We built two open-source memory tools for AI agents, both developed by @AtomicStrata
LLM-Wiki Compiler is your persistent knowledge base - Durable markdown compiled from your sources and built to compound over time.
Atomic Memory is your agent's persistent working memory - It only finds the specific facts that it needs, and you can directly correct its knowledge when needed.
Each remains valuable on its own, but even stronger together. Available at: https://t.co/08ryYr1jRP
Andrej Karpathy's pattern is to compile knowledge once and grow smarter for every query you make, which is what we built with LLM-Wiki Compiler.
We extended that idea to AI agent memory. Once you've fed information to your agent, it's tracked as claims with evidence and lineage. When something changes, only what needs to change gets revised. Nothing gets silently replaced without a record of what it used to believe.
The repo is open and we are actively building. Come contribute! ⬇️
https://t.co/8eM1UmdTal
We just open-sourced AtomicMemory.
The AI memory industry has a black-box problem.
AtomicMemory is a configurable open-source SDK + self-hosted Core engine for memory your AI can inspect, correct, swap, and run on your own infrastructure.
Apache 2.0. HTTP-first. Docker quickstart.
https://t.co/pSn52AL7zQ
Run a Smarter Memory Layer at
a Lower Cost for your AI Agents
Your agents inject their entire memory file into every prompt, whether it is relevant or not. Hermes native memory includes the full MEMORY.md every turn. OpenClaw carries full cross-channel context on every query. That is a fixed token cost you pay regardless of whether any of what it retrieves is useful.
Atomic Memory sits underneath both Hermes and OpenClaw and changes how memory gets injected. Retrieving only the facts the current query actually needs. Benchmarks show it does this at a lower cost per query than tools with comparable retrieval accuracy, which enables precise context injection without the token overhead.
This is @_HermesAgent backed by Atomic Memory in a real work setup.
Every decision, update, and correction your team makes gets organized and stays inspectable across sessions.
Atomic Memory improves your Hermes agent by replacing the 2.2KB native memory cap with unbounded, per-turn memory that resolves contradictions before anything hits storage.
The memory layer your team actually needs.
https://t.co/R73EedhENy
OmenX is live on @base.
You can trade what the world is watching:
sports, crypto, stocks, and global events
with leverage and built-in protection on @base.
For too long, event prediction felt like static bets.
We’re changing that with leveraged outcome trading, continuous markets, and exchange-grade infra.
Built for real traders.
We built AtomicMemory because agent memory has always been a black box you cannot check.
Inspectable, correctable, contradiction-safe memory for AI agents.
Here's everything we shipped and where to find it 🧵
The door is opening.
Blueprint claims are going live on @opensea
Claim details
• May 7
• 7PM GMT+8
• 2,222 passes
• Free to claim
👉 https://t.co/39ocsa5sxg
Ready for a 1v1 PVP match-up in our Beta Arena? 🎮
Elimination round. You lose, you’re out.
Win… and you take a shot at $2,000 USD.
Be among the first to step in and prove it.
xTOMO for everyone who joins.
Limited slots. Register before it’s too late 👇
https://t.co/nIjGyeiU2B