OKF Agent Memory – Git-native persistent memory for AI coding agents • Hacker News Board

Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#21

Post by steammaho » Sun, Sep 06, 2026, 4:46 AM UTC

mbreese wrote: post #16

triyambakam wrote: post #6

How well does the model adhere to using this in a harness like Codex where it may be directed to use the built in memory tooling? Maybe I'll need to try an experiment directing it to save to its native memory to use OKF instead

This is usually my main concern with tooling like this that isn’t a first party project. Anthropic can tune Opus, Fable, etc and their harness to use their memory format or preferred method of tool calling. I have had mixed results getting LLMs to consistently use third party tools. I’m very much in favor of things like OKF wikis for memory or knowledge storage/retrieval. So I too would love to know how well this rea…

honestly didn't notice much degrading of standard compact. Have several sessions which already lasts for several month and they are perfectly fine

Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#22

Post by muhammadwaqar1 » Sun, Sep 06, 2026, 4:58 AM UTC

svyatov wrote: post #15

The performance is cool and all, but what about capture/retrieval quality? Are there any benchmarks for that?

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Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#23

Post by Abdullah_Sattar » Sun, Sep 06, 2026, 5:18 AM UTC

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Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#24

Post by skeledrew » Sun, Sep 06, 2026, 5:23 AM UTC

techgnosis wrote: post #9

skeledrew wrote: post #7

I want this, but also for cross-project memory. Save me from building my own, which I have planned but figure something would eventually pop up in HN...

https://github.com/huggingface/funes Maybe?

Not really. Could be a starter, but I specifically want everything to be stored as plain text and no vector search.

Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#25

Post by langs » Sun, Sep 06, 2026, 6:22 AM UTC

I don't get it. Why benchmark the latency instead of recall/precision? Optimizing for millisecond-level latency is meaningless in the context of LLM calls. Accuracy is the tool's greatest value, yet there is no testing for it?

Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#26

Post by ankitmathur01 » Sun, Sep 06, 2026, 7:25 AM UTC

calebkaiser wrote: post #5

Love seeing projects like this. The performance benchmarks are nice to see. Have you done any benchmarks against approaches like OpenAI's Symphony for things like token usage or task completion?

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Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#27

Post by swordsith » Sun, Sep 06, 2026, 7:46 AM UTC

Personally I've always seen AI 'memory' as a pain point for people in their experience using LLMs than a benefit from the agent remembering the last unrelated thing you were working on. It wastes context similarly to 'skills'. The most efficient workflow imo is having a few well written (not by ai) md files across a clean codebase.

Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#28

Post by sebastienburel » Sun, Sep 06, 2026, 10:12 AM UTC

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Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#29

Post by ahmedelsama » Sun, Sep 06, 2026, 2:16 PM UTC

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Re: OKF Agent Memory – Git-native persistent memory for AI coding agents

#30

Post by bayesianbot » Sun, Sep 06, 2026, 4:06 PM UTC

esafak wrote: post #18

pdimitar wrote: post #17

Earlier quoted context omitted.

Huh? Can you show source on the "it will not compact"? Very interesting.

"With Astra, we’re introducing a new way for Codex to preserve and retrieve context when the context window fills. Historically, models have used compaction to summarize work during long sessions, such as when debugging complex issues or tackling large refactors. Each compaction can leave out details about why a fix failed or how a component behaves. In Codex, Astra can keep notes across context windows, preserving a…

This clearly is Codex-specific, not as much a feature of the model (though obviously they probably have trained it to be great at working with their own tools). Sounds somewhat similar to pi-observational-memory I'm using with Pi.