Beehive – An open source IFTTT powered by Go's templating engine

In plain words

Beehive is an open source automation tool that lets developers create if-this-then-that workflows using Go's templating engine. It enables users to connect different services and automate tasks by setting up conditional triggers and actions. Built with Go, Beehive is designed for developers who want to build custom automation logic without relying on proprietary platforms. The project is available on GitHub for anyone to download, modify, and extend.

written from the facts on this page · September 2026

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  Beehive – Multi-Workspace Agent OrchestratorFeb 2026 · storozhenko98.github.io · ▲47

  hey hn, i built beehive for myself mostly. it has gotten to the point where my work consists in supervising oc or cc labor at tasks for multiple issues in parallel. my set up used to be zellij with a couple tabs, each tab working in a separate dir and it was a pain to manage all that. i know i could use git worktrees but they're kind of complicated, if you don't know how to use them it is easy to mess up, and i just prefer letting agents run in separate dirs with their own .git and not risk it. while i like zellij and use it inside beehive, i dont like the tabs and i forget where i am half…

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  Beehive – Talk 1:1 About Anything2021 · askbeehive.com · ▲11
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  Go-Bt: Minimalist Behavior Trees for GoApr 2026 · github.com · ▲62

  Hey HN, I just published v0.1.0 of go-bt and would love some feedback from the Go veterans here. Thanks in advance!

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  Open sourcing our ERP (Sold $500k contracts, 7k stars)Feb 2026 · github.com · ▲32

  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…

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