@curiouskitty Great question. To avoid turning Waydev into a commit/LoC scoreboard we made a few deliberate product choices.
First, we do not optimize around raw activity metrics. Indicators such as commits, lines of code, PR counts, and the like may be useful as context, but they are simplistic and dangerous in game when used as results. We focus more on system-level flow, quality, and delivery signals such as cycle time, review time, deployment frequency, change in failure rate, rework, incidents, and what we actually ship to production.
Second, we extend measurement from the individual to the team, repo, and organizational level. The goal is to understand how the system performs, where work gets stuck, and whether the adoption of tooling, process, or AI is improving outcomes. Not to rank engineers.
Third, we combine metrics rather than displaying them in isolation. Increased PR volume alone tells you very little. But PR volume plus more review time, more work and more events tell a very different story. This way you reduce metric gaming by making the trade-offs visible.
Fourth, we recommend that companies use Waydev for coaching and operating rhythms, not performance management. The best rollouts are for engineering leaders, not as scorecards for individual compensation discussions. Use it to ask: where are the bottlenecks, which teams need support, what changed after adopting AI tools, what’s improving, what’s getting worse?
My simple rule is this: if a metric can be easily played, it should never be a goal. It may be a signal, but never a target.
So the operational model we propose is:
Measure teams and systems, not individuals.
Look at bundles of results, not single vanity metrics.
Use trends and before/after analysis, not snapshots.
Combine quantitative signals with qualitative context such as DevEx feedback
Never use a single metric as a proxy for engineer quality.
This way you get value from engineering intelligence without creating Goodhart-law behavior.