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- Hacker News
- How are you using this compared to more explicit approaches where you lay out the project documentation in certain formats and conventions?by hankbond
- 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 insteadby triyambakam
- 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 really integrates into one of the coding harnesses (Claude code or Codex mainly).
by mbreese - cool going to check it out, I've got an opensource project that might compliment it that I'm excited to try
- 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...by skeledrew
- by _ink_
- by techgnosis
- by vshulcz
- I had been building https://github.com/tenequm/pond for this exact purpose for a while, and it works like a charm in my case.
Give it a try, hope it will help you to solve your need without injecting anything in your context all the time.
by opwizardx - 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.by swordsith
- How does it compare to https://github.com/scaccogatto/okf-skills ?by rogeliodh
- 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?by calebkaiser
- This one was posted before?by iJohnDoe
- Why do you need an MCP server at all when the spec itself is so simple?by opwizardx
- Nice tool! If you want to publish your okf bundles for humans to read (like on a github pages or your intranet), i developped an open source solution to do that : https://github.com/oak-invest/kiso - It's like Hugo for OKFby straumat
- I like the idea.
To avoid losing context, I mainly conduct the planning session and the implementation session separately.
From the standpoint of building enterprise products, what worries me most is whether the agent we are implementing may not have understood a completely different context.
If okf_memory maintains domain knowledge very well, it is expected that implementation will be possible in unit functional units within a consistently smooth session.
However, there is a risk in applying this idea directly to practical work, so I’ll have to test it separately on a personal project.
by kimseungyong - 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?by langs
- Has anyone else benchmarked all these tools for precision/recall? I too want to know if agent memory is something I should add. I only do session memory for now and that is quite useful.by esafak