Figma产品经理的AI日常：PM OS实战
做法与步骤
- PM OS是一个共享repo而非产品：Ezra和同事把个人Claude Code配置整理成31个技能，供Figma全体PM使用，靠一个仓库让60到70名PM保持同步。
- Ezra每天运行六次的技能用来驯服Slack，把消息处理自动化，体现“在正确的地方偷懒”的思路。
- 用Codex做bug bash：bug排查agent能发现他本人不会注意到的问题，说明AI在质量检查上有互补价值。
- AutoXP是一个自动化增长PM，只保留一个人工检查点就能跑实验，且第一个实验就找到了大幅增长机会。
- 与Jev合作搭建实时写作助手，Jev还曾接管他参加的所有会议长达两周，展示AI介入日常沟通的深度。
- 技能经过构建、被“吐槽”和精简的过程，最终从终端迁移到本地Web前端，降低使用门槛。
对实践的启示
对AI应用从业者：把个人AI配置沉淀为团队共享的技能仓库，比采购工具更能推动落地；非工程角色也能通过技能化封装用AI完成实际工作，关键是找到高频场景（如Slack）先跑通。
原文摘引
his goal is to be “lazy in the right places.”
he found almost no one outside engineering using AI to get real work done
Why PM OS is a repo, not a product
▸ 展开原文全文（48 段，抓取自 Lenny's Newsletter）
Ezra Mechaber is a growth product manager at Figma whose goal is to be “lazy in the right places.” When he joined Figma, he found almost no one outside engineering using AI to get real work done, so he and a couple of fellow PMs turned his personal Claude Code setup into PM OS, a shared repo of 31 skills that every PM at Figma now uses. In this episode, Ezra walks me through his favorite skills, how he bug bashes with Codex, AutoXP—an automated growth PM that found a huge win on its very first experiment—and a real-time writing assistant he built with Jev.
Listen or watch on YouTube, Spotify, or Apple Podcasts
What you’ll learn:
- Why PM OS is a repo, not a product
- The skill Ezra runs six times a day to tame Slack
- How one repo keeps 60 to 70 PMs in sync
- Why his bug-bash agent catches things he never would
- How AutoXP runs experiments with one human checkpoint
- Why Jev took over every meeting he was in for two weeks
- What to do when you want to yell at your AI
Brought to you by:
Optimizely—Your AI agent orchestration platform for marketing and digital teams
Jira Product Discovery—Prioritize with insights, build with confidence
In this episode, we cover:
(00:00) Episode preview
(00:51) Introduction to Ezra Mechaber
(02:04) The origin story of Figma’s PM OS
(06:30) PM OS demo: the “chief of staff” setup
(10:28) How the repo works: skills, hooks, and private sub-repos
(12:00) How the skills got built, roasted, and whittled down
(14:15) Build artifact, FigJam MCP, and coaching skills
(17:33) Transitioning from the terminal to a local web front end
(19:30) Bug bashing with Codex
(22:08) AutoXP: an automated growth PM
(26:26) Claire’s Experiment Engine backstory
(26:58) Building a real-time writing assistant with Jev
(33:15) Lightning round and final thoughts
Tools referenced:
• Figma: https://www.figma.com/
• FigJam: https://www.figma.com/figjam/
• Figma MCP server: https://developers.figma.com/docs/figma-mcp-server/
• Claude Code: https://www.claude.com/product/claude-code
• Codex: https://openai.com/codex/
• Cursor Automations: https://cursor.com/docs/cloud-agent/automations
• Jev: https://typesafe.ai/
• Marker: https://marker.page/
• Instinct: https://instinct.com/
• Dots: https://openai.com/index/introducing-dots/
Other reference:
• Jev for beginners: how to use it and what to build: https://www.lennysnewsletter.com/p/jev-for-beginners-how-to-use-it-and
Where to find Ezra Mechaber:
LinkedIn: https://www.linkedin.com/in/ezra-mechaber
Website: https://ezramechaber.com/
Where to find Claire Vo:
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].