Building AI Agents (Clearly Explained)

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

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

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

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

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

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

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

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

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

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