- Every session starts with the learner's knowledge graph as base
context (precision probing); selection problem noted: pedagogical
relevance != semantic closeness (structural neighborhood, diagnostic
hotspots, frontier strip); strategies to tune on data.
- Sub-agent architecture: async background workers with live activity
indicators; demo-builder TESTS code headlessly; visual-maker verifies
by looking (port of vault svg-maker); mermaid needs no sub-agent;
researcher tool for fact verification (port of pi web-search/web-fetch
+ interactive-subagents researcher prompt).
- Not-a-chat presentation principle marked LOW PRIORITY per user.
Amos
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