Decide and set the tripwires

Commit on the numbers; leave a door for the future.

First time here? Paste the Context Pack first so the AI understands your project - open it from the header above.

Prompt Capsule

Make the decision. Score files, vectors, and hybrid on: recall quality per my query mix (weighted by the actual style ratios), operational cost (dependencies, embedding upkeep, backup story), debuggability (can I see why recall returned X?), inspectability (human read/edit, git-diffable), and migration cost later. Write the decision paragraph citing the benchmark numbers. Then set revisit triggers with values: entry count exceeding N, paraphrase-miss rate above M% in recall logs, or recall latency above T. Add the trigger checks to the memory health metrics if those exist. Whatever wins, ensure a human-readable export path exists so memory is never opaque.

Paste into EmergentFull Build: complete implementation prompt with explicit requirements

Quick is short. Full Build is recommended for most steps. Strict forces real logic when the AI keeps faking output.

Actual change check

Expected after this step

A numbers-backed decision with concrete revisit triggers.

Should NOT happen

An existing feature broke
A button only logs to console
Data disappears after refresh
Errors fail silently with no visible state

This is what should exist before you continue. If reality does not match, do not move on.

Your notes for this step

Track what changed, failed, or needs follow-up. Notes export with the flow.

Pass the Verify Gate to complete this step

Verify before continuing

Do not move on until every check is true. The complete button stays locked until then.

Scores weighted by the real query mixDecision cites the benchmarkTriggers have numeric thresholds wired to metrics where possible

Do not continue if…

! Adopting a vector stack for 80 memories a grep would search perfectly
! Dismissing vectors while users paraphrase every query and lexical misses them
! Benchmarking on toy data that flatters one side
! A decision without triggers, silently outgrown a year later

If the AI messes this up

Use this when:

- it only made visual forms or placeholder UI
- buttons do nothing or only log to console
- data is not persisted - state disappears on refresh
- something that worked before is now broken

Use this when the AI fakes progress or breaks the feature. It forces a real fix.

The decision contradicts the benchmark. That means an unstated criterion is doing the work - name it explicitly (e.g. a hard git-inspectability requirement), add it to the matrix, and re-score transparently.