Inside Claude Code: How an AI Native Team Actually Works | Cat Wu
Claude Code product lead on getting user feedback every 10 minutes, choosing prototypes over docs, and why designers and PMs should check in code directly
Dear subscribers,
Today, I want to share a new episode with Cat Wu.
Cat is the product lead for Claude Code and she showed me how one of the most AI-native teams in tech actually works. Highlights include getting user feedback every 10 minutes, going straight to prototypes instead of docs, and designers checking in code directly. Cat also shared her 3 best Claude Code tips and what’s next for the product.
Watch now on YouTube, Apple, and Spotify.
Cat and I talked about:
(00:00) The process behind the best Claude Code features
(05:00) How engineers can own features from idea to launch
(10:04) Getting feedback every 10 minutes from 1000+ users
(14:00) How designers and PMs can ship production code
(19:58) How the Claude Code team does AI evaluations
(29:04) 3 tips from Cat to get the most out of Claude Code
(30:12) Why your Claude.md file is so important
(33:32) What's next for Claude Code and AI agents
Thanks to Miro for sponsoring today’s newsletter
Miro got to the bottom of what’s causing workflow bottlenecks in their new survey of 6,000+ knowledge workers worldwide, and the results aren’t pretty:
🔴 62% say busywork drains their energy and 58% report reduced creativity
🔴 83% push their best work outside the workday
One stat that offers encouragement: 76% believe AI can help reduce silos and cut repetitive tasks so people can focus more on creative, strategic work.
Top 10 takeaways I learned from this episode
Ship demos, not docs. “We don’t use Google Docs much on our team. The source of truth is the code base.” Cat and the team prefer using Claude Code to prototype features to get user feedback ASAP instead of writing multi-page specs.
Engineers own features end-to-end. "Many of our best features came from an engineer prototyping an idea and shipping it to internal users.” You can tell whether a feature is good or not by whether internal users and beta customers start using it organically. Just ship progressively and see what users love.