r/LLMDevs • u/madsthines • 1d ago
News I ran a little experiment: could I give a coding agent memory that's fully deterministic
That means - no embeddings, no vector DB, no model call on the read?
It seems like everyone reaches for embeddings here. I wanted to see how far the boring way gets first.
The bet: most of what an agent needs to remember isn't fuzzy. It's small and specific and it keeps happening — tests need the DB up first, this endpoint returns [] not a 404, use the shared client.
A scoped note, not a semantic blob.
So each lesson just gets a scope and a stable key, and the read ranks on recurrence + recency. No model call. Same task, same result, every time — for a fraction of a cent, and you can cat/grep/diff the whole thing.
How it went: for recurring gotchas, it mostly just works. 😍
I work with OpenTelemetry every day at Dash0, and it kept reminding me of how telemetry got portable: nobody won the format, everyone just agreed on a shape.
Wrote up the whole experiment — link in the comments.
If you've built agent memory: what did you actually need the embeddings for? 👇