Brex CEO：别只搭一个 Agent，要搭有职责、主管和预算的 AI 员工

A product team's effectiveness depends on how quickly it turns customer signals into something that actually solves the problem.

When building becomes easier, choosing the right problem matters more than shipping a larger number of features.

Consistent product quality requires reviewing real work and turning repeated judgments into reusable standards.

An AI employee should own a defined job with persistent state, specific skills, and a human escalation path.

Candidate assessments should remain traceable to evidence and reviewable by humans rather than being treated as unquestionable scores.

A code-capable agent needs enforceable boundaries outside its own instructions, including controls on network actions.

Token consumption becomes meaningful only when it is connected to a use case, an outcome, and the money actually paid.

Teams can allow bounded exploration first and optimize proven workflows later using evidence about quality and cost.

Signals from messages, meetings, and email become useful when they update an inspectable state for people and projects.

Selling completed work raises the product bar because customers expect an outcome, not merely access to a tool.