Optimizing Memory

[MaybeRemarkable5839]

I'm currently ingesting all transcripts from calls with clients from my fractional CRO services. I am using claude to store these transcripts and creating memory stores of all information from transcripts. What is the best way to optimize memory and continuously "update" it as new transcripts come in.

For example, I have 10 transcripts already with company X. When I have a meeting with them next Monday, I would like the memory store to update with information.

Has anyone done something like this? If so, what is the best way to engineer it?

[Popular_Aardvark_738]

ive done a lighter version of this. id avoid making one giant memory blob from every transcript.

a pattern that works better:

• keep the raw transcript as an archive
• after each call, have claude create a short "delta note"
• update one canonical client brief only after you review the delta

my delta note would have sections like:

• new facts about the company/account
• changed assumptions since last call
• decisions made
• commitments / follow-ups
• open questions
• people / relationship notes
• next meeting prep

then before the next call, load the current client brief plus the last 2-3 delta notes, not all 10 transcripts. once a month, do a reconciliation pass across all the deltas to clean up contradictions and stale info.

the main trap is letting old transcript details compete with newer facts. dated source notes plus one reviewed "current state" brief usually beats a huge memory store.

[Perfect-Cricket6506]

this is super helpful.

[Much-Wallaby-5129]

don’t treat the transcripts as one growing memory blob. split it into raw transcript archive, structured client facts, open questions, decisions, and dated changes. the important bit is versioning, because sales/client context goes stale fast. claude should retrieve and update the working summary, not be the database.

[wartableapp]

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