MEASUREMENT
Stop calling it AI productivity.
Put a dollar value on it.
One unit: engineering rework that did not happen. Work that would have gone on correcting, expanding, re-reviewing or reimplementing an incomplete change — because the missing impact was found before implementation, not after the pull request. Put your own numbers in; we will not let the result pretend to be more than an estimate.
Open detailed for the review, QA, incident and onboarding time the same discovery avoids — and for what GitMir costs you.
Cost of continuing under the assumptions you entered
Every number above came from the sliders, not from your system. The same figures can be observed instead: run the open source on real work, connect the team, and the audit reports what actually happened rather than what was assumed.
See what the audit measures →MODELLED FROM YOUR ASSUMPTIONS — NOT OBSERVED
Evidence level 1 — your own estimate. Nothing here is measured. Level 3 needs workflow evidence: git history, PR comments, task logs and validation records from your own changes. Connect produces it from work your team is already doing.
- Estimate
- Observed from real changes
- Production evidence
The baseline is frozen before GitMir sees the request — the original scope, estimate and acceptance criteria. Then the same change is analysed, implemented and validated.
| Metric | Baseline | With GitMir | Evidence |
|---|---|---|---|
| Affected product objects | 3 | 11 | Confirmed impact map |
| Services in scope | 2 | 6 | Architecture review |
| Acceptance criteria | 4 | 10 | Approved scope |
| Open decisions found | 0 | 3 | Decision log |
| Review cycles | 3 | 1 | PR history |
| Rework hours | 12 | 3 | Team estimate |
| Validation mismatches caught | 0 | 2 | Validation report |
A scope that grew from 3 objects to 11 is not a bigger task. It is the task that was always there, found while changing your mind was still free.
- Level 1EstimateYour own assumptions, multiplied. Useful for a conversation, not for a business case — this is what the calculator above produces.the calculator above
- Level 2Observed baselineYour historical tickets, pull requests, review cycles and incidents, read as they are. Still your data, but no longer your guesses.
- Level 3Observed from real changesYour own changes as they happen, split into the first pass and everything after it: iterations, review cycles, late discoveries, and which areas of the model the time fell in. Produced by Connect, not bought.what a connected team produces
- Level 4Production evidenceThe same measurement running continuously across the organization after deployment.