Activeloop (@activeloop) / X

Activeloop

1,448 posts

Activeloop

@activeloop

Make Intelligence Compound. Infrastructure for Continual Learning

Mountain View, CA

Joined April 2020

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Activeloop
@activeloop
Apr 13
One session ends → poof. Everything important disappears. A teammate cracks a brutal prod issue → it dies in their terminal forever. Next week you’re debugging the exact same damn problem for the third time. We were so done with it. So we built Hivemind. A shared memory
Davit
@DBuniatyan
Apr 13
Article
When Claude session ends, everything important disappears. Finally fixed the agent amnesia problem.
TLDR: I gave my Claude Code, Codex & OpenClaw agents a shared brain. Now they never forget a fix, a decision, or a hard-won trace again. You know that sick feeling as an engineer. You (or your...
Activeloop
@activeloop
Jul 31
Building a truly continual learning is hard. Deciding where to store the learning is not yet figured out. Is it cn the context, updating weights, or learning cartridges? What signal it should supervise the learning from? How do you learn from your own traces? There many more
Davit
@DBuniatyan
Jul 31
Can AI learn from its own traces? To build a true continual learning system, I had to answer the following questions. - What is in the agent traces? - Where should model store the learning? - Which it should supervise from? - How do you learn from failed experience? - Which
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Activeloop
@activeloop
Jul 28
Hivemind is now on WhatsApp. Ask it what your agents are doing: “Can you check the status of my agents?” “What did the team work on last week?” • See agent activity and outputs • Switch between organizations • Get team recaps All from one WhatsApp chat.
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Activeloop
@activeloop
Jul 23
Every eng team working with agents now has the same problem: documentation is outdated the moment it's written. So we made it self-updating. Hivemind already turns your coding agents' traces into skills. Now that same pipeline maintains your docs. As your agents learn, your
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Activeloop
@activeloop
Jul 21
We talked to hundreds of engineers at AGI Summit this weekend. We started to notice some patterns around issues. The same frustrations came up over and over: • “We are trying to reel in our engineer spend and API cost on tokens” • “We’re seeing the same bugs come up
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