Why this decision matters
AI coding assistance mainly reduces time spent on boilerplate, interface adaptation, test drafting, code explanation and documentation synchronization.
Use AI for bounded tasks with compilable or testable outputs, then invest the saved time in architecture review, critical logic, security and target-environment validation.
Conditions to confirm before development
- Draft repetitive data structures, validation and interface boilerplate
- Generate unit and boundary tests from an agreed contract
- Explain unfamiliar modules, logs and dependencies during diagnosis
- Synchronize comments, API notes and change summaries with reviewed code
Implementation and delivery approach
Limit each task to defined files or interfaces and require formatting, static analysis, tests and human review before integration.
Compare cycle time, review changes, defects and test outcomes for similar tasks rather than measuring generated lines of code.
Acceptance boundary
Security-critical, financial, permission and low-level device code needs stricter review. Generation speed is not a delivery-time guarantee.