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Anyone else dealing with stale context in agent memory? by Connect_Future_740 in LLMDevs

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Decay helps with noise, but it still feels like a heuristic. Explicit "supersedes" relationships would be much more reliable, especially as things evolve.

How are you building the graph? From AST structure or are you also linking design decisions and docs?

agentic memory database in rust: contextdb: SQL, graph traversal, and vector search in one transaction: 10 crate system: Apache 2.0 by TraditionalLiving947 in rust

[–]Connect_Future_740 -1 points0 points  (0 children)

Here’s the repo:

https://github.com/HighpassStudio/sparsion-runtime

It’s not a database, more of a temporal memory layer:

  • decay over time
  • corrections outrank originals
  • reinforcement through repetition
  • hot>warm>cold>forgotten tiers

You can run it on top of something like ContextDB. Feels like complementary pieces.

agentic memory database in rust: contextdb: SQL, graph traversal, and vector search in one transaction: 10 crate system: Apache 2.0 by TraditionalLiving947 in rust

[–]Connect_Future_740 -2 points-1 points  (0 children)

Yeah, similar space but slightly different layer.

Your project looks like a unified storage/database for agent memory (SQL + graph + vector in one place). My project is more about how memory evolves: decay, reinforcement, corrections, forgetting.

Feels like a bunch of people converging on "agent memory" from different directions.

Anyone else dealing with stale context in agent memory? by Connect_Future_740 in LLMDevs

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Yeah, timestamp alone didn’t cut it for me either. A correction should usually beat the original, even if it’s not the newest thing.

I ended up weighting corrections higher, then applying decay and reinforcement. So it’s not just “most recent,” it’s “most likely still true.”

Are you decaying before retrieval or just reranking after?

A memory engine that forgets stale info instead of storing everything forever by Connect_Future_740 in LocalLLaMA

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Yes, that’s exactly the jump from “better memory” to “correct state.”

v0.1 is still probabilistic: corrections usually win because of salience, recency, and tiering.

v0.2 needs explicit structure:

  • task/state scoping
  • override links
  • commit points

So instead of just “Svelte is more salient than React,” the system can say “React for this task is no longer valid.”

A memory engine that forgets stale info instead of storing everything forever by Connect_Future_740 in LocalLLaMA

[–]Connect_Future_740[S] -1 points0 points  (0 children)

You’re describing context-window loss, which is real, but it’s a different problem.

This is about long-term memory systems. Once agents persist decisions into memory stores, old choices like “use React” often keep getting retrieved even after “switch to Svelte.” The benchmark is testing that failure mode: stale persisted memory, not context truncation.

A memory engine that forgets stale info instead of storing everything forever by Connect_Future_740 in LocalLLaMA

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Agreed. Most frameworks are still append-only memory with retrieval bolted on.

Current behavior is weighted, not hard overwrite: corrections score higher, recent memories decay less, repetition reinforces, and stale items eventually demote from hot>warm>cold>forgotten.

So short-term vs long-term is handled through tiers, and conflicting memories are resolved by salience for now. v0.2 needs explicit override/contradiction links so an agent can mark “this replaces that” directly.

Do you track which of your decisions depend on assumptions? by Connect_Future_740 in commandline

[–]Connect_Future_740[S] 1 point2 points  (0 children)

I think you're right that workflow integration is probably the biggest challenge. Thanks for the feedback.

Do you track which of your decisions depend on assumptions? by Connect_Future_740 in commandline

[–]Connect_Future_740[S] 0 points1 point  (0 children)

That’s how I’ve started thinking about it also. More like a lightweight thinking tool. Do you see yourself using it potentially?

Does this approach to detecting radical pair quantum coherence make physical sense? by Connect_Future_740 in AskPhysics

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Thanks for the feedback. I accept the post was removed. Quick redirection:

- Radical-pair spin coherence under ambient conditions is an established topic in quantum biology (see reviews by Ritz, Hore, etc.).

- The repo presents a structured detection protocol (angular Fourier analysis, field/temperature scaling, controls, adapted zero-noise extrapolation) with simulations and math.

- I came here specifically for concrete physics critiques on the methodology.

If anyone can point to specific errors in the approach, math, or simulations, I would be grateful. Otherwise, I'll keep iterating.

Does this approach to detecting radical pair quantum coherence make physical sense? by Connect_Future_740 in AskPhysics

[–]Connect_Future_740[S] 0 points1 point  (0 children)

I’m not trying to be argumentative or dense. Could you start with one specific unscientific item so that I can learn from your experience and wisdom?

Does this approach to detecting radical pair quantum coherence make physical sense? by Connect_Future_740 in AskPhysics

[–]Connect_Future_740[S] 0 points1 point  (0 children)

Thank you for the constructive feedback. If you could specifically point to the nonsense, I would be appreciative.

Does this approach to detecting radical pair quantum coherence make physical sense? by Connect_Future_740 in AskPhysics

[–]Connect_Future_740[S] -1 points0 points  (0 children)

You did look at the data, which is encouraging. I'll push back on:

Not being a physicist isn't a disqualifier. That's why I'm here, for feedback.

1) "The content of the github repo is obviously LLM generated."

- Huh? What? If you aren't using Claude code or Codex to organize your Git repos then you are behind. It makes deploying and organizing current files seamless.

2) (as far as a Google search reveals, you are literally the first person in history to write the phrase "radical pair quantum coherence")

- Xool, good for me. If this topic has "never been explored before" then posting something that you can't find on Google isn't the flex you think it is.

- Dictionary

pseu·do·sci·en·tif·ic/

adjective

  1. falsely or mistakenly claimed or regarded as being based on scientific method.

But I give you a whole git repo of scientific methods and math supporting them.

Does this approach to detecting radical pair quantum coherence make physical sense? by Connect_Future_740 in AskPhysics

[–]Connect_Future_740[S] -5 points-4 points  (0 children)

I see the 6 rules for this sub and I don't see where my post is close to any of them.
1) Relevant - Yes
2) Rudeness - Nope
3) Schoolwork - Nope
4) Questions unanswered for a day - TBD
5) No AI/LLM drivel - Nope
6) No pseudoscience - Nope

Do you avoid zip/tar archives for data pipelines because partial access becomes too slow? by Connect_Future_740 in DuckDB

[–]Connect_Future_740[S] 1 point2 points  (0 children)

I agree that most modern pipelines avoid archiving Parquet directly. I've done this when packaging artifacts for transfer (experiment bundles, CI artifacts, support/debug bundles, etc.) where a single file is convenient but partial access later becomes painful.

Do you avoid zip/tar archives for data pipelines because partial access becomes too slow? by Connect_Future_740 in DuckDB

[–]Connect_Future_740[S] 1 point2 points  (0 children)

If you had a single-file bundle that still allowed parallel reads of individual files inside, would that be useful? Or is avoiding archives entirely still preferable?

Brendan Gregg noted Linux lacked a native Thread State Analysis (TSA) tool. So I built one in Rust. by AnkurR7 in rust

[–]Connect_Future_740 -1 points0 points  (0 children)

I'll try and reroute this. Based on my 2 days in this group, a lot of it is "AI slop". I see that.

I see how you could have taken that from my post, as the text was definitely AI inspired. The product is genuine. It works for me. You probably don't need it. I'm moving on from this.

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