What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams)
- Source
- lennysnewsletter.com
- Author
- Lenny Rachitsky
- Date
Context
More generated code is an incomplete measure of engineering progress. Fiona Fung, who leads the Claude Code and Cowork teams at Anthropic, describes pairing freedom to pursue ideas with accountability for the problem being solved.
Her examples explain why output counts can mislead: porting an existing library can produce many lines, while a framework change can deliver the same result with fewer. She recommends defining the intended outcome and choosing a measure that tracks it. In this account, an engineer's responsibility includes deciding what improvement matters and checking whether the work delivered it.
“Coding is no longer the bottleneck. It's lifted the ceiling of what anyone is able to do.”
Fiona Fung
“We say with high agency, it's also high accountability.”
Fiona Fung
“Like it's okay to make mistakes, just make new ones so that we're always learning.”
Fiona Fung
“culture is like a living breathing thing. It's not just a poster you slap on a wall”
Fiona Fung
- 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
podcastThe 100-person AI lab that became Anthropic and Google's secret weapon | Edwin Chen (Surge AI)
podcastWhy humans are AI’s biggest bottleneck (and what’s coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead)
podcastThe coming AI security crisis (and what to do about it) | Sander Schulhoff
podcastWhy most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google, and Amazon
podcastHead of Claude Code: What happens after coding is solved | Boris ChernyLenny Rachitsky
podcastAnthropic’s first technical PM on token maxing, the jagged edge, and living in the future | Dianne PennLenny Rachitsky
podcastHow Anthropic’s product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code)Lenny Rachitsky
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