Feed AI your full evidence constellation, not a cold…
When using AI to analyze accumulated evidence around an open question, provide the constellation of linked notes (question + partial answers + contradictions + gaps) as context rather than asking the AI to answer from scratch, because the accumulated context enables pattern recognition your cold query cannot access.
When This Fires
- You've been researching a question for days or weeks and have accumulated multiple notes
- You're stuck on a problem where you have lots of partial information but no coherent synthesis
- You want AI to help with a question where the generic internet answer isn't what you need
- You're about to type a simple question into AI despite having a rich knowledge trail behind it
Common Failure Mode
Asking AI a fresh question each time you return to a persistent problem, treating each session as independent. You get the same generic answer repeatedly because the model doesn't know about your previous rounds of investigation. Your accumulated evidence — the most valuable input you could provide — sits unused in your notes while you type cold queries.
The Protocol
Before querying AI about a persistent question: (1) Gather all linked notes — the question itself, each partial answer, contradictions between answers, and identified gaps. (2) Paste them as structured context with labels: "Question: ... Partial answers: ... Contradictions: ... Gaps: ..." (3) Ask the AI to identify patterns across the evidence, not to answer the question from scratch. The model's pattern recognition operating on your curated evidence produces insights that neither you nor the model could reach alone.