What happens after coding is solved? | Fiona Fung (Manager of the Claude Code and Cowork Teams)
episodePreviously titled “Building the most AI-pilled engineering team in the world | Fiona Fung (Manager of the Claude Code and Cowork Teams)” — renamed by the publisher on Aug 2, 2026
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What has Fiona learned about building a high-performing engineering team?
Anthropic engineers on average have eight times as much code per quarter as they did compared to 2025. Coding is no longer the bottleneck.
It's left at the ceiling of what anyone is able to do.
Everything is now possible in theory. Now it's about how ambitious can you be?
It's always something we ask ourselves. What's better than me doing it? I haven't thought to.
The people that seem to be doing best are taking the most initiative, getting the most proactive, have the most agency.
We say with high agency is also high accountability. So it's all about making sure folks have the freedom to cook. But then it's also like, okay, what's the accountability for it?
How is AI transforming the role of software engineers?
What's a hypothesis of what you're trying to solve?
I'm curious what is lost in this new world of software engineering.
How does Fiona's team use AI to manage and review output?
could start being a lonely experience because we all started just working with our agents so much. And on the Clock Code team recently, we started a pairwise programming lunch.
Something you think about is this gap forming between people that are leaning into AI, killing it, and then people that are not. Super frustrated, fighting, resisting.
In terms of frustration, I think sometimes I also see a little bit of fear. For anything that there is a fear, my advice is lean in and ask, what can I do about it? What is within my control?
Today, my guest is Fiona Fung. Fiona leads the teams behind Claude Cote and co-work at Anthropic. She oversees both Boris Cherny and Kat Wu, both of whom who have been on the podcast and whose episodes are in the top 10 most listened to episodes of all time. Before Anthropic, at Microsoft, Fiona ran the teams that built TypeScript and Visual Studio. After that, she went to Facebook, where she started the Facebook Marketplace team, which she took from idea to launch. Today, Facebook Marketplace generates over $100 billion in GMV every year. Also, while at Meta, she oversaw work on Meta's first smart glasses product, and then she helped build Orion, their first AR glasses product. Then she went to Instagram, where she led infrastructure, growth, integrity, and safety teams.
While at Instagram and at Meta, she oversaw an org of over 500 people.
What does an AI-pilled software team look like in 2026?
Fiona has been an engineer for over 25 years and as a long-time engineering leader, especially now at Anthropic, she has such a unique lens into where things are heading, what's worth paying attention to, and what teams should be thinking about right now as AI transforms the world of building. A huge thank you to Kat Wu, Boris Cherny, and Mohamed Hegazi for suggesting topics and questions for this conversation. Before we get into it, don't forget to check out Lenny'sproductpass.com for a free year of the hottest and most well-crafted AI products in the world, available exclusively to Lenny's newsletter subscribers. With that, I bring you Fiona Fung. Fiona, thank you so much for being here. Welcome to the podcast.
Thanks so much for having me, Lenny.
So I was at the Code with Claude event, I don't know, a month ago at this point. And I went to your talk and I was just like, holy shit, I got to get Fiona on this podcast. She's thinking so far ahead of where everybody else is going and where people are at with AI. So you've been an engineer for 25 years. I was browsing your LinkedIn. You started at IBM of all places. Such a different place to be these days.
What is the 'bad vs. sad' quality framework in software development?
Yes. And it's just insane how much the job of an engineer has changed over the past just like two years. It's like a completely different job. Like people may forget 100% of code was written by humans not long ago. And now it's getting to 100% of code written by AI. As Boris famously said, coding is salt. Along these lines, there's just this tweet that you guys put out yesterday where you showed, here's the tweet. Anthropic engineers on average ship eight times as much code per quarter as they did compared to 21 to 2025. We'll show this chart on the screen. It's just like stable, stable, stable, stable, shooting off into the moon. So it's just insane how much this role has changed. I'm curious about your kind of path as an engineer going, living through this, having been an engineer for a long time.
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Chapters
8 chapters
1
What has Fiona learned about building a high-performing engineering team?
0:00–0:30
2
How is AI transforming the role of software engineers?
0:30–0:36
3
How does Fiona's team use AI to manage and review output?
0:36–1:53
4
What does an AI-pilled software team look like in 2026?
1:53–3:05
5
What is the 'bad vs. sad' quality framework in software development?
3:05–4:06
6
What challenges does context switching present in AI-native teams?
4:06–4:17
7
How are product management and data science roles evolving?
4:17–8:38
8
What keeps Fiona up at night regarding team culture at scale?
8:38–1:38:42
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