Every AI conversation contains knowledge worth keeping, but most of it gets trapped in separate chats and tools. Living Brain captures that knowledge, connects it to what you already know, and turns it into a persistent memory that keeps evolving. Share that intelligence across AI models, apps, and agents through API, SDK, or MCP, so every new interaction builds on the last instead of starting over. Reuse memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
Hey Product Hunt 👋 I’m Christel, founder of ChatAndBuild, and I was part of Twitter's first international team.
We have built the Living Brain - a model independent, harness independent, efficient brain that travels with you across any AI platform.
Living Brain gives your AI tools a shared, persistent memory. It turns your notes, documents and conversations into connected knowledge that you can inspect, update and reuse across compatible assistants and agents.
For example, save a project brief, customer requirements and the decisions behind your roadmap in one brain.
Connect it to your AI tools, and they can retrieve that context when you ask them to work on the project.
With Living Brain, you can:
🧠 Build a memory around your work, projects and preferences. 🔗 Reuse that memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more 🛠️ Give your own apps and agents persistent context through our API. 📚 Review the organised knowledge and the sources behind it.
We’re measuring how accurately AI can use that memory, alongside how much context it needs.
Our latest internal evaluations show:
We're #1 on LoCoMo with 92.2% judged accuracy, answering 1,420/1,540 questions correctly with approximately 63.8% less context.
Those context reductions compare average retrieved memory with the displayed full-history references — approximately 9.4K versus 26K tokens on LoCoMo, and 5.1K versus 115K on LongMemEval-S.
We want you to choose each AI for what it does best, with your accumulated context coming along.
We’re building this for people who use several AI tools, teams whose context is scattered, and developers building agents that need continuity.
I’d love to hear from you. What’s the one thing you’re tired of explaining to AI over and over?
Tell us your workflow. I’d love to see where Living Brain could help, and where we still need to improve.
What stands out to me is the promise that memory can travel across tools without becoming an invisible pile of stale assumptions.
How do you decide what deserves to become durable memory rather than temporary context? And when someone’s priorities or preferences change, how does Living Brain surface and resolve contradictions instead of quietly carrying the old version forward?
I like that you can inspect why a memory was kept, with Freshness, Strain and Readiness indicators. In my own product, the hardest part of any memory is knowing when it has gone stale. How do you decide that a memory is deprecated: by age, by contradiction with newer input, or by the user's feedback?
interesting prodcut! can I use this across coding agents? I generally use cursor - how easy is integration?
congrats on the launch christel. to your question, which pages actually convert and which just get traffic. agents forget that every session -> if memory also kept why i rejected a draft last week that alone would help
Definitely interesting, would love to test it out, From where to try it?
Living Brain helps to solve a frustration that many of us know firsthand: having to repeat the same context every time we switch AI tools. For me, knowing that I can carry my notes, decisions and project context across compatible tools makes it easier to choose the right AI without starting from scratch, and this is exactly the advantage that Living Brain gives you!
You can create a Brain in ChatChat without code, or connect Living Brain to your apps through our API, MCP, SDK and CLI.
I’m excited to share what we’ve built and would love to hear how it helps you!
My current workflow is a lot of jumping b/w references, random ideas, feedback, and last-minute changes. Because of Living Brain, I can come back to an idea later w/o losing the thought process that made it click. I get to spend more time actually creating instead of retracing how I got there.
I like this. In my experience the built in AI memories keep the wrong things. They drags the reasoning into the output and forgets the one instruction I actually cared about. Can I see why something was kept or left out of a brain?
We built Living Brain because no one should feel stuck with one AI tool just because all of their context is there.
You should be free to try what is new, use what works best, and switch when you need to, without starting from scratch each time.
Your memory should be yours, and it should travel with you.
Being able to inspect the sources behind a memory matters as much as carrying it between tools. I'd want to trace an old decision back to its source and correct it once when the project changes.
A big part of being a creator is moving between tools. One moment I'm editing a video, the next I'm searching for assets, organizing references, writing scripts, or experimenting with a different AI tool.
But every tool holds a different piece of the process. Ideas get buried in chats, decisions get lost, and sometimes you spend more time rebuilding context than actually creating.
That's why I find Living Brain interesting. It's not about adding another tool to the workflow. It's about making the knowledge and context you've already built useful across the tools you work with.
Your tools should change as your work evolves. Your knowledge shouldn't have to start over.
Excited for what's ahead for Living Brain and @ChatAndBuild 🚀
Interoperable memory systems are becoming only more important in a world where AI models change every month. Having a Living Brain has completely changed how I use AI in my daily life. Now I don't have to reintroduce myself every time because my memory travels with me!
Been burned by memory tools that quietly inject stale context into new sessions. The health scores (Freshness, Strain, Readiness) are exactly what’s been missing. Love that you can see when memory goes stale. Proud to be a part of this team, we are here for more!
My favorite AI product at the moment!! As a student, I can confidently say that Living Brain helps to organize and store all the information needed for my academic achievements, and hence I have more space in my own brain for generating new ideas and learning new concepts🥳🤩
About Living Brain on Product Hunt
“Interoperable, efficient memory layer for agentic AI”
Living Brain launched on Product Hunt on November 5th, 2026 and earned 248 upvotes and 37 comments, earning #2 Product of the Day. Every AI conversation contains knowledge worth keeping, but most of it gets trapped in separate chats and tools. Living Brain captures that knowledge, connects it to what you already know, and turns it into a persistent memory that keeps evolving. Share that intelligence across AI models, apps, and agents through API, SDK, or MCP, so every new interaction builds on the last instead of starting over. Reuse memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
Living Brain was featured in Productivity (665k followers), Developer Tools (522.7k followers) and Artificial Intelligence (483.1k followers) on Product Hunt. Together, these topics include over 405.4k products, making this a competitive space to launch in.
Who hunted Living Brain?
Living Brain was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Living Brain stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hey Product Hunt 👋 I’m Christel, founder of ChatAndBuild, and I was part of Twitter's first international team.
We have built the Living Brain - a model independent, harness independent, efficient brain that travels with you across any AI platform.
Living Brain gives your AI tools a shared, persistent memory. It turns your notes, documents and conversations into connected knowledge that you can inspect, update and reuse across compatible assistants and agents.
For example, save a project brief, customer requirements and the decisions behind your roadmap in one brain.
Connect it to your AI tools, and they can retrieve that context when you ask them to work on the project.
With Living Brain, you can:
🧠 Build a memory around your work, projects and preferences.
🔗 Reuse that memory across ChatGPT, Claude, Gemini, OpenClaw, Hermes, Cursor, Codex and more
🛠️ Give your own apps and agents persistent context through our API.
📚 Review the organised knowledge and the sources behind it.
We’re measuring how accurately AI can use that memory, alongside how much context it needs.
Our latest internal evaluations show:
We're #1 on LoCoMo with 92.2% judged accuracy, answering 1,420/1,540 questions correctly with approximately 63.8% less context.
Those context reductions compare average retrieved memory with the displayed full-history references — approximately 9.4K versus 26K tokens on LoCoMo, and 5.1K versus 115K on LongMemEval-S.
We want you to choose each AI for what it does best, with your accumulated context coming along.
We’re building this for people who use several AI tools, teams whose context is scattered, and developers building agents that need continuity.
I’d love to hear from you. What’s the one thing you’re tired of explaining to AI over and over?
Tell us your workflow. I’d love to see where Living Brain could help, and where we still need to improve.
— Christel