Podcast
How I AI
Hosted by Claire Vo · EN
How I AI, hosted by Claire Vo, is for anyone wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will share a specific, practical, and impactful way they’ve learned to use AI in their work or life. Expect 30-minute episodes, live screen sharing, and tips/tricks/workflows you can copy immediately. If you want to demystify AI and learn the skills you need to thrive in this new world, this podcast is for you.
74episodes
Episodes
Newest firstAll episodes
Spec-driven development: The AI engineering workflow at Notion | Ryan Nystrom
3d ago00:47:53Summary readyRyan 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.
Summary
Code with Claude: The 5 biggest updates explained
1w ago00:11:50Summary readyClaire 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.
Summary
Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird)
1w ago00:42:19Summary readyJohn 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.
Summary
The internal AI tool that’s transforming how Stripe designs products | Owen Williams
1w ago00:54:44Summary readyOwen 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.
Summary
From a $6.90 newsletter to $3M API: How a non-coder built Memelord | Jason Levin
2w ago00:51:53Summary readyJason 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.
Summary
GPT 5.5 just did what no other model could
3w ago00:23:36Summary readyIn 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.
Summary
What Claude Design is actually good for (and why Figma isn’t dead, yet)
3w ago00:27:33Summary readyIn 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.
Summary
How Intercom 2x’d their engineering velocity in 9 months with Claude Code | Brian Scanlan
3w ago01:18:45Summary readyBrian 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.
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Claude Cowork 101: How to automate your workday without touching code | JJ Englert (Tenex)
Apr 1300:50:11Summary readyJJ 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.
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I built a custom Slack inbox. It was easier than you’d think. | Yash Tekriwal (Clay)
Apr 800:44:36Summary readyYash 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.
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