Open sourcing our ERP (Sold $500k contracts, 7k stars)
We recently open-sourced Hive after using it internally to support real production workflows tied to contracts totaling over $500k. Instead of manually wiring workflows or building brittle automations, Hive is designed to let developers define a goal in natural language and generate an initial agent that can execute real tasks. Today, Hive supports goal-driven agent generation, multi-agent coordination, and production-oriented execution with observability and guardrails. We are actively building toward a system that can capture failure context, evolve agent logic, and continuously improve…
In plain words
Hive is an open-source ERP system that generates AI agents from natural language descriptions of business goals. Developers can define workflows without manual wiring, and the system coordinates multiple agents to execute real production tasks with built-in observability and safety guardrails. It's designed for teams needing autonomous agents to handle business workflows at scale, with plans to add self-improving capabilities that learn from execution failures.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
We recently open-sourced Hive after using it internally to support real production workflows tied to contracts totaling over $500k. Instead of manually wiring workflows or building brittle automations, Hive is designed to let developers define a goal in natural language and generate an initial agent that can execute real tasks. Today, Hive supports goal-driven agent generation, multi-agent coordination, and production-oriented execution with observability and guardrails. We are actively building toward a system that can capture failure context, evolve agent logic, and continuously improve workflows over time - that self-improving loop is still under development. Hive is intended for teams that want: - Autonomous agents running real business workflows - Multi-agent coordination - A foundation that can evolve through execution data We currently have nearly 100 contributors across engineering, tooling, docs, and integrations. A huge portion of the framework’s capabilities - from CI improvements to agent templates - came directly from community pull requests and issue discussions. We want to highlight and thank everyone who has contributed. Specifically out top 11 contributors @vakrahul @Samir-atra @VasuBansal7576 @Aarav-shukla07 @Amdev-5 @Hundao @Antiarin @AadiSharma49 @Emart29 @srinuk9570 @levxn
Does the same job
all alternatives →
Warp Open-SourceMay 2026 · github.com · ▲226Agentic development environment built with the community
AI Hive May 2026 · app.aihive.global · ▲53Build, deploy, and run all your AI agents in one platform.
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
