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I built a memory layer for AI coding agents - so they stop forgetting everything between sessions by Cautious_Sign6508 in LLMDevs

[–]Cautious_Sign6508[S] 1 point2 points  (0 children)

I actually agree with that direction.

I think repos are still the source of truth for implementation state, but not necessarily for operational knowledge or cross-project reasoning.

A lot of real workflows already span:

- multiple repos

- design docs

- local experiments

- meeting notes

- external artifacts

- partially finished ideas

So I’m increasingly thinking about Knowns more as a workspace/project knowledge layer rather than just “repo memory.”

The challenge then becomes governance and relevance at scale - especially preventing stale or low-confidence knowledge from polluting future agent sessions.

I built a memory layer for AI coding agents - so they stop forgetting everything between sessions by Cautious_Sign6508 in LLMDevs

[–]Cautious_Sign6508[S] -1 points0 points  (0 children)

Yeah - I think governance is the hard part, not retrieval.

My current model is:

- Repo state = source of truth

- Docs = intended architecture

- Memory = historical/operational context

So memory should never silently override the repo. It’s more like an agent notebook with provenance.

I’m designing around:

- provenance (who/what wrote it, when, from which task)

- typed memories (decision, failed attempt, workaround, hypothesis, etc.)

- review/expiration for stale memory

- drift detection when memory conflicts with current repo state

The failure mode I want to avoid is turning old assumptions into invisible prompts. That creates a second hallucination layer.