Why this decision matters
AI tools can assist requirement structuring, code drafting, test design, diagnosis and document review, but gains depend on constraints, review and automated validation.
AI is most useful for repetitive and verifiable work. It should not replace architecture decisions, business confirmation, security review or final acceptance.
Conditions to confirm before development
- Convert meeting and requirement material into reviewable checklists
- Draft boilerplate, bounded interface code and test cases
- Assist log inspection, error explanation and version comparison
- Cross-check API documents, deployment steps and change records
Implementation and delivery approach
Define coding rules, interface contracts, test gates and review ownership before using AI-generated intermediate work. Keep every change under version control and human review.
Measure requirement-to-review time, test coverage, rework, build pass rate and documentation consistency rather than lines of generated code.
Acceptance boundary
AI output can contain incorrect logic, outdated dependencies or unsafe implementation. Engineers must review permissions, data handling and production configuration.