Teaching — how the system learns what to do

The connectors and processing loop are machinery; the user has to tell the system what to do, correct it, and get its ideas surfaced back. The system should feel like something you're teaching, not configuring — that framing is current. Scope check (ruling 11): this area is more ambition than reality, still important, but not central — don't let it crowd out the working system when prioritizing.

What shipped of it

The teaching relationship exists, through a different stack than the original design guessed:

• Personality/guide cards holding source: inferred beliefs.
• The retro procedure (bbx retro): mines recent chat sessions for what the boxholder implicitly taught, integrates it as beliefs with recurrence-based confidence, and turns authoritative changes into question cards (../implemented-plans/box-retrospectives.md).
• Briefing cards — per-directory agent context.
• Category rules on landmark cards — triage corrections accrete as prose rules at the destination (../triage.md).

The original §23 "meta-processes (future)" — behavior review, instruction distillation — is implemented as the retro system.

What remains aspiration

• Proposals — the system creating "I think we should do X" artifacts and waiting for buy-in. No proposal-card schema exists; the closest living path is a retro-generated question card. Proactive suggestion ("you have three meetings tomorrow and no prep time — want me to block some?") is wanted (see interaction-model.md on proactivity) but not built.
• Feedback loops from edits — user modifies a draft, system learns tone. Retro covers the chat-visible slice of this; nothing systematic beyond it.

The goal stands: better at knowing what you want in familiar territory, better questions in unfamiliar territory. This is where the personality of a box lives — what makes it yours rather than generic automation.