Precise, fast lookups from massive memory.md
It’s clear that a new kind of multi-faceted, multi-layered “memory system” is required to properly, fully serve the LLM harness. Not flat files, not semantica, not graph. What?
To my mind, after looking at it for 5 minutes to eval if it’s worth a try …. qmd — ” so qmd lookup engine can prevent the massive .md files from being preloaded into context, right? context could simply be told to ‘defer all lookups to qmd via its mcp’ or something liek that, yes?, to allow huge storage, quick index lookups, and yet tiny contexts?” —–
Yes — that’s exactly the point.
QMD can let us stop preloading huge .md files into prompt context.
Better pattern:
Tiny bootstrap context:
“Do not preload memory docs. Query QMD MCP for project facts, routes,
architecture, prior notes, preferences, and operating constraints.”
Huge Markdown corpus:
indexed by QMD, not pasted into context
At task time:
AI asks QMD:
- project rules for current repo
- relevant architecture
- route/controller docs
- prior notes
- exact file/feature facts
Benefits:
- tiny startup context
- huge durable Markdown storage
- fast lookup
- better relevance than dumping everything
- less stale/sloppy prompt bloat
- Markdown remains human-editable canonical truth
- QMD index is disposable/rebuildable
Important nuance:
- Hard safety rules still need bootstrap/preloaded context.
Things like “no edits without approval”, “no docker”, “don’t touch /opt/self/github/pi” should stay in tiny always-loaded bootstrap. - Everything else can be QMD-deferred.
Ideal split:
Always in prompt:
- minimal immutable operating contract
- current cwd/repo identity
- “query QMD before claiming project facts”
In QMD:
- AGENTS/architecture/inventory/routes/devnotes
- project history
- stack-specific docs
- long preferences
- procedural notes