Boris Cherny describes a transformation already complete at Anthropic: “Every single function on our team codes. Our PMs code, our designers code, our EM codes, our finance guy codes. Everyone on our team codes.” He predicts “the title software engineer is going to go away. It’s just going to be maybe builder, maybe product manager.”
The team he’s building reflects this: “I’m sort of a hybrid — I do design and user research and write code. We love hiring engineers that are like this. We love generalists.” The most effective engineers are bimodal — either hyper-specialists who understand runtime systems better than anyone, or hyper-generalists who span product, design, and user research.
The most revealing hiring signal: an engineer named Daisy “instead of just adding a feature, first put up a PR to give Claude Code a tool so that it can test an arbitrary tool. Then she had Claude write its own tool instead of herself implementing it.” Boris values this meta-level thinking — building tools for the agent to build with — over raw implementation skill.
Boris himself no longer writes code by hand: “I uninstalled my IDE. It’s just 100% Claude Code and Opus. I land 20 PRs a day.” At Anthropic, “since Claude Code came out, productivity per engineer has grown 150%” — compared to his Meta days where “a gain of 2% in productivity was a year of work by hundreds of people.”
This extends Technical knowledge can become a liability when working with AI from the individual level to organizational design. It also connects to AI compresses the distance between idea and execution but not between good and bad judgment: when everyone can code, the differentiator becomes judgment about what to build, not the ability to build it.