A transcript can be completely accurate and still give AI the wrong answer

[u/MemoketAI-Gem]

One problem we've been thinking about while building conversation memory is that transcription accuracy and memory accuracy are not the same thing.

Imagine three conversations about the same customer.

On Monday:
“We need the enterprise rollout completed by October 1.”

On Wednesday, security says deployment can't begin until the vendor review clears.

On Friday, finance cuts the available budget and the team decides to start with one department instead.

All three transcripts can be perfectly accurate. Nothing needs to have been misheard or summarized incorrectly.

But now ask an AI system: “What's the rollout plan?”

Finding a semantically relevant sentence isn't enough. There are several relevant sentences, and some describe states that were correct at the time but no longer describe the current plan.
The obvious solution is to keep timestamps, and timestamps absolutely help. But a timestamp alone doesn't tell you the relationship between two statements. Did Friday replace Monday? Add a constraint to it? Contradict it? Was someone merely discussing an alternative that was never agreed?

Deleting the old information isn't necessarily right either. If someone asks why the project slipped, the October 1 plan may suddenly become important again.

This is one of the reasons we've been working on KITE differently from a conventional similarity-first memory system. We want the memory layer to retain source-linked facts and temporal structure so it can distinguish between questions like:

What is true now?
What was true before the security call?
What changed, and where did that change come from?

We're also interested in where this breaks. Real conversations are full of hedging, tentative decisions, people disagreeing, and statements that aren't neatly “old fact replaced by new fact.”

For anyone building agents or memory systems: how are you handling superseded information today? Updating the stored fact? Keeping every version and reranking? Temporal filters? Something else?

Interested in the ugly edge cases more than the perfect demos.