A meeting note is not ready for an AI agent until it separates evidence from state

Most AI note takers stop when the transcript becomes a clean summary. That is useful for a person reading the meeting, but it is not enough for an AI agent that has to continue the work later.

The failure is simple. A summary mixes three different things: what was actually said, what is currently true, and what should happen next. Once they are mixed, a later agent cannot tell whether ship Friday was a firm commitment, a suggestion, or the summarizer's inference.

I have started using a three layer note.

Source: the transcript or audio with timestamps. This is evidence, not working memory.

Current state: goals, decisions, constraints, owners, deadlines, and open questions.

Change log: what changed, what it replaced, and the source timestamp for the change.

Then I test the note in a fresh AI session. I give it only the exported note and ask what was decided, what is still uncertain, who owns the next action, which claims are directly supported, and what would become stale if a newer conversation changed one constraint.

A good note should let the agent answer and point back to evidence. It should also survive one correction. If yes was actually maybe, fixing it once should update every later export and retrieval result.

This changes how I evaluate note takers. I care less about whether the summary sounds polished and more about whether another agent can retrieve the right current state, act on it, and show why.

Disclosure: I am building Handov around this conversation to agent handoff problem, so I am biased. The three layer test is useful with any note taker or plain Markdown file.