The Startup Ideas Podcast

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