How I AI

• How to create your own AI performance coach: Optimizing your unique nutrition, recovery, and injury management needs | Lucas Werthein (Cactus)

  Lucas Werthein, the COO and co-founder of Cactus, shares how he built a personalized AI wellness coach using ChatGPT to optimize his athletic performance while managing past injuries. After multiple surgeries on his knees, shoulder, and foot, Lucas created a system that synthesizes data from medical imaging, blood tests, wearable devices, and nutrition plans to provide personalized recommendations. His AI coach helps him balance competitive tennis, weightlifting, and running a company while maintaining his goal of “feeling 25 in a 40-year-old body.” Lucas demonstrates how this approach transforms siloed health information into actionable insights that protect joints, optimize recovery, and extend peak performance.What you’ll learn:How to configure a ChatGPT with multiple data types, including MRIs, x-rays, blood tests, and wearable metrics, to create a comprehensive health profileA framework for setting clear performance boundaries that prioritize joint protection, energy optimization, and injury preventionTechniques for using AI to balance nutrition around special events like social dinners while maintaining performance goalsHow to use images and videos to get AI feedback on physical symptoms and injury recovery timelinesA method for validating and contextualizing medical advice by having AI synthesize information from multiple health-care providersWhy creating clear rules and anti-prompts helps AI deliver practical, evidence-based recommendations instead of trendy supplements or extreme protocols—Copy Lucas’s Health Coach Prompt: https://www.lennysnewsletter.com/p/how-to-create-your-own-ai-performance-coach—Brought to you by:WorkOS—Make your app enterprise-ready todayGoogle Gemini—Your everyday AI assistant—Where to find Lucas Werthein:Website: https://cactus.is/—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to Lucas’s athletic background and injury history(04:55) The challenge of synthesizing siloed health data(06:11) Building a GPT to optimize performance and recovery(09:57) Demonstrating the data types integrated into the AI coach(13:54) Configuring the GPT with clear performance goals and boundaries(16:31) Setting realistic expectations for the AI coach(17:50) Creating nutrition, training, and recovery frameworks(21:47) Establishing hard boundaries and anti-prompts(24:25) Example: Managing nutrition around special events(27:30) Accessibility and affordability of on-demand coaching(28:24) Practical examples and real-life scenarios(29:31) Using AI for injury management and recovery planning(34:19) Validating expert opinions and translating medical advice(37:25) Vision for the future of AI in personal health coaching(43:27) Other AI workflows: synthetic clients and AI co-founders(48:48) Final thoughts on AI reliability and evolution—Tool referenced:• ChatGPT: https://chat.openai.com/—Other references:• InBody scan: https://inbodyusa.com/• Whoop: https://www.whoop.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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• “Farm-to-table software”: How I built a Thanksgiving party hub using Lovable for managing invites, dishes, shared recipes, and photos

  In today’s pre-Thanksgiving episode, I walk you through how I vibe coded my very own “Thanksgiving party hub” using Lovable—and how I transformed it from AI-generated slop into something warm, personal, and genuinely useful. I show you exactly how I upleveled the typography, visuals, and structure using Google Fonts and Midjourney style references, and then I share one of my favorite real-life AI hacks: how to turn any messy online recipe into a clean, step-by-step, kid-friendly version that’s actually usable while you’re cooking. This is a cozy, practical walkthrough of my real design process—the little tricks I use to make AI-built apps feel handcrafted instead of generic.What you’ll learn:How to build a fully functional Thanksgiving party hub in Lovable—guests, dishes, recipes, and photosHow I uplevel AI-generated designs using Google Fonts and TailwindHow to use Midjourney style references to create custom images that match your aestheticHow to add custom features to vibe-coded apps, like dietary preferences and allergen tagsHow to iterate on layouts inside Lovable using screenshots and small, targeted promptsHow I use ChatGPT to restructure recipes so the measurements are embedded directly in each stepHow to make recipes kid-friendly and easier to follow using a simple formatting prompt—Brought to you by:WorkOS—Make your app enterprise-ready today—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to the Thanksgiving party hub concept(02:20) Starting a project in Lovable and initial design assessment(04:59) Upleveling typography with Google Font combinations(08:36) Creating custom header images with Midjourney(11:39) Adjusting aspect ratios for Midjourney images(14:22) Fixing design issues incrementally(18:52) Adding dietary-restriction functionality(23:36) AI recipe reformatting for easier cooking(26:02) Thoughts on ChatGPT 5.1(30:51) Final implementation and recipe sharing—Tools referenced:• Lovable: https://lovable.dev/• Midjourney: https://www.midjourney.com/• Google Fonts: https://fonts.google.com/• ChatGPT: https://chat.openai.com/• Canva Font Combinations: https://www.canva.com/font-combinations/—Other references:• Polenta and Sausage Stuffing Recipe: https://www.epicurious.com/recipes/food/views/polenta-and-sausage-stuffing-233030 • Runaway Pancakes (kid-friendly recipe site): https://runawaypancakes.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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• “Nobody wanted to do this work”: How Emmy Award–winning filmmakers use AI to automate the tedious parts of documentaries

  Tim McAleer is a producer at Ken Burns’s Florentine Films who is responsible for the technology and processes that power their documentary production. Rather than using AI to generate creative content, Tim has built custom AI-powered tools that automate the most tedious parts of documentary filmmaking: organizing and extracting metadata from tens of thousands of archival images, videos, and audio files. In this episode, Tim demonstrates how he’s transformed post-production workflows using AI to make vast archives of historical material actually usable and searchable.What you’ll learn:How Tim built an AI system that automatically extracts and embeds metadata into archival images and footageThe custom iOS app he created that transforms chaotic archival research into structured, searchable dataHow AI-powered OCR is making previously illegible historical documents accessibleWhy Tim uses different AI models for different tasks (Claude for coding, OpenAI for images, Whisper for audio)How vector embeddings enable semantic search across massive documentary archivesA practical approach to building custom AI tools that solve specific workflow problemsWhy AI is most valuable for automating tedious tasks rather than replacing creative work—Brought to you by:Brex—The intelligent finance platform built for founders—Where to find Tim McAleer:Website: https://timmcaleer.com/LinkedIn: https://www.linkedin.com/in/timmcaleer/—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to Tim McAleer(02:23) The scale of media management in documentary filmmaking(04:16) Building a database system for archival assets(06:02) Early experiments with AI image description(08:59) Adding metadata extraction to improve accuracy(12:54) Scaling from single scripts to a complete REST API(15:16) Processing video with frame sampling and audio transcription(19:10) Implementing vector embeddings for semantic search(21:22) How AI frees up researchers to focus on content discovery(24:21) Demo of “Flip Flop” iOS app for field research(29:33) How structured file naming improves workflow efficiency(32:20) “OCR Party” app for processing historical documents(34:56) The versatility of different app form factors for specific workflows(40:34) Learning approach and parallels with creative software(42:00) Perspectives on AI in the film industry(44:05) Prompting techniques and troubleshooting AI workflows—Tools referenced:• Claude: https://claude.ai/• ChatGPT: https://chat.openai.com/• OpenAI Vision API: https://platform.openai.com/docs/guides/vision• Whisper: https://github.com/openai/whisper• Cursor: https://cursor.sh/• Superwhisper: https://superwhisper.com/• CLIP: https://github.com/openai/CLIP• Gemini: https://deepmind.google/technologies/gemini/—Other references:• Florentine Films: https://www.florentinefilms.com/• Ken Burns: https://www.pbs.org/kenburns/• Muhammad Ali documentary: https://www.pbs.org/kenburns/muhammad-ali/• The American Revolution series: https://www.pbs.org/kenburns/the-american-revolution/• Archival Producers Alliance: https://www.archivalproducersalliance.com/genai-guidelines• Exif metadata standard: https://en.wikipedia.org/wiki/Exif• Library of Congress: https://www.loc.gov/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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• How this CEO turned 25,000 hours of sales calls into a self-learning go-to-market engine | Matt Britton (Suzy)

  Matt Britton is the founder and CEO of Suzy, a consumer insights platform that has raised over $100 million in venture capital and works with top brands like Coca-Cola, Google, Procter & Gamble, and Nike. Matt is also the bestselling author of YouthNation, a blueprint for understanding the seismic shifts shaping our future economy, and Generation AI, which explores how Gen Alpha and artificial intelligence will transform business, culture, and society. In this episode, Matt demonstrates how he built a comprehensive AI workflow using Zapier that transforms customer call transcripts into a wealth of actionable intelligence. Despite not being a coder, Matt created a system that automatically generates call summaries, sentiment analysis, coaching feedback, follow-up emails, SEO-optimized blog posts, and more—all from a single customer conversation.What you’ll learn:How to build a trigger-based workflow that automatically scrapes and processes customer call transcripts from platforms like GongA systematic approach to quantifying customer sentiment on a 1-10 scale that has proven highly predictive of churn and upsell opportunitiesHow to create an automated coaching system that provides personalized feedback to sales reps after every customer interactionA workflow for extracting keywords from customer conversations to inform Google ad campaigns without manual interventionTechniques for automatically generating privacy-compliant blog content from customer calls that drives organic traffic and paid search performanceWhy CEOs and executives need to build AI skills firsthand rather than delegating implementation to engineering teamsHow to use Google Sheets as structured databases for AI lookups and enrichment within automated workflows—Brought to you by:Brex—The intelligent finance platform built for foundersZapier—The most connected AI orchestration platform—Where to find Matt Britton:LinkedIn: linkedin.com/in/mattbbrittonInstagram: https://www.instagram.com/mattbrittonnyc/Company: https://www.suzy.com/—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to Matt Britton(02:36) Why Zapier became the backbone of Matt’s AI automations(04:17) Identifying your core business problem(09:02) How Matt built the initial trigger automation with Browse AI(13:42) The value of CEOs getting hands-on with building(14:00) Scraping and processing call transcripts(20:14) Using LLMs to generate call summaries and sentiment scores(23:25) Creating a Slack channel for real-time call insights(26:17) Extracting keywords for Google Ads campaigns(28:35) Building an AI coach for sales and customer success teams(29:48) Creating a follow-up email writer for post-call communication(35:25) Generating redacted blog content from customer conversations(37:51) How this approach changes team building and hiring priorities(40:19) Matt’s prompting techniques and final thoughts—Tools referenced:• Zapier: https://zapier.com/• Gong: https://www.gong.io/• Browse AI: https://www.browse.ai/• ChatGPT: https://chat.openai.com/—Other references:• Qualtrics: https://www.qualtrics.com/• SurveyMonkey: https://www.surveymonkey.com/• Slack: https://slack.com/• Google Sheets: https://www.google.com/sheets/about/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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• The complete beginner’s guide to coding with AI: from PRD to generating your very first lines of code

  This episode is for complete beginners. I walk you through how to build your very first coding project using AI tools—even if you’ve never written a line of code. Together, we’ll create a personal project hub that automatically generates documentation and lets you build interactive prototypes. I’ll show you the process step by step—from setting up a repository, to creating AI agents that help with specific tasks, to deploying a functional web app locally.What you’ll learn:How to set up a simple Next.js application from scratch using Cursor’s AI agent capabilitiesMy workflow for creating AI agents that generate consistent documentation (like PRDs in Markdown format)How to build and display clickable prototypes without worrying about complex backend functionalityThe basics of using GitHub to track changes and manage your code repository as a non-technical personWhy starting with a personal project hub is the best way to ease into AI-assisted codingMy favorite practical tips for iterating on designs and functionality using AI tools—without needing deep technical expertise—Brought to you by:ChatPRD—An AI copilot for PMs and their teams—In this episode, we cover:(00:00) Introduction(05:11) Starting with a requirements document in ChatPRD(08:22) Attempting to use v0 for initial prototyping(15:02) Pivoting to Cursor for initial prototyping(20:20) Running the app locally and reviewing the initial version(24:07) Setting up GitHub for version control(27:09) Creating an AI agent for writing PRDs(31:04) Using the agent to create a sample PRD(35:00) Building a prototype based on the PRD(37:00) Testing and improving the prototype(40:00) Adding documentation and improving the design(43:20) Recap of the complete workflow—Tools referenced:• Cursor: https://cursor.com/• ChatPRD: https://www.chatprd.ai/• v0: https://v0.dev/• GitHub Desktop: https://desktop.github.com/• Next.js: https://nextjs.org/• Tailwind CSS: https://tailwindcss.com/—Other references:• Lovable: https://lovable.ai/• Bolt: https://bolt.new/• Claude Code: https://www.claude.com/product/claude-code• Markdown: https://www.markdownguide.org/• GitHub: https://github.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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