Session Journal

Overview

Maintains session continuity by logging decisions, progress, and rationale.

Core principle: Check for project lessons at start, log significant decisions during work.

Announce at start: "Applying session-journal skill for context warm-up."

The Process

At Session Start

1. Check <workspace>/.ai-memory/lessons/ for project lessons
2. If found: Load relevant lessons for current context
3. Announce: "Loaded [N] project lessons" or "No prior lessons found"

During Work

Log significant decisions to brain/<conversation-id>/sessions/<YYYY-MM-DD>.md:

## Decisions
- **HH:MM** - [Decision]: [Rationale]

Only log when:

• Choosing between alternatives
• Making architectural decisions
• Deviating from expected approach

At Session End

1. Summarize accomplishments
2. Note open threads
3. Check if patterns emerged → trigger lessons-capture if so

Session Log Format

# Session: YYYY-MM-DD

## Lessons Loaded
[List of project lessons applied]

## Decisions
- **14:32** - Chose Redis over Memcached: Better pub/sub for realtime
- **15:07** - Used existing auth pattern from lesson `auth-jwt.md`

## Open Threads
- [ ] Need to verify rate limiting behavior

Discrepancy Handling

If a loaded lesson contradicts current MCP data (Jira, Confluence):

1. Flag: > [!WARNING] Lesson X says Y but MCP says Z
2. Use MCP data for this session
3. At session end, prompt: "Update lesson?"

Common Mistakes

• Logging every small decision (keep it scannable)
• Forgetting to note WHY a decision was made
• Not checking for project lessons at session start
• Silently overriding lessons without flagging

Checklist

Before ending session:

• Significant decisions logged with rationale
• Open threads documented
• Any discrepancies flagged and addressed