Operate: keeping it correct after go-live
An agent that was right in March starts being wrong in September. Vendors change document formats, thresholds drift away from practice, models get deprecated, and the process the audit mapped quietly moves. The Engineering Engine is infrastructure, and infrastructure gets maintained.
| Measure | Before | After | Change |
|---|---|---|---|
| Review wait time | 11 hours | 2 hours | 82% faster |
| Time to a new hire's first merged change | 26 days | 11 days | 58% faster |
| Context search per engineer | 3.1 hrs/week | 40 min/week | 78% removed |
| First-pass review accuracy | 92.5% | 98.2% | +5.7 pts |
| Cost per pull request reviewed | $57 | $24 | 58% lower |
- W0Go-live92.5%
- W4Dismissed flags retune repository conventions95.1%
- W8Test framework upgrade detected97%
- W12Noise floor raised after false-positive review98.2%
| Point | Value |
|---|---|
| W0 | 92.5% |
| W2 | 93.9% |
| W4 | 95.1% |
| W6 | 96.2% |
| W8 | 97% |
| W10 | 97.7% |
| W12 | 98.2% |
Accuracy climbs because corrections from your team are fed back, not because the model improved on its own. The marked weeks are the events that moved it. Each Engine reaches a different plateau, because each starts from a different baseline and a different exception mix.
Model swaps
Review quality is re-benchmarked against the flags your engineers accepted and dismissed on your own repositories, so a model change is measured on your code rather than a public benchmark.
Codebase drift
Conventions change, services get split, and a review rule tuned against last year's structure starts producing noise. Drift gets detected and the agents retuned against the current tree.
Next workflow along
Internal support questions from finance and operations reuse the context agent already indexing the codebase and its documentation.
- Drift report: where practice has moved away from what the agents were built against
- Threshold tuning against the decisions your team actually made
- Document and format updates as vendors and systems change
- Accuracy review by exception type, not one blended number
- Business review against the baseline the audit set
- Scoping the next workflow, usually the one adjacent to what already runs
- Model re-benchmarking against your own captured decisions
- Roadmap for the following quarter, with what we would not build and why
Start with the engineering workflow that costs you the most
The audit runs 3 to 4 weeks on site at $15–25k, credited in full against a build signed within 90 days. It produces the system map, the exception taxonomy and a build plan, and you own all of it whether or not the build follows.
The before and after columns are modelled from the basis company, and the accuracy curve is the shape we build toward rather than a measurement. Eidral has run no client engagement, so there is no delivered result to show here, and a curve presented as measured would be the one claim on this site that could not survive a reference check.