Engineering intelligence
Know whether the work was any good.
- Slop16
- Real judgment11
- Unremarkable85
Throughput tells you a team was busy. It cannot tell you whether anyone exercised judgment, and when producing is free that is the only question left worth asking.
The number your other dashboard is scoring as productivity.
Slop is work that looks right, passes review, and costs you later. It does not show up in throughput because throughput counts it as a win. We compute it from what happens to a change after it merges, and we price it, so the conversation happens in a budget meeting rather than a retro.
- Rework: merged work rewritten within ninety days
- Review drag: reviewer minutes per merged change, by team
- Compounding: complexity added that never comes back down
- Orphaned change: work no author can account for at sampling
Priced
$412k
- Rework38%
- Review drag27%
- Compounding21%
- Orphaned14%
The only number that goes up when people think harder.
Judgment leaves a trace, just not in the event log. It is in what got rejected, what got redirected, and what was thrown away before it cost anything. We read the artifact rather than the metadata, which is why we can see a reviewer who changed the direction of a change and not merely its wording.
- Redirections: review that changed what was built, not how
- Rejections: work stopped before it entered the codebase
- Abandoned designs: the cheapest possible failure, counted as a win
- Concentration: whether judgment sits with three people or thirty
Avoided
$780k
- Payments34%
- Identity28%
- Ledger19%
- Growth8%
Growth ships fastest and thinks least. No throughput chart contains that sentence.
The standard reporting, done properly.
Delivery, review health, quality and DORA, attributed to teams and initiatives rather than to individuals, and benchmarked against organisations we will name rather than an industry average nobody can audit.
- DORA, with the distribution shown and not just the median
- Review as a gate or a bottleneck, per team and per repository
- Incidents traced back to the change that introduced them
- Benchmarks against a named comparison set
Stop making the same correction twice.
Every review comment your team writes is a standard someone is holding in their head. We turn the recurring ones into context the agents actually receive, so the correction is made once rather than every sprint. It is the one feature here that reduces the work instead of reporting on it.
- Recurring review comments clustered into rules
- Rules shipped into the agent's context, not a wiki nobody opens
- Measured by whether the correction stops recurring
- Error handling at boundariescaught 34×
- No new global statecaught 21×
- Migrations must be reversiblecaught 17×
- Test the failure pathcaught 9×
Recurrence down 62% on captured rules since adoption.