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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 просмотров • 4 месяцев назад •via X (Twitter)

Комментарии: 67

Фото профиля Davit
Davit4 месяцев назад

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.

Фото профиля Davit
Davit4 месяцев назад

Here is the source, please star it!

Фото профиля Chubby♨️
Chubby♨️4 месяцев назад

Really promising results! Love it

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Chubby♨️
Chubby♨️4 месяцев назад

You are welcome ! All the best

Фото профиля Jaymin Shah
Jaymin Shah4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Charly Wargnier ♨️
Charly Wargnier ♨️4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

🦾🦾🦾

Фото профиля shirish
shirish4 месяцев назад

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

Фото профиля Tuki
Tuki4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Shruti
Shruti4 месяцев назад

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.

Фото профиля Kamo
Kamo4 месяцев назад

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.

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Alex Prompter
Alex Prompter4 месяцев назад

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

Фото профиля Michael Sutyak
Michael Sutyak4 месяцев назад

The SkillOpt implementation really is a game changer.

Фото профиля Davit
Davit4 месяцев назад

fully agree it has been already useful for us internally!

Фото профиля Adel Bucetta
Adel Bucetta4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля K
K4 месяцев назад

This makes agent performance compound over time

Фото профиля Davit
Davit4 месяцев назад

not just single agent, but many agents

Фото профиля Peter Mick
Peter Mick4 месяцев назад

AI is getting smarter and smarter hey? 🥰

Фото профиля Davit
Davit4 месяцев назад

now its all about the harness

Фото профиля Jaynit Makwana
Jaynit Makwana4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Emanuele Fenocchi
Emanuele Fenocchi4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Alvin
Alvin4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Prasenjit
Prasenjit4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Shraddha Bharuka
Shraddha Bharuka4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

continual learning is going to unlock fire and forget agents!

Фото профиля AI Mastery Guide
AI Mastery Guide4 месяцев назад

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

Фото профиля Shubham Sharma | AI & Tech
Shubham Sharma | AI & Tech4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

let us know how it goes for you

Фото профиля Shubham Sharma | AI & Tech
Shubham Sharma | AI & Tech4 месяцев назад

Sure

Фото профиля Alex Veremeyenko
Alex Veremeyenko4 месяцев назад

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

Фото профиля Gina Acosta
Gina Acosta4 месяцев назад

The future is agents that learn from the whole team

Фото профиля Davit
Davit4 месяцев назад

pluribus is the way to go!

Фото профиля Chidanand Tripathi
Chidanand Tripathi4 месяцев назад

The cross-agent part is wild

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Mr Das
Mr Das4 месяцев назад

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

Фото профиля Vipin Gautam (Viipin I Gautam)
Vipin Gautam (Viipin I Gautam)4 месяцев назад

Most agents learn per task. Hivemind learns across tasks.

Фото профиля Davit
Davit4 месяцев назад

thanks @viipin8 for support!

Фото профиля Vipin Gautam (Viipin I Gautam)
Vipin Gautam (Viipin I Gautam)4 месяцев назад

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

Фото профиля Bit Space 🚀
Bit Space 🚀4 месяцев назад

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

Фото профиля Andrew Yeung
Andrew Yeung4 месяцев назад

!!!

Фото профиля Davit
Davit4 месяцев назад

!!!

Фото профиля arc.
arc.4 месяцев назад

definitely trying this one! congrats team

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Gregor
Gregor4 месяцев назад

congrats on training it on my 3am debugging sessions

Фото профиля Davit
Davit4 месяцев назад

😂😂😂

Фото профиля Ege
Ege4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Ege
Ege4 месяцев назад

Gonna give it a spin and share some feedback

Фото профиля Adarsh Chetan
Adarsh Chetan4 месяцев назад

Intelligence compounds when every solved problem becomes a reusable skill.

Фото профиля Davit
Davit4 месяцев назад

every trace counts!

Фото профиля Callam
Callam4 месяцев назад

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

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Callam
Callam4 месяцев назад

any free trials available

Фото профиля Davit
Davit4 месяцев назад

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

Фото профиля Nelly;
Nelly;4 месяцев назад

this is one of those posts that makes builders stop scrolling

Фото профиля Zenith_Ai
Zenith_Ai4 месяцев назад

Nice share

Фото профиля Krishna Agrawal
Krishna Agrawal4 месяцев назад

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.

Фото профиля Davit
Davit4 месяцев назад

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!

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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!

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