How I AI

Epizodes

• Building an iPhone app with zero technical skills | Bryce Rattner Keithley 01.06.2026 46min

  Bryce Rattner Keithley has spent her career in talent and recruiting, working with technical leaders but never writing a line of code herself. Yet she managed to build Daily Hundred—a fitness app featuring custom AI-generated videos of anthropomorphic animals demonstrating exercises—and ship it to the App Store before her software engineer friends. Using Replit, Claude, Gemini, and a relentless beginner’s mindset, Bryce proves that in the AI era, execution is no longer the constraint on good ideas.What you’ll learn:How to build and ship an iPhone app using Replit without any coding knowledgeThe step-by-step process for creating custom AI-generated workout videos by combining Gemini images with real exercise footageHow to use Claude as your technical architect and Claude Code as your software engineerHow to navigate App Store submission requirements (including fixing rejection feedback)Why being hyper-literal in your prompts unlocks better AI resultsWhy a beginner’s mind is actually an advantage when building with AI tools—Brought to you by:WorkOS—Make your app enterprise-ready todayMetaview—The agentic recruiting platform for winning teams—In this episode, we cover:(00:00) Introduction to Bryce and Daily Hundred(04:48) Building with Replit(06:16) The beginner’s mindset advantage(11:17) Creating anthropomorphic animals(22:55) Moving from static image to video(27:15) The floating genie and other anthropomorphic animal generations(30:46) Shifting from web app to App Store submission(36:24) User feedback(37:41) Lightning round and final thoughts—Tools referenced:• Replit: https://replit.com/• Lovable: https://lovable.dev/• Claude: https://claude.ai/• Claude Code: https://claude.ai/code• Gemini: https://gemini.google.com/• Higgsfield: https://higgsfield.ai/• Kling: https://kling.ai/• Railway: https://railway.app/• TestFlight: https://developer.apple.com/testflight/—Other references:• How a 91-year-old vibe coded a complex event management system using Claude and Replit | John Blackman: https://www.lennysnewsletter.com/p/how-a-91-year-old-vibe-coded-a-complex• What Got You Here Won’t Get You There: https://www.amazon.com/What-Got-Here-Wont-There/dp/1401301304• How Women Rise: https://www.amazon.com/How-Women-Rise-Holding-Careers/dp/0316440124• A Whole New Mind: https://www.amazon.com/Whole-New-Mind-Right-Brainers-Future/dp/1594481717• How to Win Friends and Influence People: https://www.amazon.com/How-Win-Friends-Influence-People/dp/0671027034—Where to find Bryce Rattner Keithley:LinkedIn: https://www.linkedin.com/in/brycerattner/GitHub: https://github.com/brk-bot/Daily Hundred on the App Store: https://apps.apple.com/us/app/daily100-fitness-challenge/id6762108062—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• Claude Opus 4.8 is here. Is it as good as they say? 28.05.2026 13min

  I got a few hours of early-access testing with Anthropic’s newly released model Opus 4.8. I walk through real coding, design, and strategy tasks across Claude Code and Claude Cowork, and give you my unfiltered view on what impressed me and what didn’t.—What you’ll learn:Where Opus 4.8 excels: greenfield prototypes, one-shot features, and fast executionWhere it struggles: the last 10%, edge cases in existing codebases, and hallucinationsHow Opus 4.8 compares to Opus 4.7 on business strategy workWhy I’m still reaching for Opus 4.7 on data-heavy strategy and roadmap workThe new features shipping alongside the model: dynamic workflows with parallel subagents and effort control in Claude.ai and CoworkThe prompting and harness strategy I’d use to get the most out of it—In this episode, we cover:(00:00) Introduction to Opus 4.8 (00:44) Benchmark performance and pricing(01:53) First coding test: Building a prototyping tool(03:00) Where it failed: The last 10% problem(03:27) The hallucination problem(04:23) Testing Opus 4.8 on existing codebases(05:24) The ambition test: Building games for a 9-year-old(07:03) Business strategy test: 4.7 vs 4.8(08:23) The roadmap test(09:17) Final verdict—References:• System Card: Claude Opus 4.8: https://cdn.sanity.io/files/4zrzovbb/website/c886650a2e96fc0925c805a1a7ca77314ccbf4a6.pdf• Introducing Claude Opus 4.8 on X: https://x.com/claudeai/status/2060042702150930686?s=20—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• The Codex feature that works while you sleep 27.05.2026 30min

  In this 30-minute episode, I walk through my favorite feature in Codex: the /goal command. I show how Goals transform AI from a turn-based assistant that needs constant ‘what’s next?’ prompting into an autonomous agent that can work for hours on complex, multi-step tasks. I share three real examples: eliminating thousands of Sentry errors, cleaning 3,900 emails down to 68, and organizing hundreds of Linear tasks.What you’ll learn:What Goals are and how they differ from standard promptsHow I used /goal to eliminate hundreds of error logs in my codebase over a five-hour autonomous runThe non-technical use cases that make Goals incredibly powerful: cleaning up 3,900 emails in under four hours and organizing hundreds of project management tasks in LinearHow to write effective /goal prompts with measurable outcomes, verification methods, and constraintsWhen not to use Goals and what makes a strong versus weak GoalWhy Goals represent a fundamental shift in how we work with AI, from babysitting the model to managing it—Brought to you by:Mercury—Radically different banking loved by over 300K entrepreneurs—In this episode, we cover:(00:00) Introduction(01:50) What is /goal and when should you use it?(02:45) The difference between prompts and Goal-based loops(04:06) Claire’s first five-hour 45-minute autonomous coding task(05:05) How to manage a Goal lifecycle: view, pause, resume, and clear(06:06) How to write strong goals: outcomes vs. outputs(07:34) The six components of effective Goals(08:57) Example: Reducing P95 checkout latency with /goal(09:36) Demo: Using /goal to eliminate Sentry errors in ChatPRD(13:18) Demo: Burning down Vercel API errors(17:28) Non-technical use case: Cleaning 3,900 emails with /goal(21:24) Demo: Using /goal to clean up Linear project tasks(24:41) When not to use /goal(26:10) Why /goal changes everything—Tools referenced:• Codex: https://openai.com/codex/• Sentry: https://sentry.io/• Vercel: https://vercel.com/• Linear: https://linear.app/—Other reference:• OpenAI blog post “Using Goals in Codex”: https://developers.openai.com/cookbook/examples/codex/using_goals_in_codex—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• How the engineer behind Claude Cowork actually uses Claude | Felix Rieseberg (Anthropic) 25.05.2026 59min

  Felix Rieseberg is the engineering lead for Claude Cowork and Claude Code Desktop at Anthropic. He previously spent five years at Slack building developer tools. In this episode, Felix demonstrates how he uses Claude to solve real-life problems: analyzing floor plans to build interactive 3D house walkthroughs, automatically tracking promises he makes on Twitter, and building a $20 hardware device that physically approves Claude actions with a button press.What you’ll learn:How to use Claude Cowork to turn a 2D floor plan into an interactive 3D walkthrough where you can move furniture aroundThe “go one abstraction layer up” philosophy: why you should never manually enter data Claude can find itselfHow to use your email as an inventory database for furniture, clothing, and personal purchasesWhen to use Opus vs. Sonnet 4.6 (hint: it’s about how well you can scope the problem, not technical complexity)How live artifacts work and why they’re powerful for dashboards that refresh with real-time data from your connectorsThe product philosophy behind making latency delightfulHow to build your own $20 hardware device using Claude Code (no hardware experience required)Why Felix never reads the code Claude writes and judges it purely on output—Brought to you by:Magic Patterns—Prototypes that look like your productGuru—The AI layer of truth—In this episode, we cover:(00:00) Introduction to Felix Rieseberg(02:40) Felix’s role at Anthropic(03:25) The multiple tabs in Claude and why they exist(05:55) Using Claude Cowork to design a new house using floor plans(09:52) When to use Opus versus Sonnet 4.6(12:37) Building an interactive 3D furniture planner(14:30) Using your email as a source of truth for personal inventory(15:58) The anti-to-do list: going one abstraction layer up(23:14) Introduction to live artifacts(26:02) Building a personal dashboard with live data(28:37) Being polite to Claude (and why it matters for your humanity)(30:28) Claude interaction tips(32:33) Looking at the daily dashboard(33:55) How live artifacts work with connectors(35:02) Redesigning the dashboard(37:55) The biggest gap: people don’t know what problems AI can solve(41:52) The reverse interview(42:30) Making latency delightful through asynchronous design(44:05) The redesigned dashboard(45:28) AI should free up your creative energy(46:44) Building a $20 hardware Claude buddy(52:33) Why kids are magical AI users(54:30) Recap and final thoughts—Tools referenced:• Claude Cowork: https://www.anthropic.com/product/claude-cowork• Claude Code: https://claude.ai/code• Claude for Chrome: https://code.claude.com/docs/en/chrome• Claude Desktop: https://claude.ai/download• Live Artifacts: https://support.claude.com/en/articles/14729249-use-live-artifacts-in-claude-cowork• Connectors (Spotify, Gmail, Calendar, Notion): https://claude.ai/settings/connectors• Slack: https://slack.com/—Where to find Felix Rieseberg:Website: https://felixrieseberg.com/LinkedIn: https://www.linkedin.com/in/felixrieseberg/X: https://x.com/felixriesebergGitHub: https://github.com/felixrieseberg—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• What launched at Google I/O 2026 (30-minute day 1 recap) 20.05.2026 33min

  Today is day one of Google I/O 2026, and I walk through every major announcement live—from the new Gemini 3.5 model family to Anti-Gravity 2.0, Google AI Studio, Gemini’s consumer redesign, the Omni video model, Flow, Stitch, and Pomelli. I test them in real time and tell you exactly which ones delivered.What you’ll learn:How Gemini 3.5 Flash benchmarks against Claude and GPT models on speed and agentic coding tasksHow Anti-Gravity 2.0’s new features (projects, scheduled tasks, subagents, slash commands) compare to Codex and Claude CodeWhy the /grill-me slash command could be a more aggressive alternative to Claude Code’s clarification flow—and how to use itHow Google AI Studio’s new Workspace integration is designed to own the internal productivity app use caseHow Google’s new creative tools work in practice: Omni (video generation), Flow (cinematic video editing and character consistency), Stitch (streaming UI design with inline edits), and Pomelli (brand identity and asset generation)Why Google’s launch-to-availability gap is still a problem—and what to do when a featured product doesn’t actually work yet—Brought to you by:Magic Patterns—Prototypes that look like your productThoughtspot—Build AI-powered analytics into your product—In this episode, we cover:(00:00) Google I/O 2026 day 1 overview(01:47) Gemini 3.5 flash(04:19) Antigravity updates(06:32) CLI test and agent features(07:59) Core agent features released today—May 19th, 2026(09:43) New slash commands(11:20) Antigravity test results and takeaways(12:25) AI Studio updates(13:52) Access issues(15:20) Gemini redesign(17:24) Gemini image gen test(19:16) Omni (video generation)(22:56) Flow (cinematic editing)(24:31) Avatar creation test(26:45) Pomelli and Stitch(31:13) Recap and final thoughts—Tools referenced:• Gemini 3.5 Flash: https://deepmind.google/technologies/gemini/• Antigravity: https://antigravity.google/• Google AI Studio: https://aistudio.google.com/• Google Gemini: https://gemini.google.com/• Omni (video generation): https://gemini.google/overview/video-generation/• Google Flow: https://flow.google/• Stitch: https://stitch.withgoogle.com/• Pomelli (Google brand tool): https://labs.google.com/pomelli/about/—Other references:• Google I/O 2026 announcements: https://blog.google/innovation-and-ai/sundar-pichai-io-2026/—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• HTML is the new Markdown: How Anthropic engineers are building with Claude Code | Thariq Shihipar 18.05.2026 35min

  Thariq Shihipar is an engineer at Anthropic working on the Claude Code team. He’s spent the past several months experimenting with HTML as a replacement for Markdown in planning and implementation workflows, discovering that richer visual formats lead to better human engagement—and, ultimately, better products. In this episode, filmed at Anthropic’s Code with Claude event in San Francisco, Thariq demonstrates how to use HTML artifacts to create interactive plans, build throwaway UIs for specific problems, and maintain living design systems that travel with your codebase.What you’ll learn:Why HTML has replaced Markdown as the ideal format for AI agent communication and planningHow to brainstorm in HTML to get visual mockups and interactive demos instead of text listsThe technique for building throwaway micro-UIs to edit specific parts of your planHow to create a living design system in HTML that lives in your repo and travels with every projectWhy “complexity has to earn its keep” and how HTML helps you stay in the loop without over-constraining ClaudeThe prompting technique that gives Claude flexibility while ensuring that you get what you needWhy 99% of your AI-generated tokens should go to planning, interfaces, and communication—not production code—Brought to you by:Celigo—Intelligent automation built for AIPersona—Trusted identity verification for any use case—In this episode, we cover:(00:00) Introduction(02:39) HTML as the new Markdown(04:30) The compute allocator mindset(05:51) How HTML makes specs more engaging(06:48) Demo: Brainstorming in HTML with Claude Code(09:24) From brainstorm to full implementation plan(11:20) Prompting philosophy: Trust Claude but give it constraints(13:50) The future of PRDs and tech specs(18:16) Making HTML specs editable(20:23) The abundance mindset(24:17) Just-in-time documentation and throwaway software(25:39) Using plans as artifacts for implementation(26:39) Demo: Living design systems in HTML(30:16) Adding comments and annotations to HTML plans(31:42) Recap: The HTML workflow(32:21) Lightning round and final thoughts—Tools referenced:• Claude Code: https://claude.ai/code• Claude Design: https://claude.ai/design• AWS: https://aws.amazon.com/• Figma: https://www.figma.com/• GitHub: https://github.com/—Other references:• Anthropic Code with Claude event: https://claude.com/code-with-claude• SpaceX partnership announcement: https://www.anthropic.com/news/higher-limits-spacex• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox—Where to find Thariq Shihipar:Website: https://www.thariq.io/LinkedIn: https://www.linkedin.com/in/thariqshihipar/X: https://x.com/trq212GitHub: https://github.com/ThariqS—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• Spec-driven development: The AI engineering workflow at Notion | Ryan Nystrom 11.05.2026 47min

  Ryan Nystrom is a software engineer at Notion. He joined in December 2024 after Notion acquired Campsite, the team communication platform he co-founded with Brian Lovin. At Notion, he’s been a core builder of Notion AI and the Custom Agents feature launched in February 2026. He manages a team of six to seven engineers while still writing code himself, currently running Project Afterburner, a push to cut Notion’s CI time to a quarter of its current duration.What you’ll learn:How to build a Notion AI custom agent that auto-generates your daily standup pre-read by pulling from Slack, GitHub, Honeycomb metrics, and yesterday’s meeting transcriptHow to configure subagents and MCP integrations within Notion AIHow Notion’s internal “Boxy” system lets engineers @mention Codex from within Notion comments and get a full pull request with screenshots in 20 minutesThe spec-first development workflow: dictate an idea into Whisper, have Codex format it as a proper spec, commit it to the repo, and let the agent implement and verify it autonomouslyWhy fast CI is absolutely critical in the age of AI coding agentsHow to prompt AI coding agents to defend their reasoning under pushbackWhy engineering managers and even senior executives should keep writing code—Brought to you by:WorkOS—Make your app enterprise-ready todayOrkes—The enterprise platform for reliable applications and agentic workflows—In this episode, we cover:(00:00) Introduction to Ryan Nystrom(02:48) How AI has upended 12+ years of the same working routine(04:30) Project Afterburner: Notion’s push to cut CI time to a quarter(09:00) Why high-frequency, high-quality meetings beat lower-frequency standups(11:10) How automated context surfaces every engineer’s work equally(12:15) Why cutting meeting prep is a burnout protection mechanism(14:26) The case for engineering managers writing code(16:13) Inside “Boxy”: Notion’s internal VM-based background agent system(20:30) Old World vs. New World code review(24:51) Prompting Codex from Notion comments(29:20) The emotions around code review(31:01) Quick recap(32:00) Spec-first development: writing and checking agent specs into the repo(35:10) The spec as changelog: version control for how a feature actually works(37:53) How engineers’ roles are evolving(39:00) Lightning round(45:21) Where to find Ryan—Tools referenced:• Notion AI: https://www.notion.com/product/ai• Notion Custom Agents: https://www.notion.com/blog/introducing-custom-agents• Codex (OpenAI): https://openai.com/codex• Claude Code (Anthropic): https://claude.ai/code• Honeycomb (observability + MCP): https://www.honeycomb.io• Whisper (OpenAI voice transcription): https://openai.com/research/whisper• Slack: https://slack.com• GitHub: https://github.com—Other references:• How Stripe built “minions”—AI coding agents that ship 1,300 PRs weekly from Slack reactions | Steve Kaliski (Stripe): https://www.chatprd.ai/how-i-ai/stripes-ai-minions-ship-1300-prs-weekly-from-a-slack-emoji• Notion 3.3 Custom Agents launch (February 24, 2026): https://www.notion.com/releases/2026-02-24—Where to find Ryan Nystrom:X: https://x.com/ryannystromLinkedIn: https://www.linkedin.com/in/ryannystrom/GitHub: https://github.com/rnystrom—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• Code with Claude: The 5 biggest updates explained 07.05.2026 11min

  Claire breaks down the biggest announcements from Anthropic’s “Code with Claude” event and what they actually mean for builders shipping AI products today. From scheduled AI routines to outcome-based agents, multi-agent orchestration, and new memory systems, Claire walks through the features she’s most excited to use immediately—and how they could reshape the future of agentic software.What you’ll learn:How Claude Code routines let you automate recurring workflows on schedules or webhooksWhat “Outcomes” are and how rubric-based agent grading worksHow multi-agent orchestration enables specialized AI teams with different roles and toolsWhy Anthropic’s new “Dreams” memory system matters for long-term agent behaviorWhy increased Claude Code usage limits are a bigger deal than they soundHow Claire thinks about building practical agentic products today—Resources:• Code with Claude: https://claude.com/code-with-claude• Claude Code Routines Docs: https://code.claude.com/docs/en/routines• Define Outcomes Docs: https://platform.claude.com/docs/en/managed-agents/define-outcomes• Dreams Docs: https://platform.claude.com/docs/en/managed-agents/dreams• Multi-Agent Docs: https://platform.claude.com/docs/en/managed-agents/multi-agent• Managed Agent Webhooks Docs: https://platform.claude.com/docs/en/managed-agents/webhooks#supported-event-types• Codex (OpenAI): https://openai.com/codex• GitHub: https://github.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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird) 06.05.2026 42min

  John Kim is the co-founder and CEO of Delight.ai, a customer experience platform that’s transforming how companies deploy AI. But what makes John’s story fascinating isn’t just his product; it’s how he’s turned his entire company into an AI-native organization. His marketing team built a fully functional e-commerce swag store with Stripe integration in days. His sales team built their own CRM tools. His recruiting team automated their entire workflow. And it’s all tracked, measured, and celebrated through an internal platform called Automators.What you’ll learn:How Sendbird’s marketing team built a fully functional swag store with Stripe integration in a day (with no engineering support)How the Automators platform works—an internal marketplace where anyone can request AI tools and engineers (or AI agents) can build themHow to create secure, compliant templates so non-technical teams can ship to production safelyHow Sendbird built a token usage dashboard with five tiers (beginner through AI God) and why tracking the smoothness of the curve matters more than the totalWhy visible leadership usage is the most powerful adoption signalWhy Sendbird rewrote job descriptions to prioritize curiosity, agency, and energy over years of experienceHow John uses AI for his own learning—Brought to you by:WorkOS—Make your app enterprise-ready todayThoughtSpot—Build AI-powered analytics into your product—In this episode, we cover:(00:00) Introduction to John Kim(02:45) The Delight.ai swag store built by marketing in two days(05:51) The before times: when fun had to earn its place on the roadmap(07:55) Demo: The Automators platform and quest system(13:47) The AI Engineer for Internal Operations role(16:06) Demo: The company-wide skills marketplace(17:19) Treating AI adoption as a product(18:43) Real wins: team-level and campaign examples(21:51) Why SaaS isn’t dead—it’s being rebuilt internally(23:46) Demo: The token tracking dashboard(26:32) Measuring without fear: setting expectations, not punishments(28:54) Quick recap(30:51) Personal AI use cases: endless knowledge at your fingertips(36:15) Lightning round and final thoughts—Tools referenced:• Claude Code: https://claude.ai/code• Codex (OpenAI): https://openai.com/codex• Obsidian: https://obsidian.md• GitHub: https://github.com• Stripe: https://stripe.com—Other references:• Jason Levin (CEO of Memelord) on How I AI: https://www.lennysnewsletter.com/p/from-a-690-newsletter-to-3m-api-how• Konami Code: https://en.wikipedia.org/wiki/Konami_Code• Andrew Huberman’s podcast: https://hubermanlab.com/• Y Combinator: https://www.ycombinator.com/—Where to find John Kim:X: https://x.com/doshkimInstagram: https://instagram.com/doshLinkedIn: https://www.linkedin.com/in/doshkim/Company: https://delight.aiDelight.ai Spark Conference (May 7, SF): https://delight.ai/spark—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• The internal AI tool that’s transforming how Stripe designs products | Owen Williams 04.05.2026 54min

  Owen Williams is a design manager at Stripe who built Protodash, an internal AI-powered prototyping platform that lets designers and PMs create high-quality Stripe dashboard prototypes without writing code. What started as a bundle of Cursor rules and React components evolved into a full web-based prototyping studio that runs in dev boxes, complete with design review modes, variant testing, and AI-powered iteration. Surprisingly, PMs now use Protodash just as much as designers, fundamentally changing how Stripe approaches prototyping, design reviews, and engineering handoffs.What you’ll learn:How Stripe built an internal AI prototyping tool using Cursor rules, MCPs, and their design systemWhy “blurple slop” happens when designers use generic AI tools—and how to fix itThe architecture behind Protodash: React router, design system components, and MCP integrationsHow Stripe prototypes in dev boxes so designers never have to worry about local setupWhy “demos, not memos” transformed Stripe’s design review cultureHow Stripe built design review modes, variant testing, and AI annotation directly into your prototyping toolWhy internal tools don’t need to be production-grade to be transformative—Brought to you by:Celigo—Intelligent automation built for AICursor—The best way to code with AI—In this episode, we cover:(00:00) Welcome and intro to Owen Williams(02:19) The “blurple slop” problem with AI design tools(03:50) Protodash: an internal vibe-coding tool for Stripe prototypes(05:26) Why an engineering background helped Owen lower the bar for designers(07:55) The Cursor rules that taught the Stripe design system(09:04) Running prototypes on dev boxes vs. locally(10:30) “Demos, not memos” and rewiring design reviews at Stripe(14:50) Building Protodash Studio: a browser-based wrapper for prototyping(19:04) Live demo: variants, line charts, and remixing prototypes in browser(21:02) Self-testing prototypes that take screenshots and check their work(23:20) Multiple variant features(26:08) The annotate-for-AI button for in-canvas feedback(27:21) Design review mode: comments, summaries, and AI follow-up(29:39) Why building internal tools beats buying off-the-shelf(32:50) PMs as the surprise power users of Protodash(35:20) Live demo: a Black Friday/Cyber Monday pet store dashboard(42:03) Lo-fi modes, monospace fonts, and “Comic Sans for WIP” at Shopify(44:45) Quick recap(45:35) The Radar prototype that changed engineering handoff(49:08) Lightning round and final thoughts—Blog & detailed workflow walkthroughs from this episode:Stripe’s Owen Williams on Killing ‘Blurple Slop’ with an Internal Prototyping Studio: http://chatprd.ai/how-i-ai/stripe-owen-williams-on-buildling-internal-prototyping-studio↳ How To Connect a Design System to an AI Code Editor for High Fidelity Prototypes: https://www.chatprd.ai/how-i-ai/workflows/how-to-connect-a-design-system-to-an-ai-code-editor-for-high-fidelity-prototypes↳ Streamline Design Reviews with an AI-Powered Prototyping Studio: https://www.chatprd.ai/how-i-ai/workflows/streamline-design-reviews-with-an-ai-powered-prototyping-studio↳ Build a Personal AI App to Track Purchases and User Manuals: https://www.chatprd.ai/how-i-ai/workflows/build-a-personal-ai-app-to-track-purchases-and-user-manuals—Tools referenced:• v0: https://v0.app/• Cursor: https://cursor.com/• Claude Code: https://www.claude.com/product/claude-code• Claude Design: https://www.anthropic.com/news/claude-design-anthropic-labs• Figma: https://www.figma.com/• Stripe Radar: https://stripe.com/radar• Balsamiq: https://balsamiq.com/—Where to find Owen Williams:X: https://x.com/owWebsite: https://owenwillia.ms/LinkedIn: https://www.linkedin.com/in/owenpwilliams—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/X: https://x.com/clairevo—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• From a $6.90 newsletter to $3M API: How a non-coder built Memelord | Jason Levin 27.04.2026 51min

  Jason Levin is the CEO and founder of Memelord, an AI-powered meme creation platform that helps brands and individuals create contextual, trending memes. He started Memelord as a $6.90-per-month newsletter sending subscribers to a Google Slides deck, grew it to $100K ARR on Bubble without hiring engineers, then raised $3M to build it into an API-first product.What you’ll learn:How Jason grew Memelord from a $6.90/month newsletter to $100K ARR without writing a single line of codeWhy “no UX is the best UX” and how agents are becoming Memelord’s primary usersThe mandatory vibe-coding rule for his marketing team and how it unlocks unprecedented creativityWhy free tools are the new PDF downloads and how they’ve generated hundreds of thousands of emailsJason’s hardware hacking projects, including a bedside keyboard that creates Linear tickets without waking his wifeWhy AI can be funny (but humans are still funnier) and which model is the funniestThe philosophy of building hyper-personalized software just for yourself—Brought to you by:WorkOS—Make your app enterprise-ready todayPersona—Trusted identity verification for any use case—In this episode, we cover:(00:00) Introduction to Jason Levin and Memelord(04:28) Demo: Agentic meme creation with OpenClaw(06:55) “No UX is the best UX”—building for an agent-first future(08:35) How Memelord started as a $6.90 newsletter with Google Slides(12:35) Building to $100K ARR on Bubble with 395 workflows(15:20) Demo: Free tools section that generates hundreds of thousands of emails(17:59) Why Cursor is perfect for non-technical founders(20:20) Let your marketers cook—or watch them leave(24:19) Commit graph that shows the vibe-coding inflection point(25:25) Tools: Claude, Gemini, Linear, PostHog(28:19) Build weird stuff in the real world(33:24) Creative AI use cases(39:56) Using OpenClaw for calendar analysis(43:37) Can AI be funny? Which model is funniest?(45:26) Memes are not slop(46:45) What Jason doesn’t use AI for(48:12) Final thoughts—Blog & detailed workflow walkthroughs from this episode:How I AI: Jason Levin’s Workflows for Agentic Memes, Vibe Coding, and Hardware Hacking: https://www.chatprd.ai/how-i-ai/jason-levins-workflows-for-agentic-memes-vibe-coding-and-hardware-hacking↳ Build a Custom Bedside Keyboard for Idea Capture with Raspberry Pi and ChatGPT: https://www.chatprd.ai/how-i-ai/workflows/build-a-custom-bedside-keyboard-for-idea-capture-with-raspberry-pi-and-chatgpt↳ Build Free Marketing Tools as Lead Magnets Using AI Code Assistants: https://www.chatprd.ai/how-i-ai/workflows/build-free-marketing-tools-as-lead-magnets-using-ai-code-assistants↳ Automate Meme Marketing with an AI Agent and OpenClaw: https://www.chatprd.ai/how-i-ai/workflows/automate-meme-marketing-with-an-ai-agent-and-openclaw—Tools referenced:• Memelord API: https://memelord.com/api• Cursor: https://cursor.com/• Bubble: https://bubble.io/• OpenClaw: https://openclaw.ai• Claude: https://claude.ai/• ChatGPT: https://chat.openai.com/• Gemini: https://gemini.google.com/• Grok: https://grok.x.ai/• Linear: https://linear.app/• PostHog: https://posthog.com/• Zapier: https://zapier.com/—Other references:• Diego Zaks—“The best UX is no UX”: https://x.com/diegozaks/status/1966526522136649980• Sam Lessin: https://wlessin.com/• “Stop giving me advice”: https://stopgivingmeadvice.com• Memelord free tools: https://memelord.com/tools—Where to find Jason Levin:Twitter: https://twitter.com/iamjasonlevinInstagram: https://instagram.com/iamjasonlevinLinkedIn: https://www.linkedin.com/in/iamjasonlevin/Memelord: https://memelord.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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• GPT 5.5 just did what no other model could 23.04.2026 23min

  In this mini episode, I break down OpenAI’s new GPT 5.5 and GPT 5.5 Pro after weeks of early testing. I walk through three real jobs I threw at the model:  building an app for me to teach my second grader more advanced subtraction concepts, tackling a tech debt problem in the ChatPRD codebase, and hacking into a proprietary Bluetooth pixel display that every other model had failed me on. My verdict: higher intelligence, better efficiency, and genuinely autonomous long-running loops that change what I think is worth tackling.What you’ll learn:How I think about GPT 5.5 Pro’s pricing vs engineering time, and when I believe the “intelligence tax” is worth payingWhy I treat GPT 5.5 as a developer model first, and why I couldn’t find a consumer use case that justified its intelligenceThe exact prompt pattern I use to unlock a long-running autonomous subagent loopHow I got a near-six-hour autonomous run to one-shot 98% of edge cases in a migration over millions of chat threads and drop my Sentry error rate to the floorWhy I’m now throwing GPT 5.5 at tech debt, flaky tests, and security backlogs firstHow I combined a Bluetooth packet sniffer and GPT 5.5 to reverse-engineer a proprietary pixel speaker after Claude Code and GPT 5.4 both gave upHow I use the /personality command inside Codex to swap the default “baked potato” tone for something I actually enjoy working with—In this episode, I cover:(00:00) Introduction to GPT 5.5 testing(00:40) What is GPT 5.5 and how much does it cost?(03:23) Testing GPT 5.5 in ChatGPT: the intelligence overhang problem(07:12) Moving to Codex: where GPT 5.5 really shines(16:01) Hacking a Chinese Bluetooth speaker(21:47) Final thoughts on GPT 5.5’s intelligence and efficiency—Tools referenced:• GPT 5.5 and GPT 5.5 Pro: https://openai.com/index/introducing-gpt-5-5/• Codex: https://openai.com/codex/• ChatGPT: https://chat.openai.com/• Claude Code: https://claude.ai/code• Sentry: https://sentry.io/• Divoom MiniToo: https://divoom.com/products/minitoo—Other references:• OpenAI Codex Security: https://openai.com/index/codex-security-now-in-research-preview/—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• What Claude Design is actually good for (and why Figma isn’t dead, yet) 22.04.2026 27min

  In this mini episode, I do a full walkthrough of the AI design tools that dropped in April 2026: Anthropic’s new Claude Design, OpenAI’s GPT Images 2.0, and Google Labs’ open-source DESIGN.md format. I import a full design system from Lenny’s Newsletter, build a landing page, turn my own article into a polished deck, generate a brand kit for ChatPRD, and run a personal color analysis from a photo.What you’ll learn:How Claude Design handles design system imports and whether it can actually replace FigmaThe three best use cases for Claude Design: marketing landing pages, slide decks, and creative redesignsWhy ChatGPT Images 2.0 is a breakthrough for brand kits and layout workGoogle’s new DESIGN.md standardThe practical limits of AI design tools (spoiler: you’ll hit credit limits fast)—Brought to you by:WorkOS—Make your app enterprise-ready todayRippling—Stop wasting time on admin tasks, build your startup faster—In this episode, we cover:(00:00) Welcome and what’s in the spring 2026 AI design drop(01:45) Claude Design overview(03:05) Importing Lenny’s Newsletter design system into Claude Design(04:06) How Claude Design structures a design system(05:42) Google Labs’ DESIGN.md standard(06:41) Building Lenny Doc, a PRD generator landing page using the Lenny design system(09:44) Why the three-variation output is Claude Design’s smartest UX choice(10:20) Hitting the Claude Design limit and paying $200 to keep going(11:05) Where Figma still wins(13:20) Reviewing Lenny Doc(16:19) Turning an Open Claude article into a branded slide deck(17:57) The ’90s GeoCities “Lenny’s Product Zone” redesign(19:44) Claude Design recap(20:15) ChatGPT Images 2.0 and what makes it the first “thinking” image model(21:25) Generating a multi-page brand kit for ChatPRD and iterating with reference images(23:43) Personal color analysis demo(26:02) Recap—Detailed workflow walkthroughs from this episode:• How I Put Claude Design and GPT Images 2.0 to the Test: Building Landing Pages, Slides, and Brand Kits: https://www.chatprd.ai/how-i-ai/claude-design-and-gpt-images-2-building-landing-pages-slides-and-brand-kits• How to Generate a Professional Brand Kit with GPT Images 2.0: https://www.chatprd.ai/how-i-ai/workflows/how-to-generate-a-professional-brand-kit-with-gpt-images-2-0• How to Convert an Article into a Polished Slide Deck with AI: https://www.chatprd.ai/how-i-ai/workflows/how-to-convert-an-article-into-a-polished-slide-deck-with-ai• How to Build a High-Fidelity Landing Page with Claude Design: https://www.chatprd.ai/how-i-ai/workflows/how-to-build-a-high-fidelity-landing-page-with-claude-design—Tools referenced:• Claude Design: https://claude.ai/design• ChatGPT Images 2.0: https://openai.com/index/introducing-chatgpt-images-2-0/• Midjourney: https://www.midjourney.com/—Other references:• Google’s DESIGN.md: https://stitch.withgoogle.com/docs/design-md/overview• Lenny’s Newsletter: https://www.lennysnewsletter.com/• Jamie Gannon “How I AI” episode on reference styles: https://www.lennysnewsletter.com/p/mastering-midjourney-how-to-create• Brand prompt inspiration: https://x.com/riomadeit/status/2046682442791071787• Figma team “How I AI” episode on design systems: https://www.lennysnewsletter.com/p/from-figma-to-claude-code-and-back—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• How Intercom 2x’d their engineering velocity in 9 months with Claude Code | Brian Scanlan 20.04.2026 1h 18min

  Brian Scanlan is a senior principal engineer at Intercom, where he’s led the company’s transformation to AI-first engineering. In just nine months, Intercom doubled their R&D throughput while maintaining code quality, with 100% of engineers—plus designers, PMs, and TPMs—now shipping code via Claude Code.What you’ll learn:How Intercom doubled their merged PRs per R&D employee in just nine months using Claude CodeThe telemetry infrastructure they built to measure AI adoption and quality across hundreds of engineersWhy they built a skills repository with hooks that enforce engineering standards automaticallyHow they’re preparing their product for an agent-first world with CLIs, MCPs, and ephemeral APIsThe permission and accountability framework that enabled rapid AI adoptionWhy backlog zero is now achievable and what that means for engineering culture—Brought to you by:Celigo—Intelligent automation built for AICursor—The best way to code with AI—In this episode, we cover:(00:00) Introduction to Brian Scanlan(02:40) Why Intercom went all-in on AI for both product and engineering(05:01) The breakthrough moment with Opus 4.6 and Christmas break 2025(07:02) Demo: Intercom’s merged PRs per R&D head(12:50) Agent-first work as a fundamental reimagining of technical workflows(14:27) The cost tradeoff: treating AI spend as an investment(16:47) Measuring quality(21:22) Demo: Shipping a redirect in the Rails monolith with Claude Code(24:03) Creating a custom PR skill(26:33) Building a software factory with predictable quality standards(30:15) Telemetry infrastructure: Honeycomb for skill usage tracking(32:10) Session data collection and personalized usage insights(36:08) Quick overview(39:20) Walking through Intercom’s skills repository(42:16) Deep dive: The flaky spec skill and how it reached 100x capability(46:44) The “and then” workflow for building comprehensive skills(52:31) The live website and overview of workflows(53:32) How internal AI experience informs customer product decisions(56:18) Making SaaS products agent-friendly with CLIs and helpful hints(01:03:49) Why conversion drop-off is invisible in agent-driven workflows(01:05:28) Lightning round and final thoughts—Detailed workflow walkthroughs from this episode:• How Intercom Doubled Engineering Output: Brian Scanlan's 4 AI Workflows for Claude Code: https://www.chatprd.ai/how-i-ai/how-intercom-doubled-engineering-output-brian-scanlan-ai-workflows-for-claude-code• Design an Agent-Friendly CLI to Automate SaaS Product Onboarding: https://www.chatprd.ai/how-i-ai/workflows/design-an-agent-friendly-cli-to-automate-saas-product-onboarding• Build a Self-Improving AI Agent to Automatically Fix Flaky Tests: https://www.chatprd.ai/how-i-ai/workflows/build-a-self-improving-ai-agent-to-automatically-fix-flaky-tests• Automate High-Quality Pull Request Descriptions with a Custom AI Skill: https://www.chatprd.ai/how-i-ai/workflows/automate-high-quality-pull-request-descriptions-with-a-custom-ai-skill—Tools referenced:• Claude Code: https://claude.ai/code• Cursor: https://cursor.com/• Honeycomb: https://www.honeycomb.io/• Snowflake: https://www.snowflake.com/• Fin AI: https://www.intercom.com/fin• Vercel: https://vercel.com/—Other references:• Intercom GitHub Repo: https://github.com/intercom• Google API Go Client Repo: https://github.com/googleapis/google-api-go-client—Where to find Brian Scanlan:X: https://x.com/brian_scanlanLinkedIn: https://www.linkedin.com/in/scanlanb/Company: https://www.intercom.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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• Claude Cowork 101: How to automate your workday without touching code | JJ Englert (Tenex) 13.04.2026 50min

  JJ Englert leads community enablement at Tenex. In this episode, JJ provides a complete zero-to-one tutorial on Claude Cowork, Anthropic’s desktop tool that sits between simple chat and full terminal-based coding.What you’ll learn:How to create your first Claude Cowork project by connecting a folder on your computer and building context over timeThe “brain” file strategy: how to create a preferences document that Claude reads every time to understand who you are and how you workWhy one-click connectors to Gmail, Slack, Notion, and Google Calendar unlock AI that actually does work instead of just suggesting itHow to analyze your sent emails to build a writing skill that perfectly matches your tone and styleThe sub-advisory-board technique: spinning up three AI agents with different personas to review your work from multiple perspectivesHow to set permissions for each connector so Claude only drafts (never sends) or always asks before taking actionThe scheduled-task workflow that creates a morning debrief by reading your email, Slack, and calendar every day at 7:30 a.m.Why projects with shared memory beat individual chat threads for consistent, high-quality AI outputs—Brought to you by:Tines—Start building intelligent workflows todayCursor—The best way to code with AI—In this episode, we cover:(00:00) Introduction to JJ Englert(02:48) What Cowork is and who it’s for(05:49) Getting started: Opening the Cowork tab in Claude Desktop(07:04) Understanding projects as folders on your computer(07:54) Creating your “brain” file, with working preferences and context(10:24) Demo: Building a daily operating system project from scratch(12:18) How to prompt Cowork when starting a new project(14:54) Understanding the project interface and shared memory(18:37) Setting up connectors to Gmail, Slack, Google Calendar, and other tools(21:00) Using connectors to analyze your emails and build personalized writing skills(24:21) Creating a thinking-partner skill for decision support(26:18) Cowork vs. OpenClaw(27:18) Building a sub-advisory skill with multiple AI personas for feedback(34:03) Advanced skill example: Multi-step newsletter creation with research and evaluation(36:08) Setting up scheduled tasks for morning debriefs(37:57) Going beyond one-off tasks with AI(41:00) Progressive trust and the tradeoff of information for productivity(44:08) Different use cases beyond work productivity(46:08) Lightning round—Tools referenced:• Claude Code: https://claude.ai/code• Wispr Flow: https://whisperflow.ai/• Monologue: https://www.monologue.to/• Domo: https://www.domo.com/• Pencil.dev: https://pencil.dev/• Remotion: https://www.remotion.dev/• Obsidian: https://obsidian.md/• OpenClaw: https://openclaw.com/• Notion: https://notion.so/—Other references:• Get Started with Claude Cowork: https://support.claude.com/en/articles/13345190-get-started-with-cowork—Where to find JJ Englert:YouTube: https://www.youtube.com/channel/UCv2ovDhYVtlJw4QMidLFP8QX: https://twitter.com/jjenglertLinkedIn: https://www.linkedin.com/in/jj-englert-a08836a6/—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• I built a custom Slack inbox. It was easier than you’d think. | Yash Tekriwal (Clay) 08.04.2026 44min

  Yash Tekriwal is the head of education at Clay. A self-described hyper-optimizer, Yash has built multiple custom productivity applications using Perplexity Computer and OpenClaw to manage his overwhelming daily workflow—including a Slack digest system that categorizes over 150 daily notifications into actionable priorities, and a consolidated news/email/Slack dashboard that serves as his personal command center.What you’ll learn:How Yash built a custom Slack digest that categorizes 150+ daily notifications into action-required, need-to-read, and FYI bucketsWhy Perplexity Computer beats Claude Code and Codex for building personal productivity appsHis “anti-to-do list” framework: spending an hour daily automating tasks you never want to do againHow to use AI for deterministic tasks (APIs, structured data) vs. subjective tasks (categorization, summarization)Why the SaaS apocalypse narrative is wrong—and why we’re about to see an explosion of micro-softwareHow his team uses Perplexity Computer to prototype design systems and communicate with cross-functional partners—Brought to you by:Guru—The AI layer of truthThoughtSpot—Build AI-powered analytics into your product—In this episode, we cover:(00:00) Introduction to Yash(02:38) The burden of 150 daily Slack notifications(05:45) When to use AI for tasks vs. building deterministic code(06:38) Building the Slack digest with OpenClaw(11:33) Introducing Perplexity Computer and the visual dashboard(14:28) Three reasons Perplexity Computer beats Claude Code(16:14) Using connectors to automate meeting follow-ups across Notion and Asana(18:21) The Kanban-style Slack dashboard(20:15) The long tail of customer requests and the future of micro-software(24:09) The anti-to-do list framework(26:21) Building a consolidated news, email, and Slack digest(29:48) How Perplexity Computer handles authentication and deployment(31:46) Team use case: Prototyping persona-based learning journeys for Clay University(35:49) Lightning round and final thoughts—Tools referenced:• Perplexity Computer: https://www.perplexity.ai/computer/new• OpenClaw: https://openclaw.ai/• Discord: https://discord.com/• Claude Code: https://claude.ai/code• Codex: https://openai.com/codex/• Asana: https://asana.com/• Airtable: https://airtable.com/• Figma: https://www.figma.com/• Vercel: https://vercel.com/• ChatGPT: https://chat.openai.com/—Other references:• Slack: https://slack.com/• Notion: https://www.notion.so/• Superhuman: https://superhuman.com/• Clay University: https://www.clay.com/university• Kanban boards: https://en.wikipedia.org/wiki/Kanban_board—Where to find Yash Tekriwal:LinkedIn: https://www.linkedin.com/in/yashtekriwal/X: https://x.com/yash_tekCompany: https://www.clay.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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• I gave Claude Code our entire codebase. Our customers noticed. | Al Chen (Galileo) 06.04.2026 45min

  Al Chen is a field engineer at Galileo, an observability platform for AI applications, where he works on the front lines with enterprise customers asking highly technical questions. Despite never having held an engineering role, Al has built a system using Claude Code to query Galileo’s 15 separate repositories, combine that with Confluence documentation and customer-specific quirks, and deliver hyper-personalized answers that would otherwise require constant engineering support.What you’ll learn:How to use Claude Code to query multiple repositories simultaneously for customer supportWhy code is often a better source of truth than documentationHow to combine repository context with Confluence and Slack using MCPsThe “customer quirks” system that creates hyper-personalized deployment guidesHow to build virtuous loops that turn single customer questions into scalable knowledgeWhy information organization matters less in the AI eraA simple 16-line script (written by Claude Code) that pulls the latest main branch across all your repositories to keep your context currentHow to reduce engineering interruptions to near-zero by empowering customer-facing teams to query the codebase directly—Brought to you by:Orkes—The enterprise platform for reliable applications and agentic workflowsTines—Start building intelligent workflows today—In this episode, we cover:(00:00) Introduction to Al Chen(02:50) The problem: documentation wasn’t enough(04:23) Pulling 15 repos into VS Code(06:03) How Claude Code queries the entire codebase(08:00) Why current code beats documentation(08:31) The pull script that keeps everything updated(09:54) Opening projects at the multi-repo level(11:40) Live demo: answering deployment questions(13:25) The customer quirks system(15:00) Living in chaos: why organization matters less now(17:03) Competing on customer experience, not just product(18:20) Should customers be able to query the code directly?(20:05) Where humans still add value(25:46) Using AI for reactive Slack support(29:16) The “and then” workflow discovery(32:07) Scaling processes across the team(34:07) Lightning round and final thoughts—Tools referenced:• Claude Code: https://claude.ai/code• VS Code: https://code.visualstudio.com/• Pylon: https://usepylon.com/• Confluence: https://www.atlassian.com/software/confluence—Other references:• Slack: https://slack.com/• Kubernetes: https://kubernetes.io/• Stack Overflow: https://stackoverflow.com/• Intercom: https://www.intercom.com/—Where to find Al Chen:LinkedIn: https://www.linkedin.com/in/thealchen/Company: https://www.rungalileo.io—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• How to turn Claude Code into your personal life operating system | Hilary Gridley 30.03.2026 51min

  Hilary Gridley is an entrepreneur, former product leader, and new mom who previously appeared on the podcast discussing AI for managers. She returns to share how she's transformed her approach to personal productivity using Claude Code as her primary tool for managing both professional work and life admin. Hilary demonstrates her "anti-system system"—a philosophy that prioritizes simplicity over complex setup, allowing AI to learn preferences through observation rather than upfront configuration.What you’ll learn:How to capture to-dos instantly using a simple iPhone back-tap shortcut that requires zero app switchingThe “10x impact framework” for deciding what tasks to automate versus where to invest your human effortHow to use Claude Code’s observation capabilities to build a preference file that improves over time without manual setupWhy the “yappers API” (talking about what you’re doing while working) eliminates the need for complex OAuth integrationsA workflow for breaking down overwhelming tasks into 10-minute first steps that actually get completedHow to create Claude Skills by simply describing problems rather than writing code or following tutorialsTechniques for using “recording mode” to demo workflows without exposing personal information—Brought to you by:WorkOS—Make your app Enterprise Ready todayLovable—Build apps by simply chatting with AI—In this episode, we cover:(00:00) Introduction to Hilary Gridley(02:43) The opportunity cost of time as a new mom and entrepreneur(07:11) Philosophy of the anti-system system(08:05) Demo: Planning your day with Claude Code(10:00) Setting up simple iPhone shortcuts for task capture(11:48) How Claude organizes reminders and learns preferences automatically(16:19) Breaking down overwhelming tasks into manageable first steps(23:40) The yappers API: talking to Claude instead of building integrations(25:28) Daily logging and observation patterns(27:45) Quick summary(30:50) The power of screenshots(32:55) 10x impact framework for automation decisions(37:51) Applying the framework to different career stages(39:29) Building a “recording on” skill for anonymizing demos(44:11) Building a returns tracking skill from scratch(48:31) Building the muscle memory to reach for AI tools(50:18) Where to find Hilary—Tools referenced:• Claude Code: https://claude.ai/code• Obsidian: https://obsidian.md/• iPhone Shortcuts: https://support.apple.com/guide/shortcuts/welcome/ios• Cursor: https://cursor.sh/—Other references:• Figma file Hilary demo’ed: https://www.writerbuilder.com/howiai—Where to find Hilary Gridley:Substack: https://hils.substack.com/Website: https://writerbuilder.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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• How Stripe built “minions”—AI coding agents that ship 1,300 PRs weekly from Slack reactions | Steve Kaliski (Stripe engineer) 25.03.2026 41min

  Steve Kaliski is a software engineer at Stripe who has spent the past six and a half years building developer tools and payment infrastructure. He’s part of the team that created “minions”—Stripe’s internal AI coding agents, which now ship approximately 1,300 pull requests per week with minimal human intervention beyond code review. In this episode, Steve demonstrates how Stripe engineers activate development work from Slack and leverage cloud-based development environments for parallel agent workflows, and demos machine-to-machine payments where AI agents transact autonomously with third-party services.What you’ll learn:How Stripe’s “minions” write 1,300 pull requests per week with minimal human interventionWhy a good developer experience for humans creates better outcomes for AI agentsThe critical role of cloud development environments in unlocking AI-powered engineering velocityThe machine payment protocol that lets AI agents spend money to accomplish tasksThe code review strategy for handling thousands of agent-written PRsWhy non-engineers at Stripe are starting to use minions to ship codeThe future of software businesses built primarily for agent consumers—Brought to you by:Optimizely—Your AI agent orchestration platform for marketing and digital teamsRippling—Stop wasting time on admin tasks, build your startup faster—In this episode, we cover:(00:00) Introduction to Steve(02:39) Stripe’s minions and their effect on Stripe as a whole(04:42) Why activation energy matters more than execution(05:44) What is a minion? The technical architecture(06:52) Demo: Activating a minion from Slack with an emoji(09:04) Why good developer experience benefits both humans and agents(11:22) Walking through the agent loop and system prompts(13:42) Why Stripe chose Goose as their agent harness(16:00) The role of Stripe’s developer productivity team(17:15) Why cloud environments unlock multi-threaded AI engineering(21:14) One-shot prompting: from Slack to shipped PR(22:04) How Stripe handles code review for 1,300 AI-written PRs weekly(23:44) Non-engineers using minions across the company(24:53) Demo: Planning a birthday party with Claude and machine payments(32:15) Quick recap(35:08) The future of ephemeral, API-first businesses for agents(36:36) Lightning round and final thoughts—Detailed workflow walkthroughs from this episode:• How Stripe's AI 'Minions' Ship 1,300 PRs Weekly from a Slack Emoji: https://www.chatprd.ai/how-i-ai/stripes-ai-minions-ship-1300-prs-weekly-from-a-slack-emoji• How to Build an Autonomous AI Agent That Pays for Services to Complete Tasks: https://www.chatprd.ai/how-i-ai/workflows/how-to-build-an-autonomous-ai-agent-that-pays-for-services-to-complete-tasks• How to Automate Code Generation from a Slack Message into a Pull Request: https://www.chatprd.ai/how-i-ai/workflows/how-to-automate-code-generation-from-a-slack-message-into-a-pull-request—Tools referenced:• Goose (AI agent harness): https://github.com/block/goose• Claude Code: https://claude.ai/code• Cursor: https://cursor.sh/• VS Code: https://code.visualstudio.com/• Slack: https://slack.com/• Browserbase: https://browserbase.com/• Parallel AI: https://www.parallel.ai/• PostalForm: https://postalform.com/• Stripe Climate: https://stripe.com/climate—Other references:• Stripe machine payments: https://docs.stripe.com/payments/machine• Blue-Green Deployment: https://martinfowler.com/bliki/BlueGreenDeployment.html• Git worktrees: https://git-scm.com/docs/git-worktree—Where to find Steve Kaliski:Twitter: https://twitter.com/stevekaliskiLinkedIn: https://www.linkedin.com/in/steve-kaliski-079a7710/—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
• How Microsoft's AI VP automates everything with Warp | Marco Casalaina 23.03.2026 34min

  Marco Casalaina, VP of Core AI Products and AI Futurist at Microsoft, demonstrates how he uses AI tools to automate administrative tasks that typically consume valuable time. Rather than using Warp as a coding assistant (its primary marketed purpose), Marco leverages it to manage Azure resources, scan documents, compress videos, and more. He shows how these “micro-agents” can reduce friction in everyday workflows, allowing him to focus on higher-value activities. Marco also demonstrates how Microsoft 365 Copilot and ChatGPT can create triggered workflows that respond to emails or check for information on a schedule, highlighting how the line between consuming and building AI agents is blurring.What you’ll learn:How to use Warp to manage Azure resources and assign permissions without navigating complex web interfacesTechniques for automating document scanning and processing directly from the terminalMethods for analyzing and compressing video files using AI-generated FFmpeg commandsHow to create simple rules that dramatically improve AI performance for specialized tasksWays to build triggered workflows in Microsoft 365 Copilot that automatically respond to emailsHow to configure ChatGPT to perform scheduled tasks like checking for new contentStrategies for creating consistent AI interactions using AutoHotkey shortcuts—Brought to you by:Rovo—AI that knows your businessLovable—Build apps by simply chatting with AI—In this episode, we cover:(00:00) Introduction to Marco Casalaina(02:14) Why Marco chose Warp for administrative tasks(03:57) Demo: Using Warp to manage Azure resources and permissions(06:00) How CLI tools eliminate GUI friction for complex tasks(07:18) Creating rules to improve AI performance for specialized tasks(10:28) Demo: Document scanning automation(13:00) Combining odd and even pages using a Python automation(15:04) The value of ephemeral AI solutions vs. permanent tools(17:12) Video compression using FFmpeg commands(20:22) The concept of “ad hoc agents” for specific tasks(22:31) Demo: Creating triggered workflows in Microsoft 365 Copilot(25:51) Demo: Setting up scheduled tasks in ChatGPT(27:17) How AI automation changes time management(29:14) Teaching AI skills to the next generation(30:30) Strategies for improving AI performance with AutoHotkey—Detailed workflow walkthroughs from this episode:• How Microsoft's AI VP Automates Everything with 5 Micro-Agent Workflows: https://www.chatprd.ai/how-i-ai/microsofts-ai-vp-automates-everything-with-5-micro-agent-workflowsHow to Create an Automated Meeting Scheduler with Microsoft • 365 Copilot: https://www.chatprd.ai/how-i-ai/workflows/how-to-create-an-automated-meeting-scheduler-with-microsoft-365-copilot• How to Scan and Merge Two-Sided Documents into a Single PDF with AI: https://www.chatprd.ai/how-i-ai/workflows/how-to-scan-and-merge-two-sided-documents-into-a-single-pdf-with-ai• How to Automate Azure User Role Management with AI in the Terminal: https://www.chatprd.ai/how-i-ai/workflows/how-to-automate-azure-user-role-management-with-ai-in-the-terminal—Tools referenced:• Warp: https://www.warp.dev/• Microsoft Azure: https://azure.microsoft.com/en-us• Azure CLI: https://learn.microsoft.com/en-us/cli/azure/• Microsoft 365 Copilot: https://www.microsoft.com/en-us/microsoft-365/copilot• ChatGPT: https://chat.openai.com/—Other references:• NAPS2: https://www.naps2.com/• PyPDF2: https://pypdf2.readthedocs.io/• FFmpeg: https://ffmpeg.org/—Where to find Marco Casalaina:LinkedIn: https://www.linkedin.com/in/marcocasalaina/—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—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.