The agent principal-agent problem

David Crawshaw · 7 May 2026

David Crawshaw did not write this page.

Every claim below was made in this piece, quoted word for word and numbered in the order the piece makes them, so you can read it there rather than take our word for it. The sentence above each quote is our reading of the claim, not their wording. Each quote was checked against a stored copy of the page at build time; where the two differ, the quote is the fact.

Our reading
Code review as a review mechanism depends on reviewers being able to infer effort from reading code, and AI-agent-generated code erases that signal.
Mental modelSignalling

Their wordsthe reviewer is the principal, the contributor is the agent, and code review only worked because the reviewer could cheaply infer effort from reading the code. Agents collapse that signal.
Our reading
A person directing an AI agent rather than writing code themselves has no incentive to actually read the resulting code or engage seriously with reviewer feedback.
Mental modelIncentives

Their wordsThere is no incentive for the human driving the agent to actually read the code or spend time thinking about what the reviewer says.
Our reading
Making the person who directs an AI agent also own the deployment removes the principal-agent misalignment that agent-driven code review creates.
Mental modelSkin in the game

Their wordsthere is no principal-agent problem, because the human driving the machine takes on the responsibility for its actions by owning the deployment.

Keep reading

The other pieces are the ones whose claims are worded most like this one's. That measures language, not agreement: they may argue the opposite.