the agent and having it update the skill file so the same mistake is avoided going forward. Scale for productivity by starting with one agent and building up workflows before adding sub-agents — start simple, then expand. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

I sit down with Flo, founder of Lindy, to get a live demo of their new product, Lindy Assistant, an AI executive assistant that lives in iMessage and works proactively across email, calendar, Slack, Notion, and 100-plus other tools. Flo walks me through a real day of his own Lindy usage, showing how it drafts email replies, prepares meeting briefs, updates CRMs, and handles calendar changes without being asked. We compare Lindy to OpenClaw and Claude's ecosystem, talk pricing, edge-case power users, and where Lindy goes over the next five years. Try the ultimate AI assistant: https://startup-ideas-pod.link/lindy Timestamps 00:00 – Intro 01:09 – What Lindy Assistant is and why Flo built it 02:27 – The daily morning brief 05:16 – Setup: two steps, two minutes, out of the box 05:53 – Get the most out of Lindy Assistant 09:42 – My three assistant use cases: research, scheduling, and sales leads 15:51 – Lindy vs. OpenClaw 17:57 – Lindy vs. Claude ecosystem 19:51 – Where Lindy goes over the next five years 23:42 – Integrations overview (100-plus tools) 24:42 – What Lindy does well and what it does not replace 26:52 – Pricing: starts at $49/month 27:15 – How power users are using Lindy 28:18 – Voice memos, incoming phone calls, and outbound calls 30:00 – How to use Lindy alongside a human executive assistant Key Points Lindy Assistant lives in iMessage, connects to email, calendar, Slack, Notion, and 100-plus other apps, and acts proactively without being prompted. Setup takes two minutes: provide a phone number and connect a Google account, and Lindy ingests existing email and tool data immediately. Lindy pre-drafts email replies, preps meeting briefs, updates CRMs after calls, flags billing issues, and reschedules dinners at closed restaurants — all without user initiation. The voice and tone of the assistant took extensive prompt engineering; the lowercase, casual register is intentional and difficult to achieve with current models. Lindy targets the "chief everything officer" — the overwhelmed founder or executive — rather than developers or power users who want a fully programmable agent. Pricing starts at $49/month for 90-plus percent of users; heavy users can exceed that and are prompted to upgrade. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND FLO ON SOCIAL X/Twitter: https://x.com/Altimor Lindy: https://www.lindy.ai

I go solo on this episode to walk through the full list of AI trends and opportunities keeping me up at night — literally. From the one-hour company stack to ambient businesses, vertical AI, the agent economy, and the real security threats I see coming, I cover what I believe is the most asymmetric window in startup history. I share the frameworks I use to think about what to build, what to avoid, and why acting now matters more than waiting for things to settle down. Timestamps 00:10 – Intro 01:09 – 1) The One-Hour Company Stack 02:09 – 2) Old vs. new startup timeline 03:58 – 3) Ambient businesses and autonomous companies 05:18 – 4) The agent economy timeline 07:17 – 5) Agent hiring Agents 08:01 – 6) The Vertical Agent Map 09:39 – 7) Vertical AI vs. Vertical SaaS 10:53 – 8) Boring goldmine verticals 11:40 – 9) SaaS Pricing Evolution 13:26 – 10) Seat-Based vs Outcome-Based 14:51 – 11) The SaaS graveyard 16:04 – 12) The scarcity flip 17:03 – 13) The Premium Stack 18:21 – 14) The experience economy boom 18:59 – 15) Founder-agent fit 20:32 – 16) Ghost team org chart 21:56 – 17) The micro monopoly math 24:00 – 18) Agent attack surface 25:19 – 19) Agent Injection vs Phishing 26:34 – 20) Agent permission stack 27:37 – 21) The closing window 28:46 – 22) why this window is asymmetric 29:34 – 23) Building in public 30:50 – Final Thoughts Key Points I can build, launch, and get a first customer in under an hour using today's agent engineering tools and a pre-existing audience. Vertical AI taps directly into labor P&L — it replaces headcount, not just software licenses — making the TAM 10x larger than vertical SaaS. Ambient businesses running on near-zero daily human input are early but real; the arrow of progress points here. The value shift I see coming: execution gets commoditized, judgment and physical presence become premium. Agent injection is the new phishing — and I believe it scales faster and hits harder than any phishing attack did. The 100 true fans model now applies in the AI age; with agents cutting costs, 100 paying customers at $500–$1,000 a month builds a real business. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I break down the seven distribution strategies every vibe coder and builder needs to actually get customers. With 200,000 new projects launching daily on platforms like Lovable, the real bottleneck is distribution and I believe the wealthiest people over the next decade will be marketers, because code is now commoditized. I walk through each strategy with step-by-step instructions you can start this week, from MCP servers and programmatic SEO to acquiring newsletters and building AI repurposing engines. Timestamps 00:00 – Intro 01:07 – The Great Flip: Distribution Over Engineering 03:08 – The Build-First Trap 04:18 – Strategy 1: MCP Servers as Your Sales Team 06:49 – Strategy 2: Programmatic SEO (10,000 Pages) 10:09 – Strategy 3: Free Tool as Top of Funnel 13:03 – Strategy 4: Answer Engine Optimization (AEO) 15:48 – Strategy 5: Viral Artifacts (Make Outputs Shareable) 18:56 – Strategy 6: Buy a Niche Newsletter 21:40 – Strategy 7: AI Content Repurposing Engine 25:13 – Final Takeaways Key Points Distribution is the new moat — AI can build the product, but it can't build your audience or brand. Building an MCP server in 2026 is like building for mobile in 2010; early movers will own AI-native distribution channels. Programmatic SEO can scale to 300,000 monthly visitors if you create 10,000 quality pages that each pull just 30 visits a month. Free tools act as always-on marketing: you can vibe code one in a day, ship it by lunch, and it markets itself forever. Answer engine optimization (AEO) is where SEO was in 2010 — Peter Levels saw AI referrals jump from 4% to 20% in one month. You can buy a 10,000-subscriber niche newsletter for $5,000–$20,000 and inherit a direct channel to your exact audience on day one. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Dotta, the pseudonymous co-founder of Paperclip, the open-source agent orchestrator that exploded to 30,000 GitHub stars in under three weeks. We walk through a live demo where I pick a startup idea from my idea browser and we spin up a full AI-agent company in real time — hiring a CEO, founding engineer, QA agent, video editor, and content strategist inside Paperclip. Dotta shares practical tips on agent configuration, memory systems, skill installation, and the "Memento Man" mental model for keeping agents on track. The conversation covers everything from token spend management and agentic design patterns to the future of importable, shareable companies and the upcoming Maximizer Mode. Skills to build your agent team: https://startup-ideas-pod.link/skill-suite Timestamps: 00:00 Intro 02:32 What is Paperclip 04:21 Choosing a Startup Idea for the Demo 05:48 Setting Up your agents 07:51 Hiring Your First Agent and Creating a Plan 12:39 Agent Configuration and Persona Setup 17:08 Skills: Installing and Managing Agent Capabilities 21:02 How to Get Top-Quality Output from Agents 24:05 Token Spend Tracking and Subscription Usage 25:49 Agentic Design Patterns and QA Loops 29:05 Taste and Values: What AI Still Cannot Do 30:09 How Many Agents Run the Paperclip Project 32:32 Routines: Automating Recurring Agent Tasks 36:36 Who Is Using Paperclip Today 38:57 Shareable and Importable Companies 42:49 The Unproven Frontier: Do Agent Orgs Actually Work? 42:49 Maximizer Mode and What's Next 44:29 Did Dotta Expect It to Go This Viral? Key Points Paperclip is a bring-your-own-bot orchestrator: it works with Claude Code, Codex, OpenCode, and any model on OpenRouter, so you are not locked into a single provider. AI agents are "Memento Man" — they wake up capable but with zero memory, so you need heartbeat checklists, persona prompts, and written context to keep them effective. The biggest lever for quality output is encoding your own taste and values into agent skills and brand guides, because AI can do everything except know what you actually want. Agentic design patterns like engineer-to-QA review loops matter more than one-shotting an entire startup; structure prevents compounding errors. Paperclip tracks every token spent and every task completed, solving the problem of running dozens of agent windows with zero accountability. Importable, shareable company templates (like Gary Tan's G-Stack or a full game studio) point toward a future where you "aqua-hire" proven agent teams instead of building from scratch. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND DOTTA ON SOCIAL X/Twitter: https://x.com/dotta Paperclip: https://paperclip.ing Github: https://github.com/cryppadotta

I break down Firecrawl and it solves AI’s biggest blind spot, access to clean web data. I walk through the full AI agent stack every builder needs, explain why this is the "AWS moment" for web data, and share a dozen startup ideas you can build this week using Firecrawl for scraping, enrichment, and automation. Whether you want to launch a niche SaaS, a lead gen service, or a data-as-a-service business, this episode gives you the frameworks and the specifics to get started. Shoutout Firecrawl - Turn websites into LLM-ready data: https://startup-ideas-pod.link/firecrawl Timestamps 00:00 – Intro 02:14 – Why this matters now 07:40 – What is Firecrawl 11:20 – How does Firecrawl work 12:57 – The Agent Stack 14:35 – 7 Startup Ideas 24:01 – Firecrawl Hired an AI Agent as an Employee 26:24 – Final Thoughts Key Points AI models are only as good as the data they can access — clean, structured web data is the new critical infrastructure. Firecrawl replaces thousands of lines of custom scraping code with a single API call that returns clean markdown, structured JSON, and screenshots. The biggest opportunity is taking horizontal SaaS categories (SEO tools, job boards, price trackers) and building hyper-niche versions using Firecrawl at a fraction of the cost. I think about the AI agent stack in five layers: agent harness, search layer, web data layer, ops brain, and outbound/audience stack. The real business model is selling the data output, not the tool — you can charge $200 to $5,000 per month per client with margins above 95%. Vertical software always wins because people pay for specificity; Constellation Software built a ~$75 billion company on this principle. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ \FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Moritz Kremb, an OpenClaw power user and agency builder based in Berlin, to break down how to actually make OpenClaw useful. Moritz walks through a 10-step optimization guide covering everything from troubleshooting and memory management to model selection and security basics. He then demos two real systems he built with OpenClaw: a full short-form video content pipeline and a conversational CRM. This episode is for anyone who tried OpenClaw, hit a wall, and wants a clear path to turning it into a superhuman digital employee. Timestamps 00:00 – Intro and episode promise 02:17 – What is OpenClaw 03:17 – OpenClaw vs. ChatGPT vs. Claude Code 07:43 – Where Claude Cowork and Dispatch fit in 09:47 – Why choose OpenClaw over Cowork 11:03 – Step 1: Setting up OpenClaw 14:46 – Step 2: Personalize your workspace files 18:04 – Step 3: Fix and optimize memory 22:43 – Step 4: Choose the right model (OAuth method) 25:56 – Anthropic ban and model provider gray areas 27:33 – Step 5: Organize Telegram groups and topics 30:19 – Step 6: Understand the three browser modes 35:18 – Step 7: Skills — built-in, marketplace, and custom 39:03 – Step 8: Optimize the heartbeat file 42:00 – Step 9: Security basics and prompt injection 48:08 – Step 10: Least access principle and agent-owned accounts 49:52 – Use case 1: No AI Slop content system 58:37 – Use case 2: Conversational CRM 01:01:15 – Final thoughts on the future of personal agents 01:02:55 – Jensen Huang's take: OpenClaw as the new computer Key Points Upload the OpenClaw documentation into a Claude project to create a dedicated troubleshooting baseline — it solves roughly 99% of setup issues. Use the OAuth method (your existing $20 ChatGPT or Anthropic subscription) to avoid expensive API costs, and always configure backup models. Memory problems are almost always caused by memory never being saved in the first place; add an auto-save instruction to the heartbeat file so it logs every 30 minutes. Organize your OpenClaw conversations into separate Telegram groups and topics with group-specific system prompts to avoid context bleed. Stronger models are meaningfully more resistant to prompt injection; pair that with least-access principles and agent-owned accounts for a solid security posture. Custom skills are the path to real automation — whenever you do something repeatedly, tell your OpenClaw to turn it into a skill. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MORITZ ON SOCIAL X: https://x.com/moritzkremb Youtube: https://www.youtube.com/@promptwarrior/videos Instagram: https://www.youtube.com/@promptwarrior/

I sit down with Remy Gaskell to break down how anyone can build AI agents to run entire departments of their business. Remy walks through the core concepts: agent loops, context files, memory, MCP tool connections, and skills. We put everything together by building a fully functional executive assistant live on screen. This is a beginner-friendly crash course that covers Claude Code, Codex, Cowork, Antigravity, Manus, and OpenClaw, showing that once you understand how to "drive," you can jump into any agent platform. By the end, listeners know exactly how to set up markdown-based context files, connect their everyday tools, and create reusable skills that compound over weeks and months. Timestamps 00:00 – Intro 01:35 – Agents vs Chat 03:22 – The Agent Loop 05:46 – How Agents work 06:39 – Demoing Agents (Claude Code, Codex, Antigravity) 08:52 – Security and Agent Permissions 10:43 – Comparing Results Across Three Platforms 13:57 – Startup Idea: Cold Email Website Offer 14:50 – Folder Structure and Department-Based Agents 15:52 – Onboarding an Agent Like a Real Employee 17:05 – Voice-to-Text With Monologue and WhisperFlow 18:04 – Chat Memory vs. Agent Memory 19:34 – Building the agents md 22:20 – Context Engineering Over Prompt Engineering 24:29 – How Memory Compounds and Reduces Errors 30:27 – How Big Can memory md Get? 31:43 – Connecting Tools via MCP (Model Context Protocol) 34:49 – Working in Claude Code for High-Value Tasks 37:09 – Why the Real Value Is in Stacking, Not Summarizing 40:04 – What Are Skills? (SOPs for AI) 43:08 – Creating Skills 48:36 – Real-World Example: Ads Analyst Skill: 4-Hour Process in Minutes 50:37 – Chaining Skills together 52:01 – Real-World Example: Automated Car Search 53:34 – OpenClaw and Migrating Agents to More Autonomous Platforms 55:19 – Which Platform Should Beginners Start With? 56:28 – Global vs. Project-Level Skills, Context, and MCPs Key Points Agent platforms (Claude Code, Codex, Cowork, Antigravity, Manus, OpenClaw) are all running the same observe-think-act loop under the hood — learning one means you can use any of them. The shift from chat to agents requires moving from prompt engineering to context engineering: load the agent with rich context so simple prompts produce excellent results. A memory md file creates a self-improving loop where the agent learns preferences across sessions and makes fewer errors over time. MCP (Model Context Protocol), built by Anthropic, acts as a universal translator between your agent and every tool it needs — Gmail, Calendar, Stripe, Notion, and more. Skills are reusable SOPs packaged as markdown files; once you explain a process once, you can invoke it repeatedly, and they compound as you add three to five per week. Scheduled tasks turn skills into automated workflows — morning briefs, car searches, ad library analyses — that run on a cron without any manual trigger. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND REMY ON SOCIAL X:https://x.com/remy_gaskell Youtube: https://www.youtube.com/@aiwithremy Instagram: https://www.instagram.com/aiwithremy/

I break down Andrej Karpathy's new open-source project, Autoresearch: what it is, how it works, and why some of the smartest people in tech are losing their minds over it. I walk through 10 concrete business ideas you can build on top of Autoresearch loops, from niche agent-in-a-box products to always-on A/B testing agencies. I also cover Karpathy's companion launch, Agent Hub, share community reactions, and show you step by step how to get started using Claude Code and a Colab GPU. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Links Mentioned: Autoresearch Github: https://startup-ideas-pod.link/autoresearch Timestamps 00:00 – Intro 00:45 – How Autoresearch Actually Works 02:40 – Visual Walkthrough of the Autoresearch Loop 03:37 – Mental Model: Your Research Bot That Runs While You Sleep 05:26 – Idea 1: Niche Agent-in-a-Box Products 06:48 – Idea 2: A/B Testing for Marketing (Landing Pages & Ads) 08:45 – Idea 3: Research as a Service 09:43 – Idea 4: Power Tool Inside Your Own SaaS 10:49 – Idea 5: Agency That Runs 100× More Tests 12:05 – Idea 6: Auto Quant for Trading Ideas 13:44 – Idea 7: Always-On Lead Qualification & Follow-Up 14:21 – Idea 8: Finance Ops Autopilot for Businesses 15:09 – Idea 9: Internal Productivity Lab for Your Org 15:53 – Idea 10: Done-for-You Research & Due Diligence Shop 16:41 – Non business use cases 18:27 – Karpathy's Agent Hub Announcement 19:50 – How to Get Started with Autoresearch 22:21 – Final Thoughts Key Points Autoresearch is an open-source AI agent that sets a goal, runs experiments in a loop on a GPU, keeps the winners, and discards the rest — all while you sleep. You need an NVIDIA GPU to run it (tested on H100), but you can rent one cheaply through Lambda Labs, Vast AI, RunPod, Google Cloud, or Google Colab. The fastest way to get started is to use Claude Code to walk you through installation, then run it on Google Colab with a T4 GPU runtime. Ten business ideas built on Autoresearch span niches like SaaS optimization, A/B testing agencies, trading backtests, CRM lead scoring, and done-for-you due diligence. Karpathy also launched Agent Hub — essentially a GitHub designed for agent swarms to collaborate on the same codebase. The project already has 25,000+ GitHub stars and is growing fast; early movers who tinker now build an unfair advantage. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Oliver Henry, a full-time employee who is generating hundreds of dollars in monthly recurring revenue from mobile apps he barely touches, thanks to an AI marketing agent he built on OpenClaw called Larry. We walk through how Larry autonomously creates TikTok slideshow content, reads analytics, iterates on hooks and CTAs, and feeds performance data back into the content loop. Oliver also shares how he packaged the entire system as a free, downloadable skill on Larry Brain so anyone can replicate it. By the end of the episode, you will understand the full “Larry Loop”—from content creation to conversion optimization and why skills are poised to reshape how we think about SaaS altogether. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Links Mentioned: Larry Brain: https://startup-ideas-pod.link/Larry-brain QMD Skill: https://startup-ideas-pod.link/qmd-skill Timestamps 00:00 – Intro 01:25 – Background on Marketing IOS app with OpenClaw 06:43 – Larry’s first posts and iterating 03:55 – Posting Strategy and First viral hit: 137K views 12:01 – Communicating with Larry via WhatsApp 12:53 – Mission control vs. single-agent workflow 14:36 – The CTA problem: views without conversions 17:07 – The Larry Loop explained: analytics → content → metrics → iterate 18:15 – Boomers, engagement bait, and the algorithm boost 20:33 – The importance of iteration 23:36 – How Larry brainstorms and validates new hooks 27:57 – The power of OpenClaw 30:04 – The vision for Larry 31:49 – Model choices: Claude vs. OpenAI and over-optimization 34:38 – OpenClaw vs. cloud alternatives (Manus, Cowork) 37:39 – Getting started: Larry Brain onboarding and 80+ skills 40:13 – Ernesto Lopez: $70K MRR using the Larry Loop 41:27 – Doing all of this with a full-time job 42:28 – QMD Skill for cutting token usage and closing thoughts Key Points An AI agent (Larry) built on OpenClaw autonomously creates TikTok slideshows, reads analytics, and iterates on content—driving hundreds of dollars in MRR with almost zero manual effort. The “Larry Loop” is a full-funnel feedback cycle: TikTok analytics feed into content creation, and app metrics feed back into the top of the funnel so the agent continuously improves. Posting TikTok content as a draft (rather than directly via API) lets you add trending sounds and avoids the algorithm penalty for bot-posted content. Hooks drive views; CTAs drive conversions. Diagnosing which is underperforming is the key to scaling. OpenClaw skills are locally owned, fully editable, and free from hosting or subscription costs—Oliver argues they will change how we think about SaaS. Picking a model (Claude or OpenAI) matters far less than learning how to work with it; 98% of users will see little difference between incremental model upgrades. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND OLIVER ON SOCIAL X: https://x.com/oliverhenry Larry Brain: https://www.larrybrain.com

I walk through a complete 30-step playbook for building a modern SaaS company using AI agents, media, and sub-niche positioning. The core argument is that SaaS is evolving rather than dying, and the builders who win are the ones who combine a focused workflow product with a media flywheel and agent-powered execution. Drawing on my experience advising TikTok, Reddit, and building three venture-backed companies, I lay out a step-by-step framework any solo builder or small team can follow from niche selection through to becoming the default execution layer in their market. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Timestamps 00:00 – Intro 01:18 – Step 1: Start with a sub-niche inside a big market 02:21 – Step 2-5: Map Workflow end to end 06:37 – Step 6-7: Create scroll-stopping content 10:15 – Steps 8–9: Double down on organic and run paid ads on winners 11:11 – Step 10: Capture emails from day one 11:47 – Steps 11–13: Manually perform the workflow and document every step 13:40 – Steps 14–16: Turn mechanical tasks into agent workflows and connect to real tools 14:47 – Step 17: Add orchestration, retries, and verifications 16:32 – Steps 18–19: Store user preferences and launch with high-touch onboarding 18:20 – Steps 20–21: Publish measurable proof and move to per-task pricing 21:21 – Steps 22–23: Outcome pricing and compounding value 22:07 – Steps 24–27: Expand workflows, build switching costs, create case studies 23:25 – Steps 28–30: Hire from the niche, reinvest profits, become the default layer 24:08 – Closing thoughts Key Points Start in a specific sub-niche, not a broad market — that is where sustainable cash flow lives, not VC competition. The future of SaaS starts as a service business: manually performing the workflow is how I learn what to automate. Media is a core business function, not an afterthought — content creation runs in parallel with product development from day one. Mechanical tasks are AI's strongest suit; separating judgment tasks from mechanical tasks is the key architectural decision. Per-task and outcome-based pricing is replacing per-seat models, and indie builders have a structural advantage in making that shift. Orchestration — coordinating agents, validating outputs, and resolving issues — is the new interface layer and the highest-value position to own. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with Cody Schneider, growth engineer and co-founder of Graph, for a live, hands-on crash course in GTM (go-to-market) engineering powered by Claude Code. Cody walks through how he runs multiple AI agents simultaneously to handle everything from bulk Facebook ad creation and LinkedIn outreach to cold email campaigns and live data analysis — tasks that used to require a team of dozens. By the end of the episode, you'll have a full understanding of how to set up your own agent workflow, the specific tools involved, and why domain expertise paired with AI is the real competitive advantage right now. Cody’s GTM Toolkit: AI/Agent Tools: Claude Code, Perplexity API, OpenAI Codex Marketing & Outreach: Instantly AI (cold email), Phantom Buster (LinkedIn scraping/automation), Apollo API (data enrichment), Million Verifier (email verification), Raphonic (podcast host scraping): Advertising: Facebook Ads API, Facebook Ads Library (competitor research), Nano Banana Pro (AI image generation), Kai AI (bulk image generation), HeyGen API (UGC/video generation) Infrastructure & Deployment: Railway.com (servers, on-the-fly databases/Postgres), Vercel (deployment) Data & Analytics: Graphed / Graphed MCP (data warehouse, live data feeds), Google Analytics 4 CRM & Communication: Salesforce (mentioned as comparison), Intercom, SendGrid API, Slack, Cal.com API Productivity & Design: Notion, Super Whisper (voice transcription), Claude Code front-end design skill, HTML to Canvas (for converting React components to PNGs) Timestamps 00:00 – Intro 02:02 – What Is GTM Engineering? 05:12 – Setting Up Your Agent Workspace & Environment File 07:54 – Live Demo: LinkedIn Auto-Responder 09:56 – Live Demo: Bulk Facebook Ad Generator 12:31 – Live Demo: Cold Email Campaign Automation (Raphonic + Instantly) 14:47 – Live Demo: Creating Notion Documents via Claude Code 16:46 – Live Demo: Bulk Ad Creative Generator 26:05 – Live Demo: LinkedIn Engagement Scraper to Cold Email Pipeline 28:16 – Context Switching Across Tasks 29:19 – Live Demo: Bulk Ad Generator 31:41 – Live Demo: Data Analysis: Turning Off Low-Performing Ads 35:28 – Summary of GTM Engineering Workflow 37:48 – Deploying Agents and On-the-Fly Databases with Railway for Data Analysis 41:28 – The Dream of Autonomous Marketing 48:50 – Building API-First Products and Agent-Native Infrastructure Key Points GTM engineering has evolved from Clay-style data enrichment workflows into full-stack agent orchestration — where one person running multiple Claude Code agents can replace the output of a large team. The practical setup starts with a single folder containing your environment file (API keys for every tool in your stack), transcription software like Super Whisper, and Claude Code. Cody demonstrates running seven or more agents simultaneously across LinkedIn outreach, Facebook ad creation, cold email campaigns, Notion document generation, and live data dashboards. Code-generated ad creative (React components exported as PNGs) costs nearly nothing to produce at scale and allows rapid testing of messaging variations before investing in polished visuals. Deploying proven workflows to Railway turns one-off agent tasks into always-on, autonomous processes that run 24/7. Domain expertise is the real multiplier — the vocabulary you bring from your field determines the quality of output you can extract from these tools. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CODY ON SOCIAL: Cody’s startup: https://www.graphed.com/ X/Twitter: https://x.com/codyschneiderxx Youtube: https://www.youtube.com/@codyschneiderx

I take Perplexity Computer for its first real spin and test five use cases that founders can use right now to make money and move faster. I connect my Gmail live, let the AI send cold outreach on my behalf, set up daily competitive intelligence monitoring, research 50 VCs for a mock Series A, and kick off a full investment memo on Shopify, all in a single session. By the end, I walk away genuinely impressed and convinced the $200/month Max plan can pay for itself with one closed deal. Timestamps 00:00 – Intro 00:35 – What We're Testing Today 02:35 – Use Case 1: Warm Outbound at Scale 15:31 – Use Case 2: Automated Competitive Intel 25:11 – Use Case 3: Investor Pipeline Research (50 VCs) 26:58 – Use Case 4: Turn a Podcast Into a Content Machine 31:39 – Use Case 5: Live Market Diligence (Shopify Investment Memo) 34:17 – Bonus: Additional Use Cases Worth Trying 36:06 – Closing Thoughts and Takeaways Key Points Perplexity Computer runs multiple research tasks in parallel using sub-agents, skills, and tools — functioning like a virtual analyst working across the open internet. The cold outreach workflow found real email addresses, researched each prospect's recent activity, and drafted hyper-personalized emails that reference specific details — then sent them through a connected Gmail account. Setting up recurring competitive intelligence monitoring (daily reports, weekly sponsor tracking) is where the tool shifts from a one-off assistant to a persistent agent running on autopilot. The VC pipeline research use case demonstrates how founders who lack a warm network can still build a structured, targeted investor list with fund sizes, thesis alignment, and partner contacts. At $200/month on the Max plan, the cost pays for itself if even one sponsorship deal or investor meeting closes from the outreach. The platform already supports connectors for Gmail, Google Drive, Slack, HubSpot, Ahrefs, Reddit, and more — making it a serious contender for centralized founder workflows. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I sit down with my dear friend Vin (Internet Vin) for a deep, hands-on walkthrough of how he uses Obsidian and Claude Code together as a thinking partner, idea generator, and personal operating system. Vin demonstrates live how Claude Code can read, reference, and surface patterns across an entire Obsidian vault of interlinked markdown files — turning years of personal notes into actionable insights, project ideas, and even custom commands. This episode covers everything from the basic setup to advanced workflows like tracing how ideas evolve over time, generating contextual startup ideas, and delegating tasks to autonomous agents. If you are serious about getting the most out of LLMs, this is the episode that shows you how your own writing becomes the fuel. Link to Vin's skills and my notes: https://startup-ideas-pod.link/obsidian-commands Timestamps 00:00 – Intro 02:10 – What Is Claude Code? 06:45 – What Is Obsidian? 10:28 – Obsidian CLI: Giving Claude Code Access to Your Vault 14:53 – Thinking Tools: Ghost, Challenge, Emerge, Drift, Ideas, Trace 22:51 – The Role of Reflection in Building a Powerful Vault 25:15 – How This Relates to OpenClaw (Autonomous Agents) 29:13 – Live Demo: /Connect — Bridging Two Domains 31:25 – Meeting Notes & External Info 33:23 – Why Vin Keeps a Strict Separation: Human-Written vs. Agent-Written 35:42 – How Claude Code uses Obsidian 41:46 – Live Demo: /Ideas — Generating Actionable Ideas from Your Vault 47:10 – The /Graduate Command 50:29 – Why Obsidian Is the Missing Link for AI Companies 54:53 – The Alpha: Why 99.99% of People Won't Do This 57:38 – Closing Thoughts & Where to Follow Vin Key Points Claude Code is a command-line agent that can control your computer through natural language — and its power multiplies when you feed it rich, persistent context files instead of re-explaining projects every session. Obsidian is uniquely valuable because it sits on top of interlinked markdown files; the new Obsidian CLI lets Claude Code see both the files and the relationships between them. Vin built custom slash commands (/trace, /connect, /ideas, /ghost, /drift, /challenge) that let him use Claude Code as a thinking partner — surfacing latent patterns, contradictions, and ideas he would never see on his own. Writing and daily reflection are the engine of the entire system: the more you write, the more context the agent has, and the more it can do for you. Vin maintains a strict rule that only he writes into the Obsidian vault — the agent reads and generates outputs separately, so pattern detection always reflects his own thinking. Markdown files are the real oxygen of LLMs; if you are serious about building a personal OS with AI, a centralized note-taking tool built on markdown is foundational The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND VIN ON SOCIAL X: https://x.com/internetvin Youtube: https://www.youtube.com/@otherstuffpod Personal Website: https://internetvin.com/Index

I sit down with Nick Vasilescu, founder of Orgo, to break down exactly how people are turning OpenClaw — the open-source computer use agent — into a real revenue stream. Nick walks me through live demos of deploying OpenClaw for business clients, shows how sub-agents and parallelization multiply output, and shares his design-thinking framework for identifying and automating high-value workflows. We even build a TikTok trend-hunting agent from scratch during the episode to prove how fast you can go from idea to working prototype. Timestamps 00:00 – Intro 02:50 – Getting Set Up with OpenClaw 05:02 – Finding the Wedge: Automating Real Business Outcomes 07:39 – The Upwork Hack: Finding Paid Automation Jobs 09:41 – Andreessen Horowitz on Computer Use Agents 11:01 – Setting Up a Client Workspace in Minutes 12:41 – Design Thinking: Mapping Value vs. Effort 15:23 – Using OpenClaw to Prioritize Automations 17:57 – Building Automation Pipelines with Claude Code 19:33 – Sub-Agents vs. Tasks vs. Skills 23:22 – Automation Possibilities are huge 24:54 – Live Build: TikTok Trend Hunter from Idea Browser 32:09 – Start with an MVP Skill, Then Iterate 32:41 – Architecture of the TikTok Agent Script 36:59 – The Arbitrage Opportunity: Most Businesses Still Need Help 40:30 – Agents Are the New SaaS 42:42 – Demoing TikTok Trend Hunter 44:11 – Building Assets & the Abundance AI Will Bring 47:58 – Closing Advice: Get Your Hands Dirty Links Mentioned: Orgo: https://startup-ideas-pod.link/orgo Key Points OpenClaw is more than a personal assistant — it is a deployable business tool that can automate end-to-end workflows for paying clients. The fastest path to revenue is finding automation jobs on Upwork (RPA, desktop automation, workflow building) and fulfilling them with OpenClaw and Claude Code. Sub-agents allow your main OpenClaw instance to delegate specialized tasks, keeping the orchestrator free and multiplying throughput through parallelization. A design-thinking approach — mapping automation opportunities by value vs. effort — is essential before building anything. Verticalizing computer use agents for a specific industry (manufacturing, real estate, distributorships) is the major startup opportunity Andreessen Horowitz is calling out. Always start by building a lightweight MVP skill, test it, debug, and iterate before scaling. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com

I sit down with Frey Chu to go deep on how to use Claude Code to build AI-coded directories, specifically how to tackle the hardest part: getting valuable data. Frey walks us through three real-world directory examples (a funeral home directory, a senior living directory, and GasBuddy), we play a game guessing their traffic and monetization, and then he does a full live walkthrough of the seven-step process he used to build a luxury restroom trailer directory in four days for under $250. I also ask him about the future of directories in a world where LLMs are changing how people search. Timestamps 00:00 – Intro 02:15 – What you’ll learn 03:00 – Directory Game:Parting(Funeral Home Directory) 05:42 – Directory Game: A Place for Mom (Senior Living Directory) 08:00 – Directory Game: GasBuddy (Crowdsourced Gas Price Directory) 12:32 – The Data Moat Thesis 14:02 – Luxury Restroom Trailers: The Niche Directory Demo 15:52 – Before & After: WordPress Directory vs. Claude Code Directory 19:04 – Cost Breakdown: Built in 4 Days for Under $250 21:23 – Step 1: Scraping Raw Data with Outscraper 22:25 – Step 2: Cleaning Data with Claude Code 23:27 – Step 3: Using Crawl4AI for Automated Website Verification 28:01 – Step 4: Enriching Trailer Inventory Data 31:33 – Step 5: Scraping & Verifying Images with Claude Vision 36:33 – Step 6: Amenities, Features & Filter Data 38:31 – Step 7: Service Areas 39:15 – Niche Directory Ideas: Dementia Care, ADA Bathrooms, Tap Water Quality 43:38 – For Naysayers: Is Building a Directory Worth It in 2026? 47:51 – LLMs, AI Search & the Future of Directories Links Mentioned: Outscraper: https://startup-ideas-pod.link/outscraper Crawl4AI: https://startup-ideas-pod.link/crawl4AI Key Points Data is the moat for any successful directory — and with Claude Code plus Crawl4AI, the hardest part (data cleaning and enrichment) is now dramatically faster and cheaper. Every successful directory helps people save time, save money, or make money — and price transparency is a massive, underserved opportunity across boring niches. Frey built a fully enriched luxury restroom trailer directory in four days for under $250, a process that would have taken 2,000+ hours of manual work. Monetization depends on the niche: lead generation, vertical SaaS, agency services, ads, debit cards, affiliate, and marketplace models all work. Directories remain strong in an AI search world because users browsing a directory are in the decision-making phase, especially in high-stakes niches like health, legal, finance, and senior living. Building a directory is one of the best playgrounds to learn Claude Code, SEO, and lead generation — even if the first one is just a learning exercise. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND FREY ON SOCIAL X/Twitter: https://x.com/freychu YouTube: https://www.youtube.com/@FreyChu/featured ShipYourDirectory: https://www.shipyourdirectory.com/

I sit down with Jonathan Courtney, host of Unscheduled CEO Podcast, to talk about the gap between building AI-powered products and actually making money from them. Jonathan walks through his four-step "Promoter Blueprint" — traffic, holding pattern, selling event, and conversion — and shows exactly how he uses Claude and Claude Code to execute each phase. This one is a wake-up call for any founder spending more time optimizing automations than promoting what they sell. Timestamps 00:00 – Intro and Welcome Back 04:13 – The Founder’s Real Job: Promotion, Period 09:23 – The Promoter Blueprint (Screen Share) 19:38 – Using AI with Promoter Blueprint 22:52 – Inside Claude: Jonathan's Claude Workflow 28:41 – Moving from Claude to Claude Code for Builds 30:55 – Building a $450K Webinar Campaign with Claude 37:30 – Scale Up, Abundance Over Efficiency 43:57 – Final Advice: Embrace Your Role as Promoter Key Points A CEO's primary job is promoting the business — building is secondary to getting people in the door. AI tools become "procrastination machines" when builders optimize systems that have zero customers. Every revenue engine follows four phases: traffic, holding pattern, selling event, conversion (and a loop back). Claude projects combined with Claude Code create a fast workflow for going from research to a shipped marketing asset in under an hour. The current play is abundance and scale, using AI to run five campaigns instead of one, rather than cutting headcount for efficiency. Off-the-shelf solutions still beat custom builds in many cases — always ask before you spend three days vibe-coding something. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JONATHAN ON SOCIAL Unscheduled CEO Podcast: https://www.unscheduledceo.com/ X/Twitter: https://twitter.com/Jicecream LinkedIn: https://www.linkedin.com/in/jonathan-courtney-4510644b/

I sit down with James Dickerson, a growth marketer, Claude Code power user, and the mind behind The Boring Marketer, to watch him build an entire marketing system live from the terminal. James walks me through his full workflow: deep research with the Perplexity MCP, positioning angle discovery, direct response copywriting, landing page creation, lead magnet design, ad creative generation with Remotion, and traffic strategy — all inside Claude Code using stacked skills and MCPs. By the end, we have a conversion-ready funnel for a fictional AI marketing agency serving boring local businesses, and James shares the free playbook he created from a two-hour recorded session so listeners can replicate the process themselves. Timestamps 00:00 – Intro and Camera Setup Chat 02:57 – Episode Preview: Building a Vibe Marketing System 06:33 – Perplexity MCP for Market Research 08:13 – Live Demo: Researching an AI Marketing Agency Niche 09:48 – Positioning Angles Skill 11:34 – Direct Response Copywriting Skill 15:43 – Playwright MCP for Competitive Intelligence 17:37 – Keeping Your MCP Stack Simple (Perplexity, Firecrawl, Playwright) 20:59 – Anthropic's Front End Design Skill 25:51 – Remotion: Creating Video Ads from the Terminal 28:47 – Landing Page Review: "Boring Money" Agency 30:43 – Orchestrator Skill: Deciding What to Do Next 34:10 – Lead Magnet Skill 34:10 – Are Skills Underrated 39:08 – Claude Code Costs: $200/Month Max Subscription 42:03 – Live Lead Magnet Review 43:28 – Keyword Research and Traffic Strategy Skills 45:23 – The Evolution of Vibe Marketing 47:11 – Remotion Setup and Ad Creation Demo 54:47 – Final Ad and SEO Page Review 57:25 – Final Thoughts Links Mentioned: Vibe Marketing Playbook: https://startup-ideas-pod.link/vibe_marketing_playbook Vibe Marketing Skills: https://startup-ideas-pod.link/Vibe_marketing_skills Key Points Spending an hour on upfront research with the Perplexity MCP produces dramatically better marketing outputs than jumping straight into prompting. Skills are instruction manuals for your AI agent — the expert perspective you build into them (the last 10–20%) is what separates great output from generic AI slop. You can build a complete marketing funnel — landing page, lead magnet, ad creative, SEO content, and traffic strategy — in a single Claude Code session. Remotion lets you create programmatic video ads directly from the terminal at zero cost, in multiple formats, with custom branding. An orchestrator skill can guide you through what to do next, removing the "I have a landing page, now what?" paralysis. The same Claude Code environment where you build products can also ship your entire marketing system — research, copy, design, and deployment in one place. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JAMES ON SOCIAL X/Twitter: https://x.com/boringmarketer  LinkedIn: https://www.linkedin.com/in/jadickerson/

I sit down with Morgan Linton, Cofounder/CTO of Bold Metrics, to break down the same-day release of Claude Opus 4.6 and GPT-5.3 Codex. We walk through exactly how to set up Opus 4.6 in Claude Code, explore the philosophical split between autonomous agent teams and interactive pair-programming, and then put both models to the test by having each one build a Polymarket competitor from scratch, live and unscripted. By the end, you'll know how to configure each model, when to reach for one over the other, and what happened when we let them race head-to-head. Timestamps 00:00 – Intro 03:26 – Setting Up Opus 4.6 in Claude Code 05:16 – Enabling Agent Teams 08:32 – The Philosophical Divergence between Codex and Opus 11:11 – Core Feature Comparison (Context Window, Benchmarks, Agentic Behavior) 15:27 – Live Demo Setup: Polymarket Build Prompt Design 18:26 – Race Begins 21:02 – Best Model for Vibe Coders 22:12 – Codex Finishes in Under 4 Minutes 26:38 – Opus Agents Still Running, Token Usage Climbing 31:41 – Testing and Reviewing the Codex Build 40:25 – Opus Build Completes, First Look at Results 42:47 – Opus Final Build Reveal 44:22 – Side-by-Side Comparison: Opus Takes This Round 45:40 – Final Takeaways and Recommendations Key Points Opus 4.6 and GPT-5.3 Codex dropped within 18 minutes of each other and represent two fundamentally different engineering philosophies — autonomous agents vs. interactive collaboration. To use Opus 4.6 properly, you must update Claude Code to version 2.1.32+, set the model in settings.json, and explicitly enable the experimental Agent Teams feature. Opus 4.6's standout feature is multi-agent orchestration: you can spin up parallel agents for research, architecture, UX, and testing — all working simultaneously. GPT-5.3 Codex's standout feature is mid-task steering: you can interrupt, redirect, and course-correct the model while it's actively building. In the live head-to-head, Codex finished a Polymarket competitor in under 4 minutes; Opus took significantly longer but produced a more polished UI, richer feature set, and 96 tests vs. Codex's 10. Agent teams multiply token usage substantially — a single Opus build can consume 150,000–250,000 tokens across all agents. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ Morgan Linton X/Twitter: https://x.com/morganlinton Bold Metrics: https://boldmetrics.com Personal Website: https://linton.ai

I sit down with Matt Van Horn, creator of the "Last 30 Days" skill for Claude Code, as he demonstrates how this tool turns anyone into a real-time research expert. By pulling trending data from X, Reddit, and the web, Last 30 Days supercharges Claude Code prompts with current intelligence. Matt walks through live demos, from discovering popular rap songs to generating cold emails to building a Moltbot competitor, showing how non-engineers can ship products using AI tools with almost no coding background. Timestamps 00:00 – Intro 01:39 – What Is "Last 30 Days" 03:29 – Live Demo: Most Popular Rap Songs 04:47 – Cold Email Frameworks Demo 07:04 – Growing an X Following Using Recent Data 07:49 – Researching Moltbot to Build a Competitor 08:26 – Best Practices for Last 30 days 09:26 – Growing an X Following Using Recent Data Results 11:17 – Best Practices for Webdesign Research 13:44 – Building an Enterprise Moltbot Clone Live 17:43 – Generating Figma Prompts and Nano Banana Images 21:54 – Advice for Non-Engineers Getting Started with Claude Code Links Mentioned: Last 30 Days Skill: https://startup-ideas-pod.link/last30days Key Points Last 30 Days searches X, Reddit, and the web for content from the past month, creating highly optimized prompts for Claude Code. The tool requires Claude Code access, an OpenAI API key (for Reddit data), and an XAI key (for X/Twitter access). Matt demonstrates using minimal prompts to generate cold email frameworks, research trending topics, and kickstart new product builds. Compound Engineering serves as a planning tool to turn research into structured project roadmaps. Non-engineers can ship functional products by combining Claude Code with ChatGPT for troubleshooting errors via screenshots. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ Matt Van Horn X/Twitter: https://x.com/mvanhorn

I sit down with Kevin Rose for a live screen share where he walks me through “Nylon,” a personal Techmeme-style news engine he vibe-coded to track AI and tech stories. He breaks down how he pulls from RSS, enriches articles with tools like iFramely, Firecrawl, and Gemini, then generates TLDRs and vector embeddings to cluster stories with real nuance. We dig into his “gravity engine,” an editorial scoring system that ranks stories by impact, novelty, and builder relevance. The bigger theme is simple: with today’s models and workflows, a solo builder can ship wild, high-leverage software fast, then refine by cutting features down to the few that matter. Timestamps: 00:00 – Intro And What Kevin Plans To Demo 03:10 – Techmeme Breakdown And How Signal Gets Ranked 06:44 – RSS Sources, Ingestion, And The Article Pipeline 11:23 – Winner Selection: RSS vs iFramely vs Firecrawl vs Gemini 13:01 – Why iFramely And Firecrawl, Explained 16:37 – TLDRs, Vector Embeddings, And Why They Beat Keyword Search 19:49 – Task Orchestration With trigger.dev And Retries 24:58 – Clusters: Expanding With Search APIs And Discovery 27:07 – The Gravity Engine: Editorial Scoring Rubric 31:31 – Product Management: Gut, Iteration, And Cutting Features 34:53 – Synthetic Audiences And Personal Software 37:03 – What “Success” Looks Like 43:52 – Retention Mechanics And The Idea Browser Example 47:19 – “Blurred Presence” Blog Project From A 12-Year-Old Idea 50:34 – This the best time to build 51:55 – How To Work With Kevin, DIGG Reboot, And VC Today Keypoints I watch Kevin’s end-to-end pipeline for turning messy RSS links into clean, enriched, clustered stories. Kevin uses a “winner” judge to pick the best source of truth per field (summary, main content, metadata). Vector embeddings plus clustering unlock meaning-level grouping that keyword search misses. trigger.dev gives durable background jobs, retries, and observability for a solo builder workflow. His “gravity engine” acts like an editorial layer that prioritizes novelty, impact, and builder relevance. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ Kevin Rose: x: https://x.com/kevinrose personal website: https://www.kevinrose.com/about Youtube: https://www.youtube.com/@KevinRose

I sit down with Kitze to unpack how he uses Clawdbot as a personal OS that runs across Discord, Telegram, and other chat surfaces. We walk through his one-gateway setup, persona-based bots, and the way he structures channels and threads to manage customers, home logistics, and engineering work. We also dig into the self-learning angle: giving an agent shell and network access so it can discover devices, build dashboards, and automate workflows end to end. We close with a lightning round of concrete examples you can adapt across your own life and business. Timestamps 00:00 – Intro 01:42 – The Personal OS Idea 04:20 – Persona Design for Clawdbot 06:00 – Discord As The Control Center 08:23 – Self-Learning Through Shell And Network Access 09:23 – Discord Threads And Agent Workflows 10:13 – Platform Choices: Telegram, Discord, Slack 11:47 – Email Automation, Security, And Model Selection 15:07 – How Agents Change Work 18:00 – Lightning Round of Clawdbot use cases 27:09 – Spellbook: Variable-Driven Prompt Templates 29:15 – Closing Thoughts Key Points I treat Clawdbot like a gateway that routes the same core agent into many persona shells for distinct jobs I keep work organized via Discord sections, channels, and threads so agent output stays searchable I lean on shell and network access to let the agent discover devices and ship automations that span apps, NAS, and smart home I use stronger models for high-trust surfaces like email and credentials, and I scope access gradually I prototype interfaces that turn prompts into parameterized forms so workflows stay reusable and fast The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND KITZE ON SOCIAL X/Twitter: https://x.com/thekitze Tinkerer Club: https://tinkerer.club Personal Website:  https://www.kitze.io

I sit down with Alex Finn to break down how he sets up Moltbot (formally Clawdbot) as a proactive AI employee he treats like a teammate named Henry. We walk through the core workflow: Henry sends a daily morning brief, researches while Alex sleeps, and ships work as pull requests for review. Alex explains the setup that makes this work; feeding the bot deep personal and business context, then setting clear expectations for proactive behavior. We cover model strategy (Opus as “brain,” Codex as “muscle”), a “Mission Control” task tracker Henry built, hardware options, and the security mindset around prompt injection and account access. Timestamps 00:00 – Intro 02:08 – Clawdbot Overview 03:33 – The Morning Brief Workflow 05:01 - Proactive Builds: Trends → Features → Pull Requests 07:27 – The Setup: Context + Expectations For Proactivity 09:38 – The Onboarding Prompt Alex Uses 12:05 – Hunting “Unknown Unknowns” For Real Leverage 12:43 – Using the right Models for cost control 14:18 – Mission Control: A Kanban Tracker Henry Built 17:16 – The future of Human and AI workflow 22:01 – Hardware And Hosting: Cloud vs Local (Mac Mini/Studio) 25:47 – The Productivity Framework 27:10 – The Possible Evolution of Clawdbot 28:53 – Security and Privacy Concerns 33:38 – Closing Thoughts: Tinkering, Opportunity, And Next Steps Key Points I get the most leverage when I treat the agent like a proactive teammate with clear expectations and rich context. Henry delivers compounding value by shipping work for review (pull requests) based on trend monitoring and conversation memory. I separate “brain” and “muscle” by delegating heavy coding to Codex while using Opus for reasoning and direction. I track autonomous work with a dedicated “Mission Control” board so progress stays visible over time. I keep risk contained by controlling environment and account access, especially around email and prompt injection. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ALEX ON SOCIAL Youtube: https://www.youtube.com/@AlexFinnOfficial/videos X/Twitter: https://x.com/AlexFinnX Creator Buddy: https://www.creatorbuddy.io/

I sit down with Furqan Rydhan, a founding team member of Applovin and cofounder Founders Inc, as he walks me through Nebula, a Slack-like workspace where every channel holds an agent that can execute real work across the tools teams already use. We watch Nebula create and edit a Google Slides deck end-to-end, including generating an image and handling failures by retrying until it lands. Furqan shows how Nebula turns one-off work into repeatable “recipes” with scheduled triggers, like adding slides daily or publishing blog posts multiple times per day. We also talk about what “business-in-a-box” looks like in the AI era; where direction, taste, and quality loops become the edge as automation gets widely available. Timestamps: 00:00 – Intro 01:51 –Building useful agents for real work 03:34 – Nebula: a Slack-like agent workspace 05:04 – Demo: Nebula creating a Deck with Google Slides 13:25 – The “business in a box” content dream (newsletters, affiliates, ads) 14:39 – Demo: Automate Blog Posting 15:52 – What stays valuable when everyone automates 21:23 – Agent workforce and Building quality loops 25:38 – Services and agencies: delivering work with fewer humans 28:53 – Final Thoughts Key Points I watch Nebula run like “cloud code for everything else,” automating real work across tools and workflows. Agents turn one-time actions into repeatable systems via triggers and schedules. The interface mirrors Slack because work already lives in channels, threads, and context. Quality becomes the differentiator: critics, scoring, and iteration loops upgrade outputs over time. Service businesses and agencies scale faster when agents handle production-heavy tasks The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND FURQAN ON SOCIAL Furqan's X: https://x.com/FurqanR Fuqan’s personal website: https://furqan.com Nebula: https://www.nebula.gg

In this episode, I sit down with Boris, the creator of Claude Code and one of the key builders behind Claude Cowork, to unpack what Cowork actually unlocks and how people use it in the real world. He walks through a hands-on demo where Cowork organizes files, extracts receipt data, builds a clean spreadsheet, and even drives the browser to create and share a Google Sheet. We go deep on how “agentic” work feels different when the model takes actions across your computer, your browser, and your tools. Then I shift into Boris’s viral workflow for Claude Code: parallel sessions, plan-first execution, Claude.md as a compounding team memory, and verification loops that dramatically improve output quality. Timestamps: 00:00 – Intro 03:26 – Cowork Overview 05:51 – Demo: Folder Access + Renaming Receipts 08:23 – Demo: Turning Receipts Into A Spreadsheet 10:52 – Demo: Google Sheets + Chrome Control 15:52 – Demo: Emailing The Sheet + Parallel Tasking 22:07 – Best way to start/use with Cowork 24:22 – Where will AI and Agents Go Next 28:44 – Boris’s Claude Code Setup 41:12 – The “Claude” Pronunciation Discussion Key Points I use Cowork as a “doer,” not a chat: it touches files, browsers, and tools directly. I think about productivity as parallelism: multiple tasks running while I steer outcomes. I treat Claude.md as compounding memory: every mistake becomes a durable rule for the team. I run plan-first workflows: once the plan is solid, execution gets dramatically cleaner. I give Claude a way to verify output (browser/tests): verification drives quality. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND BORIS ON SOCIAL X/Twitter: https://x.com/bcherny

In this episode, I sit down with Professor Ras Mic for a beginner-friendly crash course on using Claude Code (and AI coding agents in general) without feeling overwhelmed by the terminal. We break down why your output is only as good as your inputs and how thinking in features + tests turns “vague app ideas” into real, shippable products. Was walks me through a better planning workflow using Claude Code’s Ask User Question Tool, which forces clarity on UI/UX decisions, trade-offs, and technical constraints before you build. We also talk about when not to use “Ralph” automation, why context windows matter, and how taste + audacity are the real differentiators in 2026 software. Timestamps 00:00 – Intro 01:22 – Claude Code Best Practices 05:31 – Claude Code Plan Mode 09:30 – The Ask User Question Tool 14:52 – Don’t start with Ralph automation (get reps first) 16:36 – What are “Ralph loops” and why plans and documentation matter most 18:41 – Ras’s Ralph setup: progress tracking + tests + linting 23:48 – Tips & tricks: don’t obsess over MCP/skills/plugins 27:44 – Scroll-stopping software wins Key Points Your results improve fast when you treat AI agents like junior engineers: clear inputs → clean outputs. The biggest unlock is planning in features + tests, not broad product descriptions. Claude Code’s Ask User Question Tool forces real clarity on workflow, UI/UX, costs, and technical decisions. If you haven’t shipped anything, don’t hide behind automation—build manually before using “Ralph.” Context management matters: long sessions can degrade quality, so restart earlier than you think. Numbered Section Summaries The Real Reason People Get “AI Slop” I frame the episode around a simple idea: if you feed agents sloppy instructions, you’ll get sloppy output. Ras explains that models are now good enough that the failure mode is usually unclear inputs, not model quality. How To Think Like A Product Builder (Features First): Ras pushes a practical mindset: don’t describe “the product,” describe the features that make the product real. If you can list the core features clearly, you can actually direct an agent to build them correctly. The Missing Piece: Tests Between Features: We talk about the shift from “generate code” to “build something serious.” The move is writing and running tests after each feature, so you don’t stack feature two on top of a broken feature one. Why Default Planning Mode Isn’t Enough: Ras shows the standard flow: open plan mode, ask Claude to write a PRD, and get a basic roadmap. The issue is it leaves too many assumptions—especially around UI/UX and workflow details. The Ask User Question Tool (The Planning Upgrade): This is the big unlock. Ras demonstrates how the Ask User Question Tool interrogates you with increasingly specific questions (workflow, cost handling, database/hosting, UI style, storage, etc.) so the plan becomes dramatically more precise. Spend Time Upfront Or Pay For It Later: We connect the dots: better planning reduces back-and-forth, reduces token burn, and prevents “I built the app but it’s not what I wanted.” The interview-style planning forces trade-offs early instead of late. Don’t Use Ralph Until You’ve Built Without It: Ras makes a strong case for reps: if you can’t ship something end-to-end yet, automation won’t save you—it’ll just move faster in the wrong direction. Build feature-by-feature manually first, then graduate to loops. Practical Tips: Context Discipline + Taste Wins: Ras shares a few operational habits: don’t obsess over tools like MCP/plugins, keep context usage under control, and restart sessions before quality degrades. We wrap on a bigger point: in 2026, “audacity + taste” is what makes software stand out. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND MIC ON SOCIAL X/Twitter: https://x.com/Rasmic Youtube: https://www.youtube.com/@rasmic

Today I’m joined by Samuel Thompson, an internet capitalist who’s launched 100 companies in 10 years, and he walks me through a live, end-to-end build of an info product using AI. We break down how he goes from idea → AI-written book → mockups → Shopify product page → ad creatives in a ridiculously short amount of time. The big takeaway is that this isn’t just “info products,” it’s a repeatable launch system you can apply to e-comm, SaaS, mobile apps, and pretty much anything where customer acquisition matters. We also get into the real game: CAC vs LTV, conversion rates, and how to build what Sam calls a “rigged slot machine” you can scale. Timestamps 00:00 – Intro 02:32 – Choosing the offer 05:36 - Writing ebook with ChatGPT (outline → chapters → upgrade quality) 07:30 – Mockups with Canva & Envato Elements 10:25 – Shopify themes that convert (Solo Drop + Elixir) 12:05 – Finding products to sell 16:28 - Building the Shopify Store 21:16 – Using ChatGPT to generate product-page copy fast 24:13 – What “good” conversion rates look like (3–5% target range) 28:51 – Bonus gifts strategy = perceived value + conversion lift 33:26 – HeyGen for AI photo/video ad assets + voice clone insight 35:37 – Canva static ads + high-performing angles 38:57 – Big picture: one person can build a “real business” with AI Key Points Sam’s launch loop is offer → AI asset creation → Shopify page → Meta ads → iterate on math Start with low-friction products (ebook/info) to validate customer acquisition fast The real framework is CAC vs AOV vs conversion rate, not “brand vibes” 3–5% conversion rate is a strong target on a direct-response product page Use bonus gifts to increase perceived value and lift conversion Static ads + strong angles can outperform everything when the message hits The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND SAMUEL ON SOCIAL: X/Twitter: https://x.com/samuelthompson

In this episode, I sat down with Chris Koerner and we go through a set of approachable startup ideas that start low-friction but can scale if you get distribution right. We start with a potential “app ecosystem” opportunity around Facebook Marketplace, plus a product-studio framework that combines short-form video, AI, and 3D printing to validate “dumb” products via demand before you invest. We then jump to more grounded, local-first ideas—bike washing/maintenance subscriptions, bar anti-spike stickers, and even vending-machine concepts like “shiny rock” drops at trailheads. We close with a weird Pokémon-card “meme + supply control” play inspired by the Kabuto King, including Chris’s own collecting “big reveal.” From there, I dig into why PSA-style grading feels slow and expensive, and we workshop a more modern grading experience (including a livestream/packaging angle and an AI-from-photo approach). Timestamps 00:00 – Intro 02:28 – Startup Idea 1: Facebook Marketplace App Studio 07:43 – Startup Idea 2: DTC Product Studio 17:05 – Startup Idea 3: Bike Washing/Maintenance Subscription 24:29 – Startup Idea 4: Anti-Drink-Spike Stickers 31:55 – Startup Idea 5: Shiny Rock Vending Machines 36:37 – Startup Idea 6: The Kabuto King and Card Grading Key Points I look for “alpha” where people are already obsessing, but the market structure is still primitive (like collectibles + grading). I treat “distribution” as the multiplier—short-form can make “dumb” products viable if the content loop is strong. I push for starting manually first (prove demand), then upgrading into infrastructure, subscriptions, and scale. I pay attention to marketplaces with huge usage but weak third-party tooling—there’s often a platform-layer opportunity there. I keep coming back to “repackaging” as a business model: same underlying thing, new wrapper, new buyer, new channel. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CHRIS ON SOCIAL: X/Twitter: https://x.com/mhp_guy Instagram: https://www.instagram.com/thekoerneroffice/ Youtube: https://www.youtube.com/@thekoerneroffice

We got Ryan Carson on the pod to break down the “Ralph Wiggum” Agent and why it’s suddenly everywhere. He walks me through a simple workflow that lets an autonomous agent build a full product feature while I sleep: start with a PRD, convert it into small user stories with tight acceptance criteria, then run a looped script that ships work in clean iterations. The big idea is you’re not “vibe coding” one giant prompt—you’re giving the agent testable, bite-sized tickets and letting it execute like an engineering team. By the end, Ryan shows how this becomes repeatable (and safer) with a memory layer—agents.md for long-term notes and progress.txt for iteration-to-iteration context. Timestamps 00:00 – Intro 02:44 – What is the Ralph Wiggum AI Agent 03:40 – Step 1: PRD Generator 06:11 – Step 2: Convert PRD to Json 09:47 – Step 3: Run Ralph 12:05 – Step 4: Ralph Picks a Task 13:14 – Step 5: Ralph Implements Task 14:49 – Tokens + Cost: What It Actually Spends 15:45 – Guardrails: Small Stories + Clear Criteria Keep It Sane 16:19 – Step 6: Ralph commits the change 16:38 – Step 7: Ralph Updates PRD json file 16:55 – Step 8: Ralph Logs to Progress txt 20:08 – Step 9: Ralph Picks another Task 20:48 – Step 10: Ralph Finishes Tasks 21:18 – Example of how Ryan uses Ralph 24:08 – How To Start Today (Ralph Repo) and Tips Links Mentioned: Ralph Wiggum Agent: https://startup-ideas-pod.link/Ralph-agent  AI Agent Skills: https://startup-ideas-pod.link/amp-skills  AMP: https://startup-ideas-pod.link/amp-code  Ryan’s Ralph Step-by-Step Guide: https://startup-ideas-pod.link/Ryans-Ralph-Guide Key Points I can’t expect “sleep-shipping” unless I translate the feature into small, testable user stories with clear acceptance criteria. Ralph works like a Kanban loop: pull one story, implement, commit, mark pass/fail, then grab the next. The real leverage is the reset: each iteration starts fresh with a clean context window, instead of one giant, messy thread. agents.md becomes long-term memory across the repo; progress.txt is short-term memory across iterations. The bottleneck isn’t “coding”—it’s the upfront spec quality: PRD clarity, atomic stories, and verifiable criteria. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND RYAN ON SOCIAL: X/Twitter: https://x.com/ryancarson Amp: https://ampcode.com

In this episode, I’m breaking down a guide from Ben Tossel on how you can actually build with AI agents without being technical. I walk through what he’s shipped as a “non-technical” builder, why he lives in the terminal/CLI, and the exact workflow he uses to go from idea → spec → build → iterate. We also talk about the meta-skill here: treating the model like your over-the-shoulder engineer/teacher, and using every bug as a learning checkpoint. The takeaway is simple: pick a tool, ship fast, fail forward, and build your own system as you go. Ben’s Article: https://startup-ideas-pod.link/Ben-Tossell-Article Timestamps 00:00 – Intro 01:04 – What Ben Has Shipped 03:21 – The Workflow: Feed Context → Spec Mode → Let The Agent Rip 07:52 – His Agent Setup 08:56 – Coding On The Go 10:07 – Things to Learn 13:33 – The New Abstraction Layer: Learning To Work With Agents 14:33 – Learning from Others 16:15 – Use The Model As Your Teacher (Ask Everything) 18:13 – Contributing to Real Products 19:13 – Why this is Different 21:31 – Asking Silly Questions 24:00 – Beyond “Vibe Coding”: A New Technical Class 24:43 – Vibe Coding is a game 27:12 – Fail Forward + Permission To Build And Throw Things Away 28:16 – Pick One Tool, Minimize Friction, Keep Shipping Key Points I don’t need to be a traditional engineer to ship—I can learn by watching agent output and iterating. The terminal/CLI is the power move because it’s more capable and I can see what the agent is doing. “Spec mode” works best when I interrogate the plan like a philosopher instead of pretending I understand everything. agents.md becomes my portable instruction manual so every new repo starts clean and consistent. The fastest learning path is building ahead of my capability and treating bugs as checkpoints—fail forward. Numbered Section Summaries The Thesis: Non-Technical Doesn’t Mean Non-Builder I open with Ben’s core claim: you can ship real software by working through a terminal with agents, even if you can’t write the code yourself—because you can read the output and learn the system over time. Proof: What He’s Actually Shipped I run through examples Ben built—custom CLIs, a crypto tracker, “Droidmas” experiments, an AI-directed video demo system, and automations that keep projects moving even when he’s away from his desk. The Workflow: Context → Spec Mode → Autonomy High Ben’s process is straightforward: talk to the model to load context, switch into spec mode to pressure-test the plan, link docs/repos for exploration, then let the model run while he watches and steers when needed. http://agents.md/ The “Readme For Agents” That Follows You Everywhere I explain why agents . md matters—one predictable place to tell your agent how you want repos structured, how to commit, how to test, and what “good” looks like so each session gets smoother. Coding On The Go: PRs, Issues, Phone, Telegram, Slack We get into the real “agent native” behavior: install the GitHub app, work via pull requests and issues, tag the agent to self-fix, and even push changes from your phone—plus using Slack as a one-person “product” with an agent in the loop. Learning The Primitives: Bash, CLIs, VPS, Skills I cover the building blocks Ben’s learning: bash commands and repeatable terminal workflows, preferring CLIs over MCPs to save context, and using a VPS + syncing to keep projects always-on. The Mindset Shift: The Model Is The Teacher The real unlock is treating the model like your patient expert—ask everything you don’t understand, bake “explain simply” into your agent instructions, and close knowledge gaps as they appear. Fail Forward, Pick One, Keep Shipping I end on the playbook: build ahead of your capability, treat it like play, give yourself permission to throw things away, and stop tool-hopping—pick one system and go deep. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I walk through Alibaba’s new AI agent tool, Accio, and show how it helps you go from “what should I build?” to actual product concepts and supplier options. I demo how it spots rising trends, pulls specific product opportunities (with context like search and sales movement), and even generates early design concepts. Then I test it on a real research task and use that to spin up a “cozy gaming” keyboard concept aimed at Gen-Z women. I close by showing how Accio can vet suppliers and even draft a supplier outreach email so you can start the sourcing process faster. Timestamps 00:00 – Intro 01:55 – Trend Spotting Demo 03:31 – Designing Products Demo 07:04 – Product Opportunity Pain Points Demo 10:10 – Supplier Search Demo 11:06 – Mechanical Keyboard Market Research and Pain Points 16:03 – Cozy Gaming Mechanical Keyboard For Gen Z Women 18:42 – Supplier Vetting + Due Diligence 22:00 – Supplier Outreach Key Points Accio compresses the e-commerce workflow: trends → product ideas → design concepts → supplier shortlists. The real leverage is pairing insights (ratings, negative tags, review pain) with concrete product recommendations. The “agent task” flow feels like a research assistant: it gathers sources, updates a plan, and synthesizes outputs. Accio can move from concept to execution by suggesting suppliers and drafting a structured inquiry email. You still need real diligence: call suppliers, vet claims, and start with small orders. Numbered Section Summaries Accio As An “Unfair Advantage” For E-Commerce I introduce Accio as an AI agent built around e-commerce workflows—idea generation, trend analysis, product concepts, and supplier sourcing. My core point is it reduces the friction that usually keeps me (a software person) from starting e-commerce. Trend Spotting That Goes Beyond Generic Charts Using a baby products example, I show that it’s not just search/sales graphs—it surfaces specific product categories and differentiators (like smart features) plus recommendations you can validate elsewhere. Turning Pop Culture Into Product Concepts (With Caveats) I try a “Squid Game” prompt to generate product directions and visuals. I’m clear this isn’t a “press button, print money” system, but it gets the creative juices flowing and connects ideas to sourcing. Finding Opportunities By Reading What Customers Hate In the senior dog pet supplies example, Accio highlights product opportunities and connects them to the underlying pain (accessibility, cognitive decline, weak ratings). I emphasize that the edge is insight—knowing why current products underperform. Supplier Discovery Without The Usual Alibaba Overwhelm I run a supplier prompt with constraints (OEM, private label, MOQ, certifications, reviews). The key is Accio structures what’s normally chaotic and gives a shortlist you can actually act on. Agent Research: Mechanical Keyboard Pain Points, Ranked I test an agent task to find unmet pain points and cluster them by theme, with “proof” from reviews/forums/Q&A. The point isn’t keyboards—it’s showing how fast you can go from “trend” to “what to build” using structured research. From Pain Points To A Launchable Niche Concept (Cozy Gaming) I pivot from the research into a niche: mechanical keyboards for Gen Z women aligned with “cozy gaming.” Accio proposes brand directions, a flagship product concept, and early roadmap thinking. Reality Check: Sourcing, Verification, And Outreach I ask for trusted suppliers and get a short list plus technical verification prompts (finish, sound profile, color matching). Accio then drafts a supplier email and shows how the workflow can extend to sending inquiries—while I remind you to vet suppliers carefully and start small. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this episode, I walk through a beginner-friendly, step-by-step way to set up Claude Skills so you can get more consistent, higher-value output over time. I show where to enable Skills (it’s not on by default), how to create a new skill using Claude’s “create a skill together” flow, and why Skills are different from Projects for ongoing, reusable workflows. Then I demo a real example: building a conversion-focused copywriting review skill for an agency workflow, installing it, and testing it on app store screenshots + website copy. I close with how to level up Skills by iterating them over time, using a 10-step process I reference from a “Boring Marketer” tweet. Timestamps: 00:00 – Intro 00:40 – Enable Skills (Settings → Capabilities → Skills Preview) 01:21 – Creating a new skill 06:34 – Why Skills are important Projects for “always-on” workflows 07:49 – Reviewing the skill 10:34 – Installing the skill (copy to skills / upload in Skills) 11:28 – Testing the Skill 16:14 – How to improve skill over time Key Points Skills make Claude’s output more consistent because you bake in reusable context and workflows. Skills aren’t enabled by default—turn them on in Settings → Capabilities. The easiest path for most people is “Create a skill together,” then answer Claude’s scoping questions. A strong skill includes frameworks, scoring, and an output template—not vague advice. The real power comes from iterating: test on real scenarios, critique, refine, and keep improving the skill over time. Numbered Section Summaries Why Skills Matter For Beginners I open by explaining that Skills help you get more consistent, higher-value output from Claude over time, especially if you’re a beginner and want repeatable results. Turn On Skills First Skills aren’t enabled by default, so I show the exact path: Settings → Capabilities → enable the Skills preview feature. Create A Skill (Three Paths) I walk through the three options: create with Claude, write skill instructions, or upload an existing skill Build A Real Skill: Conversion Copy Review I describe the skill I want: a conversion-focused copywriting reviewer for apps and websites, built like a specialist “employee” that can critique headlines, CTAs, value props, pricing pages, and more. Skills vs Projects (And Why Skills Win For Ongoing Work) I explain why I prefer Skills for ongoing workflows: Projects can be context-specific to a campaign, while Skills are meant to work across day-to-day work regardless of the project timeline. What Claude Generates (And Why Markdown Is Great) I show Claude generating the skill structure and markdown files (like skill md and framework docs), and I call out why markdown is practical and easy for non-technical folks to edit. Install + Test The Skill On A Real Example I install the skill (copy to Skills / upload) and test it on real assets—app store screenshots and website copy—to see if it actually follows the skill workflow. Make The Skill Better Over Time (The Improvement Loop) I share the idea that Skills shouldn’t stay static. I reference a 10-step process (understand the problem, explore failures, research, synthesize, draft, self-critique, iterate, test, finalize) and emphasize ongoing iteration based on real outputs. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

Today I break down a big news item I think is flying under the radar: OpenAI quietly launched Skills for Codex, and I explain what that means (and how it differs from sub-agents and MCPs). I then share a fast-moving trend I’m watching and why it’s a strong wedge for a simple app. After that, I recommend the to-do app I’ve used for 14 years and give away a startup idea. I close with a practical 6-step framework for going from idea → viral validation → mobile app launch in 2026. Timestamps 00:00 – Intro: the new format (news, trend, app, startup idea, framework) 00:40 – AI New Item: OpenAI launches Skills for Codex 05:45 – Trend: Face Yoga 07:56 – App Recommendation: Things 09:33 – Startup Idea: Call-an-expert service for non-developers stuck at 80% done 14:44 – Framework: Viral Mobile App Framework Key Points OpenAI “Skills” make Codex/ChatGPT more reusable and consistent by packaging repeatable workflows. A “skill” is the recipe, a “sub-agent” is extra worker instances, and an “MCP” is the tool access plug. Face yoga is an emerging sub-niche with clear app potential (simple routines, monetization via paid or ads). Last 20 is a practical marketplace idea: pay for 15 minutes of expert unblock help to finish the last 20%. Viral validation favors apps that are visually obvious, explainable in three words, and tied to insecurity-driven outcomes. Numbered Section Summaries OpenAI Skills: The Quiet Upgrade I walk through OpenAI’s launch of Skills for Codex—reusable bundles of instructions/scripts/resources that can be called directly or chosen automatically. I’m excited because this makes agent workflows more consistent and scalable across tasks. The Foundation: Skill vs Sub-Agent vs MCP I clarify the taxonomy: a skill is the written playbook, sub-agents are extra “worker” copies of the model that split a big job, and MCPs are what let the model access external systems like tickets or repos. This is the mental model I want everyone using going into 2026. The Trend: Face Yoga As An App Wedge I share a niche trend I’m seeing—face yoga—and why it’s a product opportunity similar to how yoga apps became huge. I call out the obvious app angles: guided routines, jawline/face-slimming programs, and content-driven growth via short videos. The Tool: Things (My Simple Focus System) I recommend the Things to-do app because it’s simple: “Today,” “Upcoming,” and “Someday,” without a monthly fee. I also note what’s missing (I’d like more AI features), but it still wins for focus if you don’t want a “kitchen sink” system. The Startup Idea: Last 20 (Phone-A-Friend For Vibe Coders) I give away the idea: builders get stuck at 80% after using Cursor/Replit/V0, so Last 20 matches them with someone who’s solved that exact wall before. The product is a fast screen-share session—problem solved—priced per session or bundled for teams/agencies, with the marketplace taking a cut. The Distribution Framework: Viral Validation → Launch I share a 6-step process: warm up the account, design a visually obvious app, build a tiny MVP fast, post daily until something hits, build the community before the product, then launch with a hard paywall and keep content rolling. It’s a simple playbook for getting to organic traction in 2026. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this episode, I go over one AI news item I can’t stop thinking about, one trend you can build a business around, two tools I’m using, one startup idea you should steal, and one framework to end on. I start with a leak suggesting Anthropic is productizing “agent mode” for Claude with structured task buckets and a progress/context UI. Then I use Hyrox as an example of how I validate trends quickly with search data (and what “low competition + cheap CPC + explosive growth” signals). I wrap by pitching a hotel guest-communication concierge and the “thousand people framework” for getting to clarity on your ICP and what they’ll reliably pay for. Timestamps 00:00 – Intro 00:32 – AI New Item: Anthropic leak: Agent Task Mode for Claude 04:47 – Trend: Hyrox 08:59 – AI App: Krea and Notebook LLM 12:23 – Startup idea: Digital Hotel Concierge 15:59 – Framework: The “1000 People” For founders doing $50k+ MRR+: https://startup-ideas-pod.link/offline-mode Key Points Agent workflows get “productized” when the UI guides the task (not just a blank prompt box). Trend validation can be fast: look for explosive growth + low competition + cheap CPC, then ideate apps around it. NotebookLM’s slide generation is an underrated workflow for turning sources into clean decks. The “Guest Guide” concept is a simple AI/QR wedge: answer repetitive hotel questions and monetize per property. The thousand-people exercise forces clarity: who exactly buys, what they pay yearly, and how you reach them. Section Summaries The Claude Agent Mode Leak I break down a leak claiming Anthropic is preparing a more structured “agent mode” for Claude, organized into buckets like research, analyze, write, and build plus choices like depth, format, and outputs. The big shift is moving from “open chat” to “delegating distinct tasks” with visibility into progress and context. Productized Prompts = Better Output I explain why a blank text box can be daunting, and why UI that scaffolds intent (validate/compare/forecast, quick vs. thorough, doc vs. slides vs. spreadsheet) can make results meaningfully better. To me, it points at a future where you “check in” on agents like teammates. Trend Hunting I use Hyrox, an indoor fitness competition that’s “like the new CrossFit,” as a real example of how I sanity-check whether something is becoming a business opportunity. The workflow is simple: I see it in culture, then I go straight to Idea Browser to pull search/CPC/competition signals. Two Tools I’m Testing I call out Krea as a creative AI subscription bundling multiple models, and then I highlight NotebookLM’s slide/infographic feature as the underrated part—turning a source (including transcripts) into clean, well-designed slides with strong hierarchy. Steal This: Guest Guide I pitch a hotel digital concierge that handles common guest questions via QR-code guides, priced per property with affiliate upside, and I reference Sadie as an adjacent AI hospitality product (more on calls/reservations). Then I close with the “thousand people framework”: define the real ICP, map what they’ll pay yearly, and figure out distribution—because clarity is the driver. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

I’m joined by Sahil Bloom for a throwback episode where he walks me through his “personal annual review,” a 7-question framework to reflect on 2025 and set yourself up to crush 2026. We talk about why reflection beats raw experience, how to use your calendar to surface what you’ve actually changed your mind on, and how to identify what creates vs. drains your energy. We dig into “boat anchors” (the hidden drag holding you back), what fear kept you from doing, and how to learn from both your greatest hits and worst misses. By the end, you’ll have a practical set of questions you can answer on paper to extract real insights from the year and carry them forward. Get the Personal Review Template: https://www.sahilbloom.com/annual-review Timestamps 00:00 – Intro 02:54 – Why Reflection Matters (The “Annual Review” Setup) 04:12 – Q1: What Did I Change My Mind On? 11:29 – Q2: What Created Energy This Year? 18:58 – Q3: What Drained Energy This Year? 25:05 – Q4: What Were The Boat Anchors In My Life? 33:06 – Q5: What Did I Not Do Because Of Fear? 39:51 – Q6: Greatest Hits & Worst Misses (And Why) 44:04 – Q7: What Did I Learn This Year? (Synthesize 3–10 Learnings) Key Points You don’t learn from “having a year,” you learn from reflecting on it, and that reflection becomes usable data for the next year. Your outcomes follow your energy, use your calendar to identify what creates energy and what drains it, then adjust accordingly. For “draining” activities, evaluate how you feel after (not during), because many high-value things feel hard in the moment. The fastest progress often comes from cutting what holds you back (“boat anchors”), not adding new habits or protocols. Fear is often inexperience (not inability); shine a light on it with deconstruction exercises (e.g., upsides vs. downsides) and take action. “Hits vs. misses” reflection prevents bias, overly critical people only see misses; optimists only see wins, both lose learning. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND SAHIL ON SOCIAL X/Twitter: https://x.com/SahilBloom Instagram: https://www.instagram.com/sahilbloom/?hl=en YOUTUBE: https://www.youtube.com/@Sahil_Bloom

In this solo episode, I walk through 10 concrete rules to get way more out of Claude Code and Claude Opus 4.5, based directly on tips Anthropic has shared in their docs and blog posts. I show how to move from vague prompts to architected briefs that use tone, constraints, structure, and power phrases to avoid “AI slop.” I demo examples across writing, research, teaching, and planning so you can see exactly how to apply each rule. By the end, you have a practical playbook for prompting Claude like a teammate and using it as a true thinking partner in your work. Timestamps 00:00 – Intro 00:56 – Rule #1: Tone of collaboration 02:16 – Rule #2: Principle of explicitness (action verbs, quantity, audience) 03:20 – Rule #3: Define the boundaries with clear constraints 04:26 – Rule #4: Draft, plan, then act (outline → refine → execute) 06:39 – Rule #5: Demand structured output (tables, formats, schemas) 08:00 – Rule #6: Explain the “why” behind your request 09:05 – Rule #7: Control brevity vs. verbosity (expert, brief, simplifier) 10:21 – Rule #8: Provide a scaffold and templates 11:21 – Rule #9: Use “power phrases” and expert personas 12:28 – Rule #10: Divide and conquer complex projects 14:09 – Putting it all together with an example For founders doing $50k+ MRR+: https://startup-ideas-pod.link/offline-mode Key Points I share 10 specific prompting rules that come directly from how Anthropic suggests people use Claude. I show how friendly, clear, and firm prompts beat either vague or overly polite requests. I demonstrate how explicit constraints (length, style, audience, banned words) create more creative and focused outputs. I use outlines, scaffolds, and structured formats to turn Claude into a planning and synthesis engine instead of a random text generator. I introduce “power phrases” like “think step by step” and “critique your own response” to unlock more advanced reasoning. I wrap everything into a final Stoicism lecture prompt that combines persona, context, constraints, structure, and tone. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

On this episode I sit down with Rob Hoffman, who runs a portfolio of profitable SaaS businesses (Contact, Mentions, Kleo). Rob breaks down six proven customer acquisition playbooks using real examples doing between ~$20K and $300K MRR. The episode walks through concrete strategies like waitlist launches, trend-jacking, language arbitrage, AI search, signal-search, and high-ticket ads. You will learn how to go beyond “vibe coding” and use structured marketing systems to get their first customers, raise prices, and scale more predictably. Timestamps 00:00 – Intro 04:16 – 1) Waitlist Strategy: Kleo & Mentions Case Study 19:45 – 2) Wave Surfer Strategy: TrustMRR Case Study 27:54 –3) Language Arbitrage Strategy: Teachizy Case Study 33:53 – 4) AI Search Strategy: Tally Case Study 40:30 – 5) Signal Search Strategy: LocalRank Case Study 50:04 – 6) High Ticket Ad Strategy: MailScale Case Study Key Points Most indie builders can ship products but struggle to get customers; Rob packages his experience into six repeatable acquisition playbooks. The Waitlist Strategy pairs “edgy sales” content with email nurturing, scarcity, and beta cohorts to quickly reach tens of thousands in MRR. Riding an existing wave (like fake-MRR discourse on X) plus product-led virality can generate huge attention, which is better monetized with ads than subscriptions. Language and geo arbitrage—cloning a winning SaaS into another language/market—combined with non-English SEO is “marketing on easy mode.” AI search (ChatGPT, Perplexity, Claude) is an overpowered channel right now; deep “alternatives/versus/best of” pages are heavily cited and convert far better than Google traffic. Feature-first launches, faceless accounts, and enterprise plans let products like LocalRank and MailScale stack MRR with small audiences, YouTube demos, and high-ticket sales. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND ROB ON SOCIAL X/Twitter: https://x.com/RobHoffman_ Kleo: https://kleo.so

On this episode, I breakdown eight little-known mobile apps that each generate around $50,000+ per month and explain why they work. I walk through specific examples—from AI video generators and Bible note-takers to vinyl pricing tools and AI English tutors—then explain the common patterns behind their success. The second half of the episode is devoted to six clear frameworks for spotting high-potential niches and designing simple, sticky mobile apps around them. I end the episode with a batch of extra startup ideas built on high-intent inputs like photos, videos, and scans so listeners can “vibe code” their own profitable apps in 2026. Timestamps 00:00 – Intro 02:02 – App 1: Flashloop: AI Video Generator for Viral Character Clips 03:26 – App 2: Bible Note-Taker & Prayer Recorder for Churchgoers 06:35 – App 3: AI Home Decor Interior Design App and Visualization Pain 08:48 – App 4: Moji Lab: Emoji/Sticker Packs and Expression as a Business 11:43 – App 5: Vinyl Snap: Scanning Vinyl Records for Accurate Pricing 13:51 – App 6: Genora AI: Bundling Multiple LLMs into One Assistant 16:45 – App 7: Logo Maker: AI Generated Logos 18:57 – App 8: Menu Fit: Healthy Eating Recommendations at Any Restaurant 20:44 – App 9: LangLearn: Personal AI English Tutor and Duolingo Comparison 22:37 – App 10: Zozo Fit 3D Body Scanner: Tracking Body Change, Not the Scale 25:04 – The “ 50K MRR App Framework” 31:30 – Bonus Startup Ideas Key Points Profitable mobile apps often do one high-intent, recurring job for a specific identity-based group, then charge a subscription around that behavior. Many breakout apps turn photos, videos, or scans (high-signal inputs) into premium insights like valuations, design plans, or tailored recommendations. Simple, one-screen interfaces with clear before/after transformations make these AI-powered tools feel approachable and addictive to use. The “50K MRR App Framework” combines spending power, repeating problems, visual inputs, accuracy needs, and bad existing tools to guide idea selection. New app ideas can be generated by pairing these frameworks with underserved niches like golf swings, pet health, used cars, or RV layouts. Numbered Section Summaries Why Mobile Apps Are Printing Money in 2026 The host opens by arguing that now is an incredible time to build mobile apps, pointing to new apps that have appeared “out of nowhere” and reached $50K+ per month. He cites a tweet listing 10 such apps launched in the last 180 days and sets the goal of reverse engineering what makes them work so listeners can apply the patterns to their own ideas. The 50K MRR App Framework The “50K MRR App Framework”: find a group that (1) spends money, (2) has a repeating problem, (3) uses photos/videos as inputs, (4) cares deeply about accuracy, and (5) suffers from bad existing tools. He walks through how vinyl collectors fit every criterion and stresses that while the framework is simple, execution still requires great UX, clean UI, and the right niche. The goal is to make idea selection easier by checking all five boxes before committing to an app. Six Supporting Frameworks for Designing Hit Apps I expands into six additional frameworks: start with a “nerve” (identity, urgency, stakes, repetition); solve one job that always must be done; build around a single high-intent input (photo, address, object); use AI to unlock a premium insight (price, diagnosis, summary, design plan); wrap it in a simple, desirable interface (one screen, one button, one transformation); and create a recurring behavior loop that pulls users back daily or weekly. He summarizes these in a conceptual pipeline: high-intent input → AI premium insight → simple interface → recurring loop → $50K MRR. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

On this episode I sit down with indie app builder and designer Chris ****Raroque to walk through his real AI coding workflow. Chris explains how he ships a portfolio of productivity apps doing thousands in MRR by pairing Claude Code and Cursor instead of picking just one tool. He live-demos “vibe coding” an iOS animation, then compares how Claude Code and Cursor’s plan mode tackle the same task. The episode closes with concrete tips on plan mode, MCP servers, AI code review, dictation, and deep research so solo devs can build bigger apps than they could alone. Timestamps 00:00 – Intro 03:04 – Which Tools & Models to Use 09:16 – Thoughts on the Vibe Coding Mobile App Landscape 11:14 – Live demo: prompting Claude Code to build an iOS “AI searching” animation 18:07 – Live demo: prompting Cursor with same task 21:02 – Chris’s Best Tips for Vibe Coders Key Points You don’t have to pick one IDE copilot: Chris actively switches between Claude Code and Cursor because they have different strengths. For very complex bug-hunting, he prefers Cursor with plan mode; for big-picture app architecture, he leans on Claude Code with Opus. Non-developers should start on higher-level “vibe coding” platforms like Create Anything for mobile apps before graduating to Claude/Cursor. Plan mode plus detailed, spoken prompts dramatically improves code quality, especially for UI and animation work. MCP servers and AI code review bots let solo developers safely set up infra, enforce security, and catch bugs they’d otherwise miss. Claude’s deep research is a powerful way to choose the right patterns and libraries before handing implementation back to Claude Code or Cursor. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CHRIS ON SOCIAL Youtube: https://www.youtube.com/@raroque X/Twitter: https://x.com/raroque Instagram: https://www.instagram.com/chris.raroque/

Join me as I sit down with Jonathan Courtney to host the second annual “Sippy Awards,” the most prestigious award show in tech for the products, games, and tools that shaped 2025. We crown our most-hyped products for 2026, favorite games of the year, best productivity tools, and best products under $100. We also dive into analog tools like Traveler’s Notebook, hi-fi systems, Japanese porcelain, and simple clothing uniforms as ways to make everyday life better and de-fragment your brain. Timestamps 00:00 – Intro 03:23 – Most Hyped Product of 2026 14:43 – Game of the Year 2025 19:49 – The Way to Innovate 25:41 – Premium Domains 29:56 – Best Productivity Product 42:02 – Favorite Product of 2025 54:10 – Best products under $100. Key Points The Sippy Awards are a playful but serious way for Greg and Jonathan to highlight the products and games that genuinely improved their lives in 2025. They argue that cult classics (Wind Waker, Pinkerton, Kid A, Breath of the Wild, Elden Ring) come from creators who put the audience last and follow their own taste, even at the risk of initial backlash. Distinctive visual identities and premium dot-com domains are framed as both trust builders for users and commitment devices for founders. Their favorite productivity and lifestyle tools—ChatGPT, Things, Endel, Traveler’s Notebook, YouTube Premium, Japanese porcelain—show how small, well-crafted tools reshape daily workflows and rituals. Analog practices (morning pages, notebooks, hi-fi listening) and simple clothing uniforms are presented as ways to de-fragment your brain, reduce decision fatigue, and focus on what matters. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: thevibemarketer.com Startup Empire - get your free builders toolkit to build cashflowing business - https://startup-ideas-pod.link/startup-empire-toolkit Become a member - https://startup-ideas-pod.link/startup-empire FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND JONATHAN ON SOCIAL Unscheduled CEO Podcast: https://www.unscheduledceo.com/  X/Twitter: https://twitter.com/Jicecream  LinkedIn: https://www.linkedin.com/in/jonathan-courtney-4510644b/