Level Up

Run a 7-question adaptive assessment to map what the user knows and doesn't, relevant to the current project. The output is two files future agents rely on.

Files (repo-relative)

• notes/learning/david-knowledge.md — verbatim Q&A pairs + ratings, one section per question, rounds appended.
• notes/learning/LEARNING-PLAN.md — one concise bullet per genuine gap found.

State-check first: read both files in full if they exist. If previous rounds exist, pick mostly-new territory and calibrate starting difficulty to the recorded level. If missing, create the folder and both files (plan starts as just a header).

Question rules

• 7 questions, strictly one at a time, plain text — never the questions UI.
• Start easy, adapt difficulty each answer: good answer → harder, weak answer → sideways or down.
• Orchestrator level only: systems, architecture, failure modes, security, data, scaling, product strategy, unit economics. NEVER syntax or code trivia — the user architects via AI agents, not by writing code.
• Anchor questions in the current project's real stack and features. When a question touches real code, read it and show the actual snippet when teaching.
• Cover different territory across rounds (e.g. round 1: request flow, DB, billing, moats; round 2: deploys, testing, incidents, data modeling, AI engineering, webhook security, cost engineering).

After every single answer

1. Rate honestly 1-10. No flattery — the user wants calibration, not comfort.
2. Say concisely what was missed or wrong, and teach the correct concept in a few sentences.
3. Immediately save the verbatim answer + rating + gap notes to david-knowledge.md.
4. If a genuine gap surfaced, append one concise bullet to LEARNING-PLAN.md. Skip minor misses.
5. If the user pushes back on a rating ("I knew that, just didn't say it"), bump only if genuinely deserved, and record the bump with its reason.
6. When the user says they have since learned a plan item, mark its bullet: strikethrough + ✓ learned YYYY-MM-DD.

After question 7

Append a final summary to david-knowledge.md: per-question ratings, overall score, the recurring pattern across answers (e.g. "architecture instincts ahead of failure-mode instincts"), strengths to build on, and gaps added. Give the user the same summary in chat, concise.