51–60 of 114 posts
I just had a thought about similar thing - how to track human decisions on the codebase? Consider you are writing code together with AI, how you understand which code change happened because human asked for it
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I still dont understand what "agentic memory" is . agents can already call sql / rag and grep through files or whatever. why is "agentic memory" a special thing.
Agents have to decide to search files, and they don't always know that they should. For example, if the agent sees the database, it may miss detailed instructions on how to access the database deeper in the repo. Behaviorally, humans want to be able to say "hey, here's how to access the DB. Remember that." Or better yet, for it to happen automatically. That's agentic memory.
Does anyone else not use memory? I find once there is one poisoned line of text it negatively affects everything else downstream. Instead, I use a temp/ folder with documents and use different files for different agents and models. Then I have to constantly prune and delete the files. Any information that can be extrapolated is just noise which negatively affects the agent. If you have a definition of a database stru…
My method is seven layers of files, administered differently: meta-knowledge, project seed, LLM wiki, code, tickets and todos, chat logs, artifactory. Ordered idea-to-reality. All git repos. That outgrows any context window pretty soon. My way out of that trap is to use links, both wiki links and git permalinks.
Does anyone else not use memory? I find once there is one poisoned line of text it negatively affects everything else downstream. Instead, I use a temp/ folder with documents and use different files for different agents and models. Then I have to constantly prune and delete the files. Any information that can be extrapolated is just noise which negatively affects the agent. If you have a definition of a database stru…
Your experience mirrors my own. I don't know if he coined the term, but Steve Yegge talks about 'heresies' that creep in to a system -- untrue things that stick around and permanently influence its behavior. I still find that these happen regularly and stopped using self-managing memory systems because they make heresies even harder to diagnose and remove. Within projects, I make heavy use of path-scoped rules to int…
You have to constantly tend the garden and weed these things out.
Whenever Claude makes some error ask it where and why? And then dig out the weed.
And of course if it’s in the context, probably time for a handover doc (which will need weeding) and started fresh.
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agents can call relational databases fine. infact, really good at sql if you can store your memories into that format.
that sounds horribly token inefficient, just create a tool call if you are all in on the agentic approach and hide memory retrieval behind an optimized api
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I still dont understand what "agentic memory" is . agents can already call sql / rag and grep through files or whatever. why is "agentic memory" a special thing.
Memory isn’t the same thing as rag it’s usually just a text based index of past events and the llm reads it and decides what’s important rather than querying a db
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Agents have to decide to search files, and they don't always know that they should. For example, if the agent sees the database, it may miss detailed instructions on how to access the database deeper in the repo. Behaviorally, humans want to be able to say "hey, here's how to access the DB. Remember that." Or better yet, for it to happen automatically. That's agentic memory.
yea ofcourse you have tell agent how to access you database. But why does it have a specail name, what the big deal about giving agent info how to call your db.
Now extend that to the rest of whatever system you’re working on. Do you want to manually have some preamble for every task you’re doing?
Even purely for convenience and dev experience it’s worth doing imo.