phase5-prove · git:20260423.96a5b2c · 2026-04-23 · sha256 7c7d66c2e2902ff2
phase5-prove git:20260423.96a5b2cA
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--- name: phase5-prove description: The Mileva Method (CRISP) — Phase 5: Prove. Success validation against Phase R baseline metrics, test log review, and AI justification validation. Use after deployment. Triggers on "prove", "phase 5", "validate", "did it work", "success criteria", "measure results", or after go-live. --- # P — Prove: Success Validation > Did the needle move? ## Project State > At the start of Phase P: read `docs/crisp-state.json`. Pull `phases.R.baseline` and `phases.R.successTarget` as the measurement baseline. Check `phases.S.sprints` to know what was built. > > At the end of Phase P: update `docs/crisp-state.json`: > - Add `"P"` to `phases.complete` > - Set `phases.P.complete` to `true` > - Set `phases.P.outcome` to `"success"`, `"partial"`, or `"fail"` > - Add summary notes to `phases.P.notes` This phase closes the loop back to Phase R. Three questions drive everything. --- ## 1. Did the needle move? Pull the baseline and targets from `docs/success-metrics.md` and measure against them: - **Quantitative:** Did each metric hit its target? (e.g. "quotes sent in 4min vs 4h before") - **Qualitative:** Re-run the survey or interview from the Phase R baseline frustration score — did it improve? - **Second-order effects:** Did the downstream impacts materialise? (e.g. cart abandonment dropped after checkout speed improved) --- ## 2. Was everything actually built and verified? Read `docs/test-log.md`. For every sprint that shipped: - Is there a test log entry? - Did every specced behaviour (from the sprint's AI Spec test requirements) get a test written and run? - Are there any ❌ failures that were never resolved? > A system where the metrics look good but tests weren't written is a system running on luck. The test log is how you know the difference between "it works" and "it worked that one time we checked." If the test log has gaps — identify what wasn't verified and decide: is this a risk to the outcome measurement, or is it acceptable to close? --- ## 3. Did the AI justify itself? Read `docs/problem-statement.md` — AI Justification section. The client agreed to custom AI because it could do something off-the-shelf products couldn't. Ask: **did that thing actually materialise?** > "We said custom AI was justified because [X]. Did [X] happen? Is the client getting something from this that they couldn't get from Claude.ai at $20/month?" If yes → close it. If no → document the gap honestly. It's a learning, not a failure — but it should be captured so the next project's justification gate is sharper. --- ## Outcomes **Success** → document what worked, close the project, capture learnings. **Partial** → identify which metrics hit and which didn't. Was the target unrealistic, or did the solution miss? **Fail** → return to Phase R. The problem may have been misdiagnosed, or the success criteria were wrong. > In Serbia, when things go sideways, we make jokes. It's not denial — it's perspective. Balkan humor is the ability to look at a disaster and find the absurdity before you find the culprit. Apply that here. If Phase P says fail, laugh once — then go back to Phase R with fresh eyes. A failed outcome is the most honest piece of data you'll collect in the whole project. The problem was misdiagnosed. Now you know exactly where. That's worth something. --- ## Exit Checklist - [ ] Quantitative metrics measured against baselines in `docs/success-metrics.md` - [ ] Qualitative scores re-evaluated against Phase R frustration baseline - [ ] Second-order effects checked - [ ] `docs/test-log.md` reviewed — all sprints have entries, no unresolved ❌ failures - [ ] Every specced behaviour from AI Spec test requirements confirmed as verified - [ ] AI justification validated — did custom AI deliver what justified not using off-the-shelf? - [ ] Success / partial / fail called explicitly — no ambiguity - [ ] Learnings documented (incl. what the test log revealed and whether AI justification held) - [ ] Client signed off