learn

name	Learn
description	When the principal is in learning mode (reading a repo, watching a talk, processing a new tool), /learn takes a brief input and produces a structured note in vault/concepts/learning/ with category, modern-stack location, relevance verdict, and reconsideration triggers. Captures the value of every learning sweep without requiring it to immediately translate to building.

Learn

The learning compounding skill. Most principals lose the value of a learning sweep within 48 hours — they read three repos, watch one talk, evaluate two tools, and a week later can't remember what they decided about any of them. /learn captures the structured outcome of every such sweep.

When to use

• The principal has just read a repo, paper, talk, or tool description
• The principal is evaluating something but doesn't have an immediate need
• The principal asks "should I be using X?" or "what did we decide about Y?"
• After any session where the input was learning, not doing
• Triggered by Caddy on prompts like: "/learn", "I just read", "evaluating", "looked into", "should I use", "what did we decide about", "captured this", "interesting tool", "considered tool"

How to execute

Step 1 — Take the input

The principal provides:

• Subject: the thing being evaluated (tool, technique, concept, repo, paper, idea)
• Source: where it came from (URL, talk title, conversation, repo name)
• Snapshot: 2-5 sentences on what the thing is and what it claims to do

If any field is missing, ask one focused question to get it.

Step 2 — Locate it on the modern AI stack

Reference [[Modern AI Infrastructure Stack]]. Place the subject at the right layer:

• Application
• Persistence
• Messaging
• Isolation
• Compute
• Observability
• Orchestration

If it doesn't fit cleanly on the stack, it's either a doctrine concept (note that explicitly) or an artifact-of-AI-trends category (e.g., "agent framework", "prompt-engineering pattern").

Step 3 — Assess relevance

Three categories:

• ADOPT — fits an actual current bottleneck. Action follows.
• HOLD — could fit in a future state, but no current bottleneck. Capture the trigger condition.
• REJECT — wrong category, wrong scale, or violates a load-bearing constraint. Capture the reasoning.
• MONITOR — interesting but no clear path. Re-evaluate next quarter.

Step 4 — Capture reconsideration triggers (for HOLD only)

What specific change in circumstances would flip the decision?

• "When the framework starts spawning >10 parallel agents, reconsider isolation tools."
• "When a downstream user can't sandbox safely, reconsider authority gates."
• "When the principal hits the 10K-note vault size, reconsider semantic search alternatives."

The trigger has to be observable. "When we have more time" isn't a trigger. "When DECISION_OUTCOMES.md shows 5+ failed Authority Level 1 actions in a quarter" is.

Step 5 — Write the note

File: vault/concepts/learning/<subject-slug>.md

Format:

---
title: {Subject}
tags:
  - learning
  - {category}
status: ADOPT | HOLD | REJECT | MONITOR
stack-layer: {layer or N/A}
created: YYYY-MM-DD
last-reviewed: YYYY-MM-DD
source: {URL or reference}
---

# {Subject}

## What it is

{2-5 sentences from the input}

## Stack location

{One paragraph on where it sits in the modern AI stack and what category it competes in}

## Verdict

**{ADOPT | HOLD | REJECT | MONITOR}**

{1-3 sentences on the reasoning}

## Reconsider when

{Trigger condition, only for HOLD; for REJECT, "Never (fundamental rejection)"; for ADOPT, this becomes "Adopted on YYYY-MM-DD; re-evaluate annually"; for MONITOR, "Re-evaluate next quarter"}

## Connects to

{Wikilinks to related vault notes — other tools in the same category, doctrine that applies, relevant projects}

Step 6 — Update the index

Append a one-line entry to vault/concepts/learning/INDEX.md:

- [[{subject-slug}]] — {category} — {ADOPT|HOLD|REJECT|MONITOR} — {YYYY-MM-DD}

The INDEX.md is the principal's external memory of considered tools. When they hit a real problem and need to remember "did I look at X?", the index answers in one read.

Anti-patterns this prevents

• Learning sweeps that produce no captured artifact, then are forgotten
• Re-evaluating the same tool from scratch six months later
• Not knowing whether a tool was rejected or just unread
• Reconsider triggers that exist in the principal's head but aren't written down (so they never fire)
• Adopting a tool because it's "cool" without locating it on the stack or assessing fit

Connects to

• [[Modern AI Infrastructure Stack]] — the layer map used for placement
• [[What I Am Not Building]] — REJECT entries from /learn graduate here when worth permanent doctrine
• [[Bio-hacking Posture]] — /learn is the supplements-and-restriction-evaluation skill
• vault/concepts/learning/INDEX.md — the running index this skill maintains