The Startup Ideas Podcast

The Startup Ideas Podcast

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Get your creative juices flowing with The Startup Ideas Podcast. Published twice a week, we bring you free startup ideas to inspire your next venture. Hosted by Greg Isenberg, CEO of Late Checkout and former advisor to Reddit and TikTok. Subscribe so you don't miss out. For more startup ideas, we created a database of 30+ startup ideas you can take at https://gregisenberg.com/30startupideas

Episode List

I let OpenClaw run my organic marketing (while I sleep)

Mar 9th, 2026 6:11 PM

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-2026Links Mentioned:Larry Brain: https://startup-ideas-pod.link/Larry-brainQMD Skill: https://startup-ideas-pod.link/qmd-skillTimestamps00:00 – Intro01:25 – Background on Marketing IOS app with OpenClaw06:43 – Larry’s first posts and iterating03:55 – Posting Strategy and First viral hit: 137K views12:01 – Communicating with Larry via WhatsApp12:53 – Mission control vs. single-agent workflow14:36 – The CTA problem: views without conversions17:07 – The Larry Loop explained: analytics → content → metrics → iterate18:15 – Boomers, engagement bait, and the algorithm boost20:33 – The importance of iteration23:36 – How Larry brainstorms and validates new hooks27:57 – The power of OpenClaw30:04 – The vision for Larry31:49 – Model choices: Claude vs. OpenAI and over-optimization34:38 – OpenClaw vs. cloud alternatives (Manus, Cowork)37:39 – Getting started: Larry Brain onboarding and 80+ skills40:13 – Ernesto Lopez: $70K MRR using the Larry Loop41:27 – Doing all of this with a full-time job42:28 – QMD Skill for cutting token usage and closing thoughtsKey PointsAn 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.comLCA 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 SOCIALX/Twitter: https://twitter.com/gregisenbergInstagram: https://instagram.com/gregisenberg/LinkedIn: https://www.linkedin.com/in/gisenberg/FIND OLIVER ON SOCIALX: https://x.com/oliverhenryLarry Brain: https://www.larrybrain.com

Biggest wealth creation opportunity is SaaS

Mar 4th, 2026 11:45 PM

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-2026Timestamps00:00 – Intro01:18 – Step 1: Start with a sub-niche inside a big market02:21 – Step 2-5: Map Workflow end to end06:37 – Step 6-7: Create scroll-stopping content10:15 – Steps 8–9: Double down on organic and run paid ads on winners11:11 – Step 10: Capture emails from day one11:47 – Steps 11–13: Manually perform the workflow and document every step13:40 – Steps 14–16: Turn mechanical tasks into agent workflows and connect to real tools14:47 – Step 17: Add orchestration, retries, and verifications16:32 – Steps 18–19: Store user preferences and launch with high-touch onboarding18:20 – Steps 20–21: Publish measurable proof and move to per-task pricing21:21 – Steps 22–23: Outcome pricing and compounding value22:07 – Steps 24–27: Expand workflows, build switching costs, create case studies23:25 – Steps 28–30: Hire from the niche, reinvest profits, become the default layer24:08 – Closing thoughtsKey PointsStart 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.comLCA 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 SOCIALX/Twitter: https://twitter.com/gregisenbergInstagram: https://instagram.com/gregisenberg/LinkedIn: https://www.linkedin.com/in/gisenberg/

Claude Code marketing masterclass [from idea to making $$]

Mar 2nd, 2026 6:10 PM

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 CodexMarketing & 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 4CRM & Communication: Salesforce (mentioned as comparison), Intercom, SendGrid API, Slack, Cal.com APIProductivity & Design: Notion, Super Whisper (voice transcription), Claude Code front-end design skill, HTML to Canvas (for converting React components to PNGs)Timestamps00:00 – Intro02:02 – What Is GTM Engineering?05:12 – Setting Up Your Agent Workspace & Environment File07:54 – Live Demo: LinkedIn Auto-Responder09:56 – Live Demo: Bulk Facebook Ad Generator12:31 – Live Demo: Cold Email Campaign Automation (Raphonic + Instantly)14:47 – Live Demo: Creating Notion Documents via Claude Code16:46 – Live Demo: Bulk Ad Creative Generator26:05 – Live Demo: LinkedIn Engagement Scraper to Cold Email Pipeline28:16 – Context Switching Across Tasks29:19 – Live Demo: Bulk Ad Generator31:41 – Live Demo: Data Analysis: Turning Off Low-Performing Ads35:28 – Summary of GTM Engineering Workflow37:48 – Deploying Agents and On-the-Fly Databases with Railway for Data Analysis41:28 – The Dream of Autonomous Marketing48:50 – Building API-First Products and Agent-Native InfrastructureKey PointsGTM 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.comLCA 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 SOCIALX/Twitter: https://twitter.com/gregisenbergInstagram: 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/codyschneiderxxYoutube: https://www.youtube.com/@codyschneiderx

What is Perplexity Computer?

Feb 27th, 2026 12:00 AM

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.Timestamps00:00 – Intro 00:35 – What We're Testing Today02:35 – Use Case 1: Warm Outbound at Scale15:31 – Use Case 2: Automated Competitive Intel25:11 – Use Case 3: Investor Pipeline Research (50 VCs)26:58 – Use Case 4: Turn a Podcast Into a Content Machine31:39 – Use Case 5: Live Market Diligence (Shopify Investment Memo)34:17 – Bonus: Additional Use Cases Worth Trying36:06 – Closing Thoughts and TakeawaysKey PointsPerplexity 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.comLCA 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 SOCIALX/Twitter: https://twitter.com/gregisenbergInstagram: https://instagram.com/gregisenberg/LinkedIn: https://www.linkedin.com/in/gisenberg/

How I Use Obsidian + Claude Code to Run My Life

Feb 23rd, 2026 8:00 PM

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 Timestamps00:00 – Intro02:10 – What Is Claude Code?06:45 – What Is Obsidian?10:28 – Obsidian CLI: Giving Claude Code Access to Your Vault14:53 – Thinking Tools: Ghost, Challenge, Emerge, Drift, Ideas, Trace22:51 – The Role of Reflection in Building a Powerful Vault25:15 – How This Relates to OpenClaw (Autonomous Agents)29:13 – Live Demo: /Connect — Bridging Two Domains31:25 – Meeting Notes & External Info33:23 – Why Vin Keeps a Strict Separation: Human-Written vs. Agent-Written35:42 – How Claude Code uses Obsidian41:46 – Live Demo: /Ideas — Generating Actionable Ideas from Your Vault47:10 – The /Graduate Command50:29 – Why Obsidian Is the Missing Link for AI Companies54:53 – The Alpha: Why 99.99% of People Won't Do This57:38 – Closing Thoughts & Where to Follow VinKey PointsClaude 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 foundationalThe #1 tool to find startup ideas/trends - https://www.ideabrowser.comLCA 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 SOCIALX/Twitter: https://twitter.com/gregisenbergInstagram: https://instagram.com/gregisenberg/LinkedIn: https://www.linkedin.com/in/gisenberg/FIND VIN ON SOCIALX: https://x.com/internetvinYoutube: https://www.youtube.com/@otherstuffpodPersonal Website: https://internetvin.com/Index

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