---
description: Extract learnings, domain knowledge, and decisions from the session and propose updates to context files
---

Review the current conversation and summarize everything learned about Sam's preferences, workflows, decisions, domain knowledge, and way of working that is NOT already captured in the existing context files.

## Instructions

1. Read the relevant context files to understand what is already documented:
   - ~/.config/opencode/AGENTS.md (global preferences)
   - The current project's AGENTS.md (if one exists)
   - ~/LLM Context/AGENTS.md (context system and file organization)
   - Any initiative-specific AGENTS.md files that were referenced in this session
   - Any other context files that were loaded during this session
   - ~/.config/opencode/skills/*/SKILL.md (existing skill definitions)
   - ~/.config/opencode/commands/*.md (existing command definitions)
   - ~/LLM Context/.opencode/commands/*.md (project-local command definitions)
   - Knowledge/ directories at relevant scopes (initiative, company/personal, global)
   - Decisions/ directories at relevant scopes (initiative, company/personal, global)
   - ~/LLM Context/Shared/Templates/decision-template.md (for decision format)

2. Compare what was learned during this conversation against what is already documented. Identify NEW learnings only -- skip anything already captured. Before proposing any change, read the current content of the target file to verify a previous session has not already applied the same learning.

   Determine which scopes are relevant to this session (e.g., Business/Monizze/, a specific initiative). If ambiguous, ask Sam to confirm the scope before proceeding.

3. Categorize each learning:
   - **Preference** -- how Sam likes to work (communication, review style, tooling choices)
   - **Decision** -- a concrete choice made during this session (tech stack, architecture, process)
   - **Workflow** -- how Sam interacts with agents, reviews work, iterates
   - **Correction** -- something the agent got wrong that Sam corrected
   - **Domain Knowledge** -- a fact, pattern, or observation about a specific domain (pricing, onboarding, competitors, etc.)
   - **Domain Rule** -- a confirmed pattern that should be applied by default (promoted from hypothesis after 3+ confirmations, or stated directly by Sam)
   - **Domain Hypothesis** -- a pattern that needs more data before becoming a rule
   - **Scoped Decision** -- a decision that affects more than today's task and should be logged for future reference

4. Determine the correct target file for each learning:
   - Global preferences (apply everywhere) -> `~/.config/opencode/AGENTS.md`
   - Project-specific rules -> current project's `AGENTS.md`
   - Context system changes -> `~/LLM Context/AGENTS.md`
   - Domain context -> appropriate file in `~/LLM Context/`
   - Domain Knowledge / Rules / Hypotheses -> `Knowledge/[domain].md` at the appropriate scope
     - If the file exists, add to the correct section (## Rules, ## Hypotheses, or ## Knowledge)
     - If the file does not exist, create it using the format from LLM Context/AGENTS.md
     - Check if any existing hypothesis has now been confirmed 3+ times -- propose promotion to Rule
     - Check if any existing rule was contradicted in this session -- propose demotion to Hypothesis
   - Scoped Decisions -> `Decisions/YYYY-MM-DD-{topic}.md` at the appropriate scope
     - Use the template at `Shared/Templates/decision-template.md`
     - Search existing Decisions/ for prior decisions on the same topic
     - If replacing a prior decision, populate the ## Supersedes field

5. Present learnings for review:

# Learnings - [Date]

## Summary
[1-2 sentence overview of what was learned]

## Proposed Updates

### [n]. [Short description]
- **Type:** [Preference / Decision / Workflow / Correction / Domain Knowledge / Domain Rule / Domain Hypothesis / Scoped Decision]
- **Scope:** [Global / Business/[Company] / Business/[Company]/Initiatives/[Name] / Personal / Personal/Initiatives/[Name]]
- **Domain:** [domain name, if applicable -- e.g., pricing, onboarding]
- **Learning:** [What was learned]
- **Target file:** [Path to the file that should be updated]
- **Proposed change:**
  ```
  [The specific text to add or modify in the target file]
  ```
- **Status:** Pending review

[Repeat for each learning]

## No Update Needed
[List any learnings that are already captured in existing files -- confirm they match]

6. After presenting the full summary, walk through each proposed change ONE AT A TIME. For each:
   - Show the change (target file, what will be added/modified)
   - Ask: "Accept, reject, or modify?"
   - Wait for Sam's response before moving to the next
   - Only apply the change after explicit acceptance

7. For each accepted change, update the target file immediately, then present the next one.

8. After all changes are reviewed, add a "Last Updated" entry to each modified file with the date and a brief description.

IMPORTANT:
- Never apply changes without Sam's explicit approval
- Always go one at a time -- never batch approvals
- Be specific -- show exact text to add/modify, not vague suggestions
- If a learning contradicts an existing rule, flag the conflict and ask which is correct
- Include the source of each learning (what Sam said or did that revealed it)
- Skills and commands are valid target files -- if a session revealed a gap or correction in a skill or command, propose an update to that file directly
- For knowledge items, always specify which section (Rules / Hypotheses / Knowledge) the entry belongs in
- When promoting a hypothesis to a rule, remove it from ## Hypotheses and add it to ## Rules with a note like "Promoted from hypothesis -- confirmed in [sessions/dates]"
- When demoting a rule to a hypothesis, remove it from ## Rules and add it to ## Hypotheses with a note like "Demoted -- contradicted by [what happened]"
- For scoped decisions, always use the decision template format
- When scope is ambiguous, ask Sam before proceeding -- one topic at a time