Agentmemory
Persistent memory for Claude Code, Codex & coding agents
555 followers
Persistent memory for Claude Code, Codex & coding agents
555 followers
You can now give Hermes, Claude Code, and Codex infinite memory. Agentmemory is trending on GitHub with 5,000+ Stars. CLAUDE md dumps 22,000+ tokens into context at 240 observations agentmemory: 1,900 tokens. same observations. 92% less. At 1,000 observations, 80% of your built-in memories become invisible. agentmemory keeps 100% searchable. benchmarked on 240 real coding sessions → Up to 95% fewer tokens per session → 200x more tool calls before hitting context limits → 100% open source
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Great to see the staleness question already in this thread — it's the one I'd stress-test hardest too. One angle worth adding: R@5/R@10 are recall-oriented, so a system can score beautifully and still be risky in a live codebase, because they don't penalise confidently surfacing a memory that was true last month and wrong after a refactor. The number to watch isn't "did we retrieve it" but "should this still be retrievable at all." Two things that help beyond a flat TTL: make a memory's strength a function of how recently it was reconfirmed rather than its age (a decision re-touched ten times should outlive one mentioned once, regardless of timestamp), and treat "superseded" as a first-class state the write path sets on contradiction, instead of hoping the agent notices at read time. Really nice work on the compression side — that's the part most memory layers get wrong.
Well done team! How do you detect when a stored memory contradicts current code state or is pruning still manual?
Persistent memory across sessions is one of those things that sounds like a dev tool problem but actually changes how useful AI agents are in practice. Right now every session with Claude Code starts from scratch — re-explaining context, re-loading preferences. Curious how Agentmemory handles conflicts when the same context gets updated across sessions. Does it merge, overwrite, or flag it for review?
@zrimko @rohit_ghumare I think the question is what does it do with contradicting facts ?
Blue is the best color, Red is the best color. How does it know which one to choose when asked to pick the best color (for your context) ?
@rohit_ghumare @cristian_dumitru1 haha yeah sorry for the confusion — cristian said it better than me. basically just wondering what happens when two saved preferences clash.
Congrats on the launch.
2 questions:
Will this impact more usage on tokens? since the agent need looking around and search on newer chats?
Will the memory be persistent only in CLI agents or also on their desktop application as Codex, Claude, Cursor
@rohit_ghumare that’s nice, what about 2#
Does it work only on CLIs?
92% token reduction is huge if it holds on real codebases. Curious how agentmemory handles conflicting observations: when newer context contradicts older stored memory, does recency win automatically or is there a manual override?
Cool project, how are you handling caching to ensure that it doesn't reprocess tokens unnecessarily in longer conversations?
Hey! Love it. How well would it help with handling pivots and knowing how my seed-stage startup's narrative/pitch deck and product spec changes over time? I've got canonical documents set up in Cursor, but it still takes a LOT of tidying work and any new scratch brainstorming files ruin the source of truth...