2026-03-30 23:03:26
Listen now on YouTube • Spotify • Apple Podcasts
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Optimizely—Your AI agent orchestration platform for marketing and digital teams
Rippling—Stop wasting time on admin tasks, build your startup faster
Steve Kaliski has spent over six years building developer infrastructure at Stripe. In this conversation with Claire, he breaks down Stripe’s “minions”: AI coding agents that ship about 1,300 pull requests per week, often kicked off with nothing more than a Slack emoji. He explains why the real bottleneck in engineering isn’t coding, how cloud development environments unlock parallel AI workflows, and what it takes to safely review thousands of AI-generated PRs. He also demos AI agents that can spend money, coordinate services, and complete tasks end-to-end without human involvement.
What’s good for human developers is good for AI agents (and vice versa). Stripe’s years of investment in developer experience—comprehensive documentation, blessed paths for common tasks, robust CI/CD, excellent tooling—directly translates to higher AI agent success rates. When you have clear docs on “how to add a new API field,” the agent can follow those same instructions. This creates a virtuous cycle: investments in DX improve agent performance, and investments in agent infrastructure (like cloud environments) benefit human developers too.
Activation energy is the real bottleneck, not coding speed. Steve hasn’t started work in a text editor in months. Instead, work begins in Slack threads, Google Docs, or support tickets—the natural places where ideas emerge. By allowing engineers to kick off development with a single emoji reaction, Stripe lowered the friction between “good idea” and “code in production.” This is especially powerful in large organizations, where coordination costs typically kill momentum before coding even begins.
Cloud development environments are non-negotiable for multi-threaded AI work. Running multiple AI agents in parallel requires cloud-based dev environments that can spin up in seconds, run isolated workloads, and never fall asleep. This infrastructure investment—which Stripe’s developer productivity team built long before AI agents—now enables engineers to run dozens of agents simultaneously without melting their MacBook Pros.
1,300 AI-written PRs per week requires shifting review capacity, not eliminating it. Stripe still reviews every AI-generated PR, but the review process relies heavily on automated confidence signals: comprehensive test coverage, synthetic end-to-end tests, and blue-green deployments that enable quick rollbacks. The bottleneck shifts from writing code to reviewing it—and eventually to generating enough good ideas in the first place.
Machine-to-machine payments unlock ephemeral, API-first businesses. In Steve’s birthday party demo, Claude Code autonomously paid Browser Base, Parallel AI, and Postal Form for single-use services—no human signup, no subscription, no dashboard. Businesses can now optimize for agent consumers rather than human users, focusing on “hyper-useful single APIs” instead of landing pages and admin panels. The economics become transparent: tokens and dollars sit side by side, making the true cost of AI work visible.
Treat AI agents like new employees, with progressive trust. Start with limited access, expand permissions as the agent proves reliable, and maintain clear boundaries. Each minion runs in an isolated environment with specific data access—the finance agent can read bank statements but can’t send messages; the scheduling agent can text but has no financial data. This physical partitioning prevents accidental data leakage and creates accountability.
The future of software is disposable and hyper-personalized. Steve builds custom iOS apps for his toddler—music players limited to six specific songs—despite having no iOS development experience. He describes this as “the disposability of software”: when AI can build apps in hours, you can create single-purpose tools for incredibly specific use cases and throw them away when they’re no longer needed.
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
Listen now on YouTube • Spotify • Apple Podcasts
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WorkOS—Make your app enterprise-ready today
Lovable—Build apps by simply chatting with AI
Hilary Gridley returns to the podcast to share how her approach to productivity has completely evolved since her last appearance. Now a new mom and entrepreneur, she walks Claire through how she uses Claude Code as a personal operating system, managing everything from daily planning to life admin without complex tools or rigid workflows. Instead of building elaborate systems, Hilary leans into what she calls the “anti-system system”: letting AI observe her behavior, learn her preferences over time, and gradually take work off her plate. Together, Claire and Hilary explore how simple inputs—like capturing tasks with a shortcut or “yapping” to Claude throughout the day—can replace traditional productivity stacks and integrations.
The 10x impact framework: For any task, ask “If I were 10 times better at it, would it have 10 times the impact?” If no, automate it. If yes, keep it human. This applies to both work tasks and life tasks—including whether baking bread will bring you joy or feel like a chore.
Complexity has to earn its keep. Hilary only connects APIs and builds complex integrations after testing the “janky version” of a workflow for a week. Her hit rate is only 20% on workflows she actually continues using, so starting simple saves massive time.
The yappers API beats OAuth every time. Instead of connecting all your tools in the background, just talk to Claude about what you’re doing throughout the day. Hilary keeps Claude Code open in her terminal and narrates her work, letting Claude observe and take notes without complex integrations.
Let AI learn your preferences by observing, not by your defining them. Hilary never sat down to write out her ideal schedule. Claude just watches what she actually does (not what she says she’ll do) and adjusts preferences automatically. Real behavior beats aspirational planning.
Calendar management is the ultimate to-do list. You can’t say you take something seriously if you’re not putting time into it. But manually adding tasks to your calendar is tedious—so let Claude do it automatically based on what you say you want to accomplish.
Screenshots are your friend for getting started. Don’t wait for API access or permissions at work. Build a janky version with screenshots and voice dictation, prove it’s valuable, and then get the permissions you need. Half-baked ideas don’t deserve full access.
You don’t need coding knowledge to build Claude Code skills. Hilary just describes problems to Claude: “I keep forgetting to return things on time.” Claude asks a few questions, then builds the entire workflow—including checking return policies and drop-off locations automatically.
Test everything before integrating it into working systems. Hilary refuses to add new workflows to her daily routine until she’s tested them separately for a week. If something breaks, you don’t want it taking down systems that were already working.
Build the muscle memory by doing one thing with AI every day. The biggest barrier isn’t technical knowledge—it’s rewiring your brain to think “the alien in my computer could help with this.” Hilary went from “I’ll never use the terminal” to running her life in Claude Code in about a week.
How I AI: Hilary Gridley’s “Anti-System” for Automating Life with Claude Code: https://www.chatprd.ai/how-i-ai/gridleys-anti-system-for-automating-life-with-claude-code
Create a Privacy-Protecting Demo Mode for Your Personal AI: https://www.chatprd.ai/how-i-ai/workflows/create-a-privacy-protecting-demo-mode-for-your-personal-ai
Build Custom AI Automations by Having a Conversation with Claude: https://www.chatprd.ai/how-i-ai/workflows/build-custom-ai-automations-by-having-a-conversation-with-claude
Automate Your Daily Planning with Claude Code and an iPhone Shortcut: https://www.chatprd.ai/how-i-ai/workflows/automate-your-daily-planning-with-claude-code-and-an-iphone-shortcut
If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.
Catch you next week,
Lenny
P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.
2026-03-30 20:04:24
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.
Listen or watch on YouTube, Spotify, or Apple Podcasts
How to capture to-dos instantly using a simple iPhone back-tap shortcut that requires zero app switching
The “10x impact framework” for deciding what tasks to automate versus where to invest your human effort
How to use Claude Code’s observation capabilities to build a preference file that improves over time without manual setup
Why the “yappers API” (talking about what you’re doing while working) eliminates the need for complex OAuth integrations
A workflow for breaking down overwhelming tasks into 10-minute first steps that actually get completed
How to create Claude Skills by simply describing problems rather than writing code or following tutorials
Techniques for using “recording mode” to demo workflows without exposing personal information
WorkOS—Make your app Enterprise Ready today
Lovable—Build apps by simply chatting with AI
(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
• Claude Code: https://claude.ai/code
• Obsidian: https://obsidian.md/
• iPhone Shortcuts: https://support.apple.com/guide/shortcuts/welcome/ios
• Cursor: https://cursor.sh/
• Figma file Hilary demo’ed: https://www.writerbuilder.com/howiai
Substack: https://hills.substack.com/
Website: https://writerbuilder.com
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-03-29 20:31:50
Claire Vo is the host of our sister podcast, “How I AI,” a former product executive and engineer, and founder of an AI startup called ChatPRD. Claire now runs her business, podcast, and family life with the help of nine OpenClaw agents running on multiple Mac Minis and old laptops. In this episode, Claire shares her journey from OpenClaw skeptic (it deleted her family calendar the first time she tried it) to true believer, and gives a masterclass in using AI agents in real life.
Listen on YouTube, Spotify, and Apple Podcasts
The exact step-by-step process to install and set up OpenClaw (it’s easier than you think)
How to avoid the biggest OpenClaw mistakes (don’t install it on your main computer)
Actual use cases that have changed Claire’s life (e.g. family scheduling, inbound sales, podcast prep, and course management)
Why multiple specialized agents beat one general-purpose agent
The security risks everyone worries about—and how to handle them
Browser limitations, memory issues, and practical workarounds
Mercury—Radically different banking
Omni—AI analytics your customers can trust
Orkes—The enterprise platform for reliable applications and agentic workflows
• LinkedIn: https://www.linkedin.com/in/clairevo
• Podcast: https://www.youtube.com/@howiaipodcast
• Website: https://clairevo.com
• ChatPRD: https://www.chatprd.ai
• OpenClaw: https://openclaw.ai
• Claude Cowork: https://claude.com/product/cowork
• Fry’s Electronics: https://en.wikipedia.org/wiki/Fry%27s_Electronics
• Peter Steinberger on LinkedIn: https://www.linkedin.com/in/steipete
• Telegram: https://telegram.org
• WhatsApp: https://www.whatsapp.com
• Fin: https://fin.ai
• Why OpenClaw feels alive even though it’s not (this AI has a heartbeat but not a brain): https://x.com/clairevo/status/2017741569521271175
• 5 OpenClaw agents run my home, finances, and code | Jesse Genet: https://www.youtube.com/watch?v=96Vl8s3EQhk
• Executive Playbook for AI in Engineering, Product, and Design: https://maven.com/clairevo/ai-native-epd-org
• Zach Davis on LinkedIn: https://www.linkedin.com/in/zach-m-davis/
• ChatGPT Atlas: https://chatgpt.com/atlas
• Perplexity Comet: https://www.perplexity.ai/comet
• Browser (OpenClaw-managed): https://docs.openclaw.ai/tools/browser
• Buffer: https://buffer.com
• Brave: https://brave.com/search/api/
• Exa: https://exa.ai
• Hilary Gridley on X: https://x.com/yourgirlhils
• How to become a supermanager with AI: https://www.lennysnewsletter.com/p/how-to-become-a-supermanager-with
• How custom GPTs can make you a better manager | Hilary Gridley (Head of Core Product at Whoop): https://www.youtube.com/watch?v=xDMkkOC-EhI
• How to debug a team that isn’t working: the Waterline Model: https://www.lennysnewsletter.com/p/how-to-debug-a-team-that-isnt-working
• Jensen Huang on LinkedIn: https://www.linkedin.com/in/jenhsunhuang
• How I built a 1M+ subscriber newsletter and top 10 tech podcast | Lenny Rachitsky: https://www.lennysnewsletter.com/p/how-i-built-a-1m-subscriber-newsletter
• Age of Attraction on Netflix: https://www.netflix.com/title/81779095
• Oura Ring: https://ouraring.com/
• Eight Sleep: https://www.eightsleep.com
• Hoopsalytics: https://hoopsalytics.com
• DJI Osmo smartphone gimbal: https://www.amazon.com/DJI-Stabilizer-Tracking-Extension-Stabilization/dp/B0FJ2L67HJ?ref_=ast_sto_dp
• Silent basketball: https://www.amazon.com/Rzkipdy-Silent-Basketball-Size-27-5/dp/B0FHFSQWPP/ref=sr_1_9
• Marc Andreessen: The real AI boom hasn’t even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom
• Treasure Island: https://www.amazon.com/Treasure-Island-Robert-Louis-Stevenson/dp/1505297400
• Alice’s Adventures in Wonderland: https://www.amazon.com/Alices-Adventures-Wonderland-Illustrated-Illustrations/dp/991673268X
• Charts for Babies: A Picture Book: https://www.amazon.com/Charts-Babies-Picture-Book/dp/1419785184
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Lenny may be an investor in the companies discussed.
2026-03-29 01:01:42
👋 Hello and welcome to this week’s edition of ✨ Community Wisdom ✨ a subscriber-only email, delivered every Saturday, highlighting the most helpful conversations in our members-only Slack community.
2026-03-25 20:03:34
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.
Listen or watch on YouTube, Spotify, or Apple Podcasts
How Stripe’s “minions” write 1,300 pull requests per week with minimal human intervention
Why a good developer experience for humans creates better outcomes for AI agents
The critical role of cloud development environments in unlocking AI-powered engineering velocity
The machine payment protocol that lets AI agents spend money to accomplish tasks
The code review strategy for handling thousands of agent-written PRs
Why non-engineers at Stripe are starting to use minions to ship code
The future of software businesses built primarily for agent consumers
Optimizely—Your AI agent orchestration platform for marketing and digital teams
Rippling—Stop wasting time on admin tasks, build your startup faster
(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
• 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
• 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
Twitter: https://twitter.com/stevekaliski
LinkedIn: https://www.linkedin.com/in/steve-kaliski-079a7710/
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-03-24 20:45:12
👋 Hey there, I’m Lenny. Each week, I answer reader questions about building product, driving growth, and accelerating your career. For more: Lenny’s Podcast | Lennybot | How I AI | My favorite AI/PM courses, public speaking course, and interview prep copilot
P.S. Get a full free year of Lovable, Manus, Replit, Gamma, n8n, Canva, ElevenLabs, Amp, Factory, Devin, Bolt, Wispr Flow, Linear, PostHog, Framer, Railway, Granola, Warp, Perplexity, Magic Patterns, Mobbin, ChatPRD, and Stripe Atlas by becoming an Insider subscriber. Yes, this is for real.
Welcome to our biannual State of the Product Job Market—our fourth and, very surprisingly, the most optimistic. In spite of the headlines about layoffs and AI taking jobs, we’re actually seeing a lot of promising signs in tech hiring, and some interesting new trends:
PM openings are at the highest levels we’ve seen in over three years
AI hasn’t slowed the demand for software engineers (at least not yet)
AI roles in general are absolutely exploding
Design roles have plateaued
The Bay Area is increasing in importance
Remote work opportunities continue to decline
Despite ongoing layoffs, the overall number of tech jobs continues to grow
While these numbers are promising, I know a lot of people are having a hard time finding a job right now. And more openings doesn’t automatically mean people are finding jobs more quickly. For anyone in that situation, first of all, I’m sorry. Second, I’m working on ways to help. Until then, check out the end of this post for a bunch of resources I’ve collected that’ll improve your odds of landing a gig.
Let’s get into it.
This analysis is based on data from TrueUp, one of my favorite collaborators and sources of data. They track job openings at tech companies and top startups around the world (over 9,000 companies) and make it easy to browse open gigs. Their data looks at roles at tech companies—the most sought-after and lucrative jobs. (It doesn’t include roles at non-tech companies and consulting agencies.)
There are over 7,300 open PM roles at tech companies globally, and trending up. This is 75% above the low we saw in early 2023, and already up nearly 20% since the start of this year. Today we have the most open PM roles we’ve seen since 2022. (You can see all of these open roles here.)
The same trend is true for engineering roles . . .
There are over 67,000 (!!!) eng openings at tech companies globally right now, with 26,000 just in the U.S. We don’t know if there would have been more open roles if not for AI or if AI is actually leading to more open roles, but since the start of this year, the increase in open eng roles is accelerating even more.
If you’re skeptical that this growth is real and likely to be sustained, we’re also seeing a surge in demand for tech recruiters. The number of open recruiter roles is almost back to 2022 peak levels. This role got hit the hardest post-Covid, and also recovered the quickest. By definition, recruiting headcount expands and contracts with hiring demand, so it’s likely a leading indication that we’re tracking toward sustained highs in hiring demand in tech.
AI roles were already growing fast in our last update mid-last year, but they are now hockey-sticking:
“AI roles” includes (1) all open roles at AI-driven companies, like OpenAI, Anthropic, Cursor, and Lovable, and (2) AI-specific roles at non-AI companies, like an AI PM at Figma. Browse them here.
Demand for AI engineers and AI PMs is similarly exploding.
Whether this is simply the number of AI companies being created or the headcount at top AI companies growing, it’s a good time to be in AI.
Unlike PM and engineering, open design jobs have been relatively flat since early 2023, and there are also fewer of these roles than PMs and engineers in absolute terms (about 5,700 globally).
I don’t know exactly what’s going on here, but it does feel AI-related. Unlike PM and eng, which started growing in 2024 (two years post-ChatGPT), design didn’t. If I had to venture a theory, I’d say that because AI is allowing engineers to move so quickly, there’s less opportunity—and less desire—to involve the traditional design process. A recent tweet commented on this same trend. That said, you’d think design would become a differentiator as more products compete for attention. Something to think about for your company! We’ll keep watching this trend and AI’s impact on org design more generally.
One interesting observation we made when we went a level deeper: the ratio of demand for PMs vs. designers has flipped. In mid-2023, we went from more open designer roles to more open PM roles. And ever since, PM demand has been pulling away (currently 1.27x). This will be another trend to monitor, in terms of how AI is reshaping org design.
The Bay Area has long had the highest share of tech roles, but that share is still growing. Over 20% of all eng and designer roles are now in the Bay Area, and over 23% (!!!) of open PM roles are too (up 50% since 2022!). And all three are still going up.
A whopping third of open AI roles are based in the Bay Area, but, interestingly, this number has stayed relatively flat in the past few years. That tells me that the Bay Area unquestionably continues to be the center of AI (the next city is New York, with 10.2%), but at the same time, AI roles outside the Bay Area continue to grow at the same rate.
One more interesting data point: NYC has established itself as the #2 tech jobs location in the world, despite not being the headquarters of any of the leading tech companies. Bengaluru (formerly Bangalore), London, Tel Aviv, and Singapore continue to be the top international hubs for tech.
