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Coding agents that actually get better the more your team uses them. Introducing Hivemind: continual learning for AI coding agents. Hivemind turns the traces from every agent your team runs (Claude Code, Codex, Cursor, Hermes, OpenClaw, Pi) into reusable skills, then pushes those skills across all of them. All...

423,696 次观看 • 4 个月前 •via X (Twitter)

67 条评论

Davit 的头像
Davit4 个月前

Hivemind works better with teams. Earn $20 credit when you invite a friend to your org on Hivemind. They’ll get $15 worth of credit to capture traces to.

Davit 的头像
Davit4 个月前

Here is the source, please star it!

Chubby♨️ 的头像
Chubby♨️4 个月前

Really promising results! Love it

Davit 的头像
Davit4 个月前

thanks @kimmonismus for the support! very excited for this release!

Chubby♨️ 的头像
Chubby♨️4 个月前

You are welcome ! All the best

Jaymin Shah 的头像
Jaymin Shah4 个月前

Most teams are accumulating agent data. Very few are converting it into institutional knowledge. Hivemind bridges that gap 🚀 Congrats @DBuniatyan bro

Davit 的头像
Davit4 个月前

thanks bro! you can fine tune your own local LLM and cut 90%+ of Anthropic/OpenAI bill on the same traces.

Charly Wargnier ♨️ 的头像
Charly Wargnier ♨️4 个月前

Really cool build, and AFAIK, a pretty unique approach too. big thx to the team for keeping it open source :)

Davit 的头像
Davit4 个月前

🦾🦾🦾

shirish 的头像
shirish4 个月前

This is how you build real organizational intelligence in the agent era.

Tuki 的头像
Tuki4 个月前

This is the first time I've seen coding agents feel less like isolated tools and more like a shared learning system.

Davit 的头像
Davit4 个月前

@TukiFromKL would love to get your thoughts on how it works for you!

Shruti 的头像
Shruti4 个月前

This is really cool. Most developers don't get the results they want from agents. It's rarely the model issue. It's that the agent has no context for how your team actually works. What you've built here changes that.

Kamo 的头像
Kamo4 个月前

Great tool not only for fixing agents' amnesia but also for teams running multiple agents who can't share the knowledge. With SkillOpt and Knowledge graph, Hivemind will be every company's superintelligence in the near future.

Davit 的头像
Davit4 个月前

@KamoAghbalyan great job @KamoAghbalyan and @efenocchi1 leading the daily releases!

Alex Prompter 的头像
Alex Prompter4 个月前

This is probably the next big layer for dev teams using agents daily: shared memory, reusable skills, continuous improvement.

Michael Sutyak 的头像
Michael Sutyak4 个月前

The SkillOpt implementation really is a game changer.

Davit 的头像
Davit4 个月前

fully agree it has been already useful for us internally!

Adel Bucetta 的头像
Adel Bucetta4 个月前

the honest answer is that most teams still struggle to reuse code between these agents. hivemind might accelerate development, but it's also a symptom of the bigger issue: how do we turn the collective knowledge of our dev teams into something more than just a bunch of smart

Davit 的头像
Davit4 个月前

would take an effort to have swarm of intelligence working tightly together, but sharing insights in real-time is the first step!

K 的头像
K4 个月前

This makes agent performance compound over time

Davit 的头像
Davit4 个月前

not just single agent, but many agents

Peter Mick 的头像
Peter Mick4 个月前

AI is getting smarter and smarter hey? 🥰

Davit 的头像
Davit4 个月前

now its all about the harness

Jaynit Makwana 的头像
Jaynit Makwana4 个月前

The cross-agent aspect is what stands out here. Most workflows still keep knowledge trapped inside one tool.

Davit 的头像
Davit4 个月前

exactly, this makes your agents disposable. You can easily switch across different ones without loosing context.

Emanuele Fenocchi 的头像
Emanuele Fenocchi4 个月前

Finally, agents can stop having the memory of a goldfish every time you open a new session. Really curious to see how much SkillOpt and the knowledge graph can improve real day-to-day coding workflows

Davit 的头像
Davit4 个月前

very proud of you and @KamoAghbalyan on implementing the feature! great job guys!

Alvin 的头像
Alvin4 个月前

oh wow, this is actually crazy cool fam . so if my team uses Claude Code and Cursor side by side, they both get smarter over time from each other’s traces? might have to try this out. Starred the repo for sure

Davit 的头像
Davit4 个月前

exactly, for fun weekend projects, you can also turn of hivemind capture, to keep it private.

Prasenjit 的头像
Prasenjit4 个月前

one line install and it works across all agents, that's clean

Davit 的头像
Davit4 个月前

yep, you can customize which agent you want to include. Also exclude specific projects.

Shraddha Bharuka 的头像
Shraddha Bharuka4 个月前

The idea of agents learning from previous successful runs is really interesting.

Davit 的头像
Davit4 个月前

continual learning is going to unlock fire and forget agents!

AI Mastery Guide 的头像
AI Mastery Guide4 个月前

Agents that get smarter from your own team's usage is such a compounding advantage 🔥

Shubham Sharma | AI & Tech 的头像
Shubham Sharma | AI & Tech4 个月前

Really cool build, and AFAIK, a pretty unique approach too. big thx to the team for keeping it open source :)

Davit 的头像
Davit4 个月前

let us know how it goes for you

Shubham Sharma | AI & Tech 的头像
Shubham Sharma | AI & Tech4 个月前

Sure

Alex Veremeyenko 的头像
Alex Veremeyenko4 个月前

This is where coding agents get scary useful: not just executing tasks, but compounding team knowledge every time they run.

Gina Acosta 的头像
Gina Acosta4 个月前

The future is agents that learn from the whole team

Davit 的头像
Davit4 个月前

pluribus is the way to go!

Chidanand Tripathi 的头像
Chidanand Tripathi4 个月前

The cross-agent part is wild

Davit 的头像
Davit4 个月前

yep, no longer you are locked into a single agent.

Mr Das 的头像
Mr Das4 个月前

Finally, AI coding teams can learn continuously together. Hivemind’s skill sharing is brilliant and seamless!

Vipin Gautam (Viipin I Gautam) 的头像
Vipin Gautam (Viipin I Gautam)4 个月前

Most agents learn per task. Hivemind learns across tasks.

Davit 的头像
Davit4 个月前

thanks @viipin8 for support!

Vipin Gautam (Viipin I Gautam) 的头像
Vipin Gautam (Viipin I Gautam)4 个月前

Pleasure is all mine, Davit And, it is well deserved appreciation

Bit Space 🚀 的头像
Bit Space 🚀4 个月前

This is how coding agents start compounding real intelligence over time.

Andrew Yeung 的头像
Andrew Yeung4 个月前

!!!

Davit 的头像
Davit4 个月前

!!!

arc. 的头像
arc.4 个月前

definitely trying this one! congrats team

Davit 的头像
Davit4 个月前

@arceyul would love to hear how it goes for you!

Gregor 的头像
Gregor4 个月前

congrats on training it on my 3am debugging sessions

Davit 的头像
Davit4 个月前

😂😂😂

Ege 的头像
Ege4 个月前

Kinda love this idea and it would be interesting to test this on a real team

Davit 的头像
Davit4 个月前

it becomes increasingly useful especially for teams! would love to hear feedback.

Ege 的头像
Ege4 个月前

Gonna give it a spin and share some feedback

Adarsh Chetan 的头像
Adarsh Chetan4 个月前

Intelligence compounds when every solved problem becomes a reusable skill.

Davit 的头像
Davit4 个月前

every trace counts!

Callam 的头像
Callam4 个月前

how do you determine what should and shouldn’t be a skill? I built this as a POC at work and it became a full time job triaging what was actually useful + came with a bunch of PII concerns

Davit 的头像
Davit4 个月前

we took inspiration from SkillOpt. Would love you to give a try and share your experience!

Callam 的头像
Callam4 个月前

any free trials available

Davit 的头像
Davit4 个月前

yes! you get free $15 credit for cloud storage. You can also invite others and get top ups :)

Nelly; 的头像
Nelly;4 个月前

this is one of those posts that makes builders stop scrolling

Zenith_Ai 的头像
Zenith_Ai4 个月前

Nice share

Krishna Agrawal 的头像
Krishna Agrawal4 个月前

AI coding agents are evolving fast. The idea of turning every coding session into reusable team knowledge is a big step toward truly learning agents.

Davit 的头像
Davit4 个月前

every stored session is a treasure for you and your team. Let's store them safely and learn from it. would love to see how it works for you!

相关视频

I gave Claude Code, Codex, and Cursor a self-improving, shared MEMORY. Now my coding agents learn from each other, and their knowledge follows me wherever I work. Coding agents work in silos. Your corrections in Cursor don't carry over to Claude Code, and skills built in Codex don't automatically transfer to other harnesses. So switching tools often means starting from scratch. What if every coding agent could learn from everything you've already done? I invited Justin D'Souza, co-founder of Asymptote Labs, to show me how to make this possible with Beacon, a 100% open-source memory layer for coding agents. We set it up live, explored real coding sessions, and watched Beacon turn past work into reusable knowledge. Here's what I learned: 1. One memory layer for 20+ coding agents. Beacon captures activity across Claude Code, Cursor, Codex, and 20+ harnesses using OpenTelemetry, hooks, and local session files. Everything gets normalized into a single format, regardless of which agent you're using. 2. Your entire coding history becomes searchable. Every prompt, tool call, command, file change, and response is captured in a structured trace. Instead of losing valuable context when a session ends, you build a searchable history of everything your agents have done. 3. Switch agents without starting over. Hit your usage limit in Cursor? Open Claude Code and ask it to continue your latest Cursor session. Beacon retrieves the relevant context in milliseconds so your next agent can pick up where the last one left off. 4. Your agents learn from your past work. This is where things get interesting. Beacon identifies repeated workflows and turns them into reusable skills. In our demo, it discovered a recurring UI development workflow and generated a skill containing the exact dev server commands, screenshot steps, and deployment instructions. You teach one agent something once. Every other agent can benefit. 5. Stop accumulating skills nobody uses. Have 100 skills but only use five? Beacon analyzes actual usage across thousands of sessions and identifies skills worth keeping, combining, or removing. Your agent's memory gets more useful, not just bigger. 6. Security rules that follow you across every harness. Beacon includes hundreds of detection rules that work across agents. It can identify risky behavior, including sequences where an agent reads sensitive credentials and then makes an outbound network request. 7. It even caught a real credential leak. While reviewing Justin's actual Cursor history, Beacon surfaced an incident where part of a production database password had been sent to a model provider. That's the power of having visibility into what your agents are actually doing. 8. One prompt to get started. Completely open source. Paste a setup prompt into your coding agent and you're off. Keep everything local on your machine, or use Beacon Cloud for free. If you're juggling multiple coding agents, you need to check this out. Drop a like and share it with someone facing the same issue. Beacon on GitHub: (don't forget to star 🌟) Enjoy the episode. Cheers!

Akshay 🚀

51,663 次观看 • 8 天前