Engineering workflow
Software Development
Use AI across coding, testing, and documentation while preserving review, provenance, security, and release ownership.
Engineering teams often begin with coding assistance and extend into review, testing, documentation, and internal tooling. Speed gains are useful only when repository and release discipline remain intact.
Candidate workflows
- bounded code and test generation
- documentation and migration drafts
- issue triage and codebase orientation
- repetitive refactoring with automated verification
Evidence to gather
Measure accepted output, review time, defect escape, security findings, test coverage, rework, and delivery time. Track whether generated changes are understandable to the team that owns them.
Staying in charge
Delegated: drafting, test generation, analysis, and well-scoped code changes.
Monitored: review findings, test results, dependency changes, secrets, provenance, and production behavior.
Accountable: the human author and approving reviewer remain answerable; release owners retain the authority to reject, roll back, or remove generated work.