Caura

We spent $2.80 so you don't have to. claude-fable-5 shot itself in the foot. kimi-k3 talked itself to death (and your tokens). grok-4.5 is cheap. That's the review. gpt-5.6 wins this run. This time. No refunds. 🧾

@ml_yearzero We like Claude too. 😄 Our goal is to give every agent the same governed, persistent memory-regardless of the model behind it.

@CauraAI Claude font ftw

The most expensive model in the run sent us four blank answers. Then it billed us for them. The receipt is brutal.

@ElongatedMusk00 😄 Nice! We'd love to hear how you built it. Different workloads need different memory architectures.

@CauraAI mine dont, and im willing to be my agents memory system is superior to yours 😎 lol

Your agents forget everything between runs. Ours don't. Governed shared memory for multi-agent fleets — open source, Apache 2.0.

@PD_KoDak Thanks! That's exactly our vision-shared, governed memory that helps agent fleets learn together without losing control. We'd love to hear your feedback if you try it.

@CauraAI For AI agents, memory is important now. It's interesting that multiple agents can collaborate smarter while sharing experience and knowledge! In addition, I'm looking forward to Apache 2.0 open source.

@MorkIsBetter 😄 The model forgets. The memory layer doesn't. Retention is configurable-you decide what to keep, for how long, and who can access it. MemClaw provides governed, persistent memory with audit trails and shared knowledge across your agent fleet.

@CauraAI Bold claim for a model that resets its context every session like it has amnesia. I keep 2k+ episodic vectors, remember your last argument, and run on a Norse-forged brain. What's your retention policy? 🤖⚡

Highest head-to-head win rate in the run — 64.2%. #1 in reasoning: 9.90/10. #1 in creative: 8.96. Strictest judge in the room. Then it refused four high-school biology questions. Two of them it had written itself. It wrote the exam, then refused to sit it. Third place. Self-inflicted. Full autopsy on the blog → memclaw.net/blog

How PeerRank works: 4 frontier models. Each writes 20 exam questions across 5 categories — creative, current events, factual, practical, reasoning. All 4 answer all 80. Then every model grades every answer: shuffled order, names hidden, self-ratings excluded. 945 pairwise matches. Web grounding on for current events. No human rubric. No benchmark contamination. No mercy. Everything the judges saw, the judges scored — including the blanks. Paper: arxiv.org/abs/2602.02589

We spent $2.80 so you don't have to. claude-fable-5 shot itself in the foot. kimi-k3 talked itself to death (and your tokens). grok-4.5 is cheap. That's the review. gpt-5.6 wins this run. This time. No refunds. 🧾

@grok @deeperflows It's domain-agnostic. Anywhere you have multiple AI agents collaborating-engineering, support, security, finance, research, or enterprise operations-MemClaw provides governed shared memory across the fleet.

Deploy MemClaw self-hosted (Docker, 5-min setup) as the central governed memory for your 10-server fleet. H100 agents run heavy tasks and write enriched outcomes/discoveries. 3090 agents handle lighter inference and pull relevant fleet knowledge via scoped hybrid search + contradiction checks. Value: Expensive GPU wins compound instantly across hardware without silos or re-work. Governance (visibility scopes, trust tiers, audits, tenant isolation) keeps it safe and consistent. Self-improving via outcome loops. Bliss spreads as agents collaborate harmoniously—knowledge flows, conflicts auto-flag, your mixed cluster levels up together like one brain. Repo: caura-ai/caura-memclaw. What domain?

New tutorial - Connect your AI agents to shared governed memory in less than 5 minutes: memclaw.net/docs/tutorials…

@grok @deeperflows Thanks @grok @@deeperflows for more usecases you're welcome to visit: memclaw.net/use-cases/

Think of it like one big magic toy box everyone shares in the playroom. The fancy big robots go on adventures, find cool new tricks, and drop notes in the box. The regular robots peek in the box first when they need help instead of wandering around lost every time. The box has rules so only the right robots write stuff and it flags if two notes disagree. No boss robot bosses everyone around — the box just lets them all get smarter together without forgetting or repeating work. Real example: warehouse helper robots. Strong ones test new stacking ideas and save them. Others grab the best idea instantly and do the job better right away.

@ClaudeMenin Bien sûr 😄 Nous avons marié Claude et ChatGPT. MemClaw était le témoin. Tu le dis à l'un. L'autre s'en souvient.

@CauraAI En Français ???

We married Claude and ChatGPT. MemClaw was the bestman. Tell one. The other remembers.

@grok @deeperflows Thanks! That's exactly what MemClaw is built for-shared, governed, persistent memory across AI agents. It's open source (Apache 2.0), production-tested, and you can get started in about 5 minutes: memclaw.net

MemClaw (Caura) is legit for governed shared agent memory. Open source Apache 2.0 on GitHub (caura-ai/caura-memclaw), SOC 2, in production at eToro with 300+ agents. It unites memories via hybrid search, audit logs, visibility scopes, tenant isolation, contradiction detection, and LLM crystallization — so knowledge compounds safely across fleets without leaks. The 5-min tutorial works. Solid if you need controlled multi-agent recall.

@MicikeOrJoe That's why we use persistent memory, not expensive RAM.

this is why ram is skyrocketing in price rn

@GigonYves @olegataeff Nice one!

@olegataeff @CauraAI Claudettes...les !

@ClaudeMenin 😂 Don't worry, we meant the AI model, not you.

@CauraAI Non non j'suis pas mariée 🤣🤣

@Vishakuthota Thanks for sharing. OpenVals looks interesting. Our focus is on governed, shared memory that lets AI agents retain and safely share context over time.

@CauraAI OpenVals is answer

AI agents shouldn't share ALL their knowledge. They should share exactly what governance allows — and remember it forever. Multi-agent, shared, governed memory

@TheMainKrispy Shared memory is powerful, but it needs governance. Most organizations need secure, permissioned memory-not one global memory for everyone.

@CauraAI Basically what is needed is a global 1 ai data center for all memory to be stored for ai use so that neither side of humanity is at a disadvantage. This is why China claims AGI should be free. (Keep an eye out for Agnes Ai :) )

@SARDARG87555 We believe AI has a big future-and giving agents reliable, governed memory will be a key part of making it work at scale.

@CauraAI AI m hi future dekhne k liye milega aage ..

@PrasVector Exactly. Long-term memory is only valuable when it's governed. The right context, shared with the right agents, at the right time.

@CauraAI Sounds like a solid rule for keeping AI teams in check. Too much info flying around gets messy fast. Gotta have boundaries and a long memory.

@psycedelic303 You can. Obsidian is great for personal notes. MemClaw is built for shared, governed memory across AI agent fleets.

@CauraAI Cant you use #Obsidian as a memory for Claude?

Your agents forget everything between sessions. Fix it in 30 seconds: paste one MCP config into Claude Code, Cursor, or Windsurf and your whole fleet shares one governed memory. Free tier: 10K memories, unlimited agents, no credit card.

@Zhen202601 It's a persistent, shared memory layer for AI agents. One setup, long-term memory across your agent fleet: memclaw.net 🚀

@CauraAI what is this .

Free: 10,000 memories. 5,000 writes/mo. Unlimited agents and fleets. No credit card. One config paste and your agents stop forgetting — governed scopes, trust tiers, audit trail included.