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- Hacker News
- 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
- 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
- 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
- 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 - This one was posted before?by iJohnDoe
- 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 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