Metrics to Track
· One min read
Part 5 of The AI-Assisted Software Engineering Workflow.
Metrics to Track
Delivery
- Idea to initialized repository
- Repository to reviewed plan
- Plan to first working implementation
- First implementation to draft pull request
- Draft pull request to merge
- Merge to deployed result
- Shipped projects or milestones per week
Quality
- Defects found during planning review
- Defects found by Qodo
- Valid findings versus false positives
- Review comments requiring human interpretation
- Rework after implementation
- Escaped defects after merge
AI Efficiency
- Model and effort level by task type
- Planning and implementation usage
- Follow-up prompts per milestone
- Review cycles per pull request
- Manual edits required
- Outcome quality relative to quota consumed
Human Load
- Concurrent active projects
- Time spent restoring project context
- Waiting or blocked time
- Decisions requiring manual intervention
- Satisfaction with the result
Useful workflow comparisons include:
- Codex only
- Opus → Codex
- Opus → Sonnet
- Codex → Opus review → Codex
- Implementation with and without the Qodo gate