Files
ai-resume/content/ai/l3/ai-memory-layers.md
Documenter 00fa15f98f Phase 1: content source of truth — 40 documents across six areas
Satisfies the Phase 1 Definition of Done:

- content/ validates cleanly against the frozen schema. `make validate`
  reports OK: 40 document(s) validated, 0 violations.
- Six areas exist, each with an L1 entry: ai-overview, platform-overview,
  edge-overview, products-overview, history-overview, about-overview.
- All six areas have an L2 entry: ai-systems, platform-estate, edge-fleet,
  products-business, history-engagements, about-narrative.
- 28 L3 artefact stubs under content/<area>/l3/. Every artefacts[].url in
  every document resolves to one of them; the validator proves there are no
  dangling references (and a deliberately broken copy exits 1).
- Every metric value traces to a source line in the evidence notes or the
  approved metric set in reference/content-map.md (per-metric citations are
  recorded in the AUD-131 completion comment).
- Every document carries confidence and last_verified=2026-10-26; the
  validator rejects a missing or non-canonical value.
- docs/content-redaction.md records the redaction pass: identifiers, third
  party personal data, credentials and infrastructure detail excluded, with
  reasons, plus the two numbers that are reported rather than smoothed.

Honesty positions held: 3 businesses active (12 adoptions over time),
Where-Woof deployed and pre-market, failures kept in (edge-failures), no
promotion of in-progress work to delivered.

No site code, no templates, no CSS, no rendering (Phase 2).
2026-10-26 17:30:35 +11:00

1.3 KiB
Raw Blame History

id, area, level, title, claim, confidence, period, tech, metrics, artefacts, public, last_verified, tags
id area level title claim confidence period tech metrics artefacts public last_verified tags
ai-memory-layers ai 3 Artefact — Memory in two layers · Engram and Headroom Memory is split by purpose — Engram stores what should persist and Headroom keeps what should not persist out of the context window. running 2020–
Engram
Headroom
SQLite
JEV
label value
memory layers 2
true 2026-10-26
ai
memory
context
artefact

Artefact — Memory in two layers · Engram and Headroom

Status: stub. A redacted session handoff and a before-and-after context measurement land in Phase 7.

What the artefact is

Engram is local-first storage for curated summaries, decisions, prompts and session handoffs in SQLite, so a conversation can be resumed in any project; it is integrated with JEV for fast compaction. Headroom is token control: it strips, cleanses and analyses code and logs before they reach the model, compressing rather than truncating.

What it proves

Two distinct problems recognised as two — persistence and window economy — instead of one tool asked to do both.

When it is delivered

Phase 7. Both tools are part of Sam's own workflow; they are deliberately not part of the public assistant, which is stateless by decision (see reference/decisions.md D11).