Documentation

Feedback loop

The feedback loop is the axis that lets Mnemix learn from outcomes. A caller agent reports what actually happened after it acted; Mnemix audits the context read and adjusts what it surfaces next time. This is what keeps the brain self-correcting instead of frozen.

The feedback record (beta)

A feedback record links a served memory packet to an outcome verdict and, when available, a correction. The public voice API does not expose this beta intake surface yet; it remains an internal substrate primitive until it graduates into the frozen public API.

Feedback verdictMeaning
helpfulThe surfaced context was right and useful.
wrongThe context was incorrect.
staleThe context was outdated.
missingThe context the agent needed wasn't surfaced.

What happens downstream

Today (as built): a feedback row does two things, immediately —

  1. Audits the read. The original context read's audit record (context_audit) is updated with the outcome, so every packet Mnemix served has a verdict attached to it.
  2. Adjusts memory confidence. The referenced memory objects get an immediate confidence adjustment — wrong/stale signals push the offending chunks down in future retrieval; helpful reinforces them.

On the roadmap (not yet live): nightly reranker calibration from accumulated verdicts, grader-threshold tuning on miscalibrations, and automatic locked-fact supersession proposals from wrong + correction pairs. Those are designed but not shipped — this page will say so when they are.

Closing the loop on coding (the dogfood case)

The clearest example is Mnemix governing its own construction. Internally, a GitHub Action can hand the merged PR outcome to the private feedback intake:

on:
  pull_request:
    types: [closed]
jobs:
  feedback:
    if: github.event.pull_request.merged == true
    runs-on: ubuntu-latest
    steps:
      - run: echo "Internal beta: send the merged PR outcome to the private feedback intake"

The public docs intentionally stop at the handoff point because this intake surface is spec-frozen but not publicly callable yet. When a merged PR later breaks staging or needs a revert, the internal workflow records that verdict and optional correction so the corpus learns which kinds of changes drift.

Why this is a primitive, not a feature

Without feedback, governance is static: the rules never improve, retrieval never adapts. The feedback loop is what turns a set of rules into a system that gets better the more it's used — while still never deleting history.

See also