Author: Haider Lasani

Agents can run the inner cycle of investigation, implementation, and checking. Teams must still own the outer loop where evidence becomes a decision.

Risk based AI development routes work by blast radius, reversibility, sensitivity, and uncertainty. Low-risk edits use a fast lane.

Clearly wrong code is cheap to reject. Almost-right code consumes expert attention because plausibility can hide one unproven product promise.

A team can generate more code and complete more tasks while creating little product value. Better measurement connects speed to accepted outcomes.

Faster code generation does not remove engineering work. It moves the bottleneck into review, verification, and accountable decisions.

A governed AI feature development workflow moves work through eight connected stages: intake, planning, specification, development, review, checks, documentation sync, and delivery. Each stage reduces a different uncertainty.