What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams)
Source
Lenny Rachitsky
Author
Lenny Rachitsky
Date
Why it matters
How Anthropic runs a team shipping 8x more code
Claude 'routines' reshape async work and managing engineers
The 'bad vs. sad' quality framework for AI output
Chapters
00:00Introduction to Fiona Fung
02:31How the engineering role has transformed over 25 years
09:28What an AI-pilled software team looks like in 2026
12:26Using Claude to manage and review team output
14:40The evolution of code review and verification
16:55Who to hire: creative builders and deep systems experts
18:18The shift to ambitious thinking
19:40The growth mindset required to thrive in AI-native teams
25:52Helping small businesses adopt AI tools
31:46How Anthropic spots latent demand and builds for it
35:08The next frontier: asynchronous work with AI routines
38:06Agency and accountability in AI-native teams
39:40The vibe shift from token-maxing to ROI measurement
44:24The 'bad vs. sad' quality framework
49:34Why all managers start as ICs at Anthropic
55:24Preventing skill atrophy
58:43Managing context switching with 20 AI agents running
1:00:08How PM and data science roles are transforming
1:03:40The importance of dogfooding and using your own product
1:08:36Outstanding questions
1:12:48The future of engineering jobs and education
1:17:59What keeps Fiona up at night: team culture at scale
1:22:53From six-month roadmaps to JIT monthly planning
1:27:03Lightning round
Transcript
Fiona Fung leads the teams behind Claude Code and Cowork at Anthropic (overseeing Boris Cherny and the entire engineering and PM team). Before Anthropic, she spent 11 years at Microsoft building Visual Studio and TypeScript and then moved to Meta, where she started Facebook Marketplace (now generating over $100 billion in GMV annually), worked on Meta’s first smart glasses and AR glasses, and led infrastructure, growth, integrity, and safety teams at Instagram. She’s been an engineer for over 25 years and has a unique perspective on how the role of building software is changing. In our in-depth conversation, we discuss: 1. What she’s learned about running a team that’s shipping 8x more code than before 2. Which roles AI will transform next 3. Specific ways her team uses AI 4. How Claude “routines” have changed how she operates as a manager 5. The context-switching problem no one has solved yet 6. The biggest unsolved problem in AI 7. What keeps her up at night — Brought to you by: WorkOS —Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lenny Mercury —Radically different banking, now with Command: https://mercury.com/ — Where to find Fiona Fung: • LinkedIn: linkedin.com/in/fionafung — Where to find Lenny: • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ — In this episode, we cover: (00:00) Introduction to Fiona Fung (02:31) How the engineering role has transformed over 25 years (09:28) What an AI-pilled software team looks like in 2026 (12:26) Using Claude to manage and review team output (14:40) The evolution of code review and verification (16:55) Who to hire: creative builders and deep systems experts (18:18) The shift to ambitious thinking (19:40) The growth mindset required to thrive in AI-native teams (25:52) Helping small businesses adopt AI tools (31:46) How Anthropic spots latent demand and builds for it (35:08) The next frontier: asynchronous work with AI routines (38:06) Agency and accountability in AI-native teams (39:40) The vibe shift from token-maxing to ROI measurement (44:24) The “bad vs. sad” quality framework (49:34) Why all managers start as ICs at Anthropic (55:24) Preventing skill atrophy (58:43) Managing context switching with 20 AI agents running (1:00:08) How PM and data science roles are transforming (1:03:40) The importance of dogfooding and using your own product (1:08:36) Outstanding questions (1:12:48) The future of engineering jobs and education (1:17:59) What keeps Fiona up at night: team culture at scale (1:22:53) From six-month roadmaps to JIT (just-in-time) monthly planning (1:27:03) Lightning round — References: https://www.lennysnewsletter.com/p/building-the-most-ai-pilled-engineering — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com . — Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com
