Measure AI impact beyond code generation.
Follow AI-assisted work from suggestion to review, merge and deployment. Understand quality, retention, throughput and cost using metrics your engineering organization already tracks.
Real Waydev dashboard screenshot. Metrics shown are illustrative and may vary by organization.
Understand the AI code lifecycle
Measure what happens to AI-assisted work after it enters engineering workflows.
- Track AI Suggestion Acceptance and Code-to-Merge Survival.
- Monitor Deployed AI Share and AI Churn over time.
- Compare outcome patterns across teams while accounting for data coverage.
Connect output, cost and data confidence
See cost per merged PR and throughput together, instead of confusing high AI usage with productivity.
- Compare AI Cost per Merged PR and token spend.
- Monitor AI PR Throughput and AI Lines per Session.
- Use instrumentation coverage and attribution confidence to interpret results.
Better engineering decisions, grounded in your data.
Beyond adoption
See what happens to AI-assisted work after a suggestion is accepted.
Cost in context
Understand spending alongside merged work and quality signals.
Trustworthy comparisons
Show unknown coverage rather than assuming every change has known authorship.
See AI Agent Effectiveness in action.
Explore how Waydev connects engineering performance, AI impact, delivery quality and cost into decisions that matter.
Dashboard screenshots and examples are illustrative. Availability, metrics and integrations may vary by customer configuration.
