The Startup Ideas Podcast

Episodes

• 
  Become a $1M/yr FDE (Full Course) 01.10.2026 53m

  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
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  OpenAI DevDay: Dots, Agents & $100B Opportunities 29.09.2026 18m

  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/
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  $5T opportunity: AI Roll Ups 28.09.2026 29m

  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/
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  Muse AI Connectors: The Next App Store Moment? 24.09.2026 26m

  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/
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  The Right Way To Write With AI 21.09.2026 1h 9m

  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
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  Jev is HERE. How to use it 18.09.2026 28m

  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
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  Instinct AI: The AI Assistant for normal people 15.09.2026 27m

  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/
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  Building a Software Factory that actually works (Full Course) 14.09.2026 31m

  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
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  You're using GPT-6 Astra WRONG 10.09.2026 22m

  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
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  Local AI Clearly Explained 08.09.2026 38m

  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/
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  These 5 Github Repos are a goldmine 02.09.2026 24m

  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/
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  Making $$$ as a Marketing Engineer 31.08.2026 35m

  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/
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  WebMCP clearly explained (and how to make $$) 26.08.2026 28m

  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
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  Screensharing top takes in AI/startups 25.08.2026 41m

  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/
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  Grok Bot: make a 1 person company with agents 21.08.2026 44m

  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
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  You need to be skillsmaxxing (10x your Claude/Codex) 19.08.2026 32m

  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/
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  How to use Claude Code better than 99% of People 17.08.2026 48m

  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/
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  How to Build an AI-Native Company in 2026 12.08.2026 48m

  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/
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  Making $$$ selling to AI Agents 10.08.2026 34m

  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/
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  These AI Marketing Agents Get You Customers 05.08.2026 43m

  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