The Startup Ideas Podcast

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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