@evermind

Long-term agent memory | self-improving | agent harness https://xitter.cf/t.co/ZsoTOVW2sf https://xitter.cf/t.co/e0OVRxKsmF

United States
Joined November 2025
Meet EverOS Cloud. 💛 Your agent shouldn’t have to start from scratch every time a conversation ends. The preferences a user shared. The decisions made during a project. The approach that worked on a previous task. That context should be available when it matters again. EverOS Cloud gives your agents persistent memory through an API: • Remember users and retrieve relevant context across sessions • Turn task experience into Cases and reusable Skill memories • Bring conversations, images, and documents into your memory workflow You build the agent experience. We handle the memory infrastructure, so you can spend less time maintaining the stack and more time making your product useful. Subscribe to EverOS Cloud Pro and get 3× the standard Pro usage allowance for 6 months. Start here: everos.evermind.ai
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Agent Memory: An AI Companion That Reaches Out First You mention your coffee preference once. In a later conversation, she remembers. OpenHer shows how memory can make an AI companion feel more familiar over time. In this demo, Iris remembers “black, no sugar” and sends a morning message without waiting for you to start the conversation. EverOS provides the long-term memory behind those remembered details. OpenHer combines that history with its own personality and proactive messaging systems, so conversations can develop beyond the first introduction. OpenHer is one example of what you can build with EverOS. Bring persistent memory to your own application with EverOS Cloud. EverOS Pro users get 3X usage for 6 months. everos.evermind.ai
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Agent Memory: Your Team’s Experience, Put to Work Your agent can search the company handbook. Can it also remember what worked on the last support ticket? Consider a request: “Refund this customer and close the ticket.” Getting it right takes more than finding a document: User Memory captures working preferences: the support lead wants refunds over $500 flagged for review and a short summary afterward. Agent Memory brings back relevant experience from previous tasks. Recorded Cases can help inform the next run, while reusable Skills capture approaches that have worked repeatedly. The Knowledge Base provides the business reference: refund windows, approval limits, and account ownership. With EverOS Cloud, we’re bringing these together so teams can give agents relevant context before a task and save useful experience afterward, through APIs that fit into existing workflows. Start with one recurring task. Give your agent something to build on next time. Subscribe to EverOS Cloud Pro now and get 3× the standard monthly usage for your first 3 months. everos.evermind.ai
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EverMind retweeted
I tested @evermind’s EverOS Cloud by giving an AI agent something important to remember: a project decision. For my fictional SpendWise app, I saved: → PostgreSQL as the database → Infrastructure budget under $100/month → A managed database at ~$180/month rejected for exceeding the budget → Reconsider only if traffic or operational needs justify the cost Then I opened a fresh session and searched EverOS for that decision. It retrieved the saved episode and profile, and the next-step recommendation respected those constraints, without resending the original decision. That’s persistent memory in action: save context once, retrieve it later, and use it to inform the next task.
🤝 Paid partnership
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EverMind retweeted
EverOS Cloud × Claude Code 🧵 Claude Code built this living blueprint in Three.js: ink shaders on cyanotype paper, stage-by-stage GPU assembly, 17 vehicle kinds. EverOS Cloud turned what it learned into self-evolving skills that any agent, not just Claude Code, can recall.
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Agent Memory: A Real-World Use Case on Rokid AI Glasses Your next conversation with your AI glasses shouldn’t start from zero. A community builder has brought EverOS Cloud to @RokidGlobal glasses, giving a wearable assistant a memory that carries across conversations. As you use it, saved details and preferences can help it respond with more relevant context, without making you explain everything again. We love seeing our community bring long-term memory into everyday life, on devices you can actually wear. Build something of your own. Subscribe to EverOS Cloud Pro now and get 3× the standard monthly usage for your first 6 months. everos.evermind.ai
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EverMind retweeted
Every AI I use eventually forgets what I'm building. Chat gets too long, or I'm re-explaining the whole project from scratch Tried @EverMind's EverOS Cloud. Went through the docs and liked how it organizes context into profiles, episodes, and a Memory Bank. Built a small chat app on its APIs. Real use case: I'm building a student resume portal for my college. Students showcase skills and resumes, alumni search by skill, review profiles, and find people for referrals and collabs. Video shows the workflow and the Memory Bank 🚀 Tired of starting from zero? Check it out: everos.evermind.ai
🤝 Paid partnership
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Some guide. Some build. Some create. Some spread the word. Together, you keep our open-source projects moving forward. To our advisors, builders, creators, and evangelists. Thank you for being part of the EverMind Open-Source Ambassador community. Your time, ideas, and contributions mean a lot to us. 💛 @li9292 @Tz_2022 @xiqingongzi @hylarucoder @OipsAnthony @yinmin1987 @t20000622yy @Av1dlive
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EverOS open-source v1.4.2 is here. This release tackles problems that show up when memory servers keep running: • Fixed a file-descriptor leak in long-lived indexes • Separated query embeddings from background writes, so searches don’t queue behind ingestion • Fixed cross-project index overwrites, your Markdown memories were never affected Upgrade: pip install --upgrade everos Check the release notes before upgrading: Milvus and certain multi-project deployments require an index rebuild. Prefer managed memory infrastructure? Build with EverOS Cloud. evermind.ai/everos
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Your agent finished the task. What should it keep for next time? Not just the conversation, the approach that worked. EverOS captures task execution as Cases and consolidates recurring successful approaches into reusable Skill memories. Agents can retrieve those procedures when a similar task comes up. Memory for what happened. Skills for how to do it again. Build with EverOS Cloud. We handle the memory infrastructure, you focus on your agent. everos.evermind.ai
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Trying a new personal agent is exciting. Uploading the same documents and explaining your work all over again is less exciting. Over time, your agent picks up the small things: how you like things written, what your project is about, which decisions you’ve already made. Moving that context elsewhere takes work, and some of it gets lost along the way. With EverOS, we’re giving that context a place to grow across supported agents. Save your conversations, documents, and useful knowledge, then connect your agents to the same memory source. We recently shared how to connect EverOS to Muse. You can start building your own memory today and keep adding to it as your work evolves. Sign up for free: everos.evermind.ai
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In case you missed it: EverOS open-source v1.4.1 The 1.4 series brings native Windows support, faster memory retrieval, and more reliable indexing. The v1.4.1 patch fixes a dependency issue affecting fresh installs. Building an agent that needs to remember users, retrieve past context, and reuse lessons from previous tasks? EverOS Cloud provides managed memory through an API, with support for conversations, images, and documents. We handle the memory infrastructure so you can focus on your product. Start building for free: everos.evermind.ai/
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EverOS, meet @Muse 💛 Connect EverOS to Muse as a custom connector to save and retrieve context from your projects, past decisions, useful knowledge, and task outcomes. A personal agent, with another memory source to work from. Setup instructions, give this link to Muse: evermind.ai/connectors/muse.…
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Love seeing our open-source ambassadors help more developers get started with EverOS and long-term agent memory. Thanks for putting this walkthrough together, @yinmin1987 💛 Maybe Raven 🐦‍⬛ can lend a wing with the next video.
If you’re building agents and hate re-explaining yourself every session — try EverOS. Local Markdown memory, simple write→recall loop. I cut a 60s beginner walkthrough (Milvus shows up when you scale).
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First Daily. Then Weekly. Now Monthly. 💛 Raven 🐦‍⬛ reached #1 on @HuggingFace @HuggingPapers Daily and Weekly Papers, and now tops September’s Monthly Papers list. We’re building the “harness of harnesses”: coordinating specialist agents, preserving experience through EverOS memory, and turning that experience into reusable skills. Open-source code you can run, research you can examine, and a community helping us move forward. Thank you to everyone who read the paper, tried Raven, and supported the project. This means a lot to our team. github.com/EverMind-AI/raven
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Thank you for all the love for Raven 🐦‍⬛ v0.2.0, the harness of harnesses, built for RSI. 💛 We kept shipping through China’s National Day holiday, and v0.2.4 is already here. You can now ask Raven to inspect and update its own settings in chat, with approval controls and API keys kept out of the conversation. Plus: unified Connectors, clearer approvals, and workspace diffs. Huge thanks to the team and everyone building with Raven. github.com/EverMind-AI/Raven
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And we are live with another rendition of @MiniMax_AI intelligence in the open with @FireworksAI_HQ, @digitalocean, @radixark, @Modular and @evermind
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