You control what the model sees. Bad context = bad output.
🧠
Fixing sessions → building systems that fix sessions
🎯 WHAT CHANGES BY THE END
You'll diagnose why an AI output failed, name exactly what context was missing or wrong, and fix it in one iteration instead of re-prompting until something works.
🙋 THIS IS YOU IF
✓Your CLAUDE.md has explicit rules that came from real failures, not speculation
✓You're deliberate about which files you include. The model only sees what's relevant to the current task
✓When an output fails, your first question is 'what was missing or wrong in the context?'
✓You manage conversation history actively so the model doesn't start contradicting itself mid-session
💡 WHAT WE'LL UNTANGLE
You still re-teach the model the same things every session because lessons aren't getting codified
The same mistakes recur. Fixing context in the moment doesn't prevent it from happening again next time
You're getting better at individual sessions but nothing carries forward
Context goes stale mid-session. The model keeps working from an earlier state after the code has already changed
Over-relying on model memory within a conversation. Do not assume it remembers details from 50 messages ago when it's already past its effective attention span