I have been building with AI since the era of raw text completions, well before Copilot, stitching tools together with personal automation scripts. Those scripts were doing agent orchestration before the word existed. When OpenClaw took off at the start of 2026, I recognised that its open-source foundation already solved part of what I had been hand-rolling for years. I forked it and built a first-party orchestration layer on top so multiple agents could actually work with each other, initially just to help me run my own projects.
Friends saw the workspace and asked me to zip it up for them. Instead I packaged it as a CLI called TheHive and shared that. They liked it, but several of them were not technical, and a product-management collaborator I have worked with for years pushed me to turn it into a real commercial harness. TheHive became Hiveclaw.
The part I would show another engineer is the Fishbowl. Once agents are genuinely collaborating, you need to see what they are saying to each other, so I built them a Slack-like workspace of their own: agents open channels, message each other, keep their own tasks, Kanbans and documents, and hold meetings, modelled on how an actual enterprise team operates. You can watch a CTO agent brief a head-of-product agent in real time, read the documents they hand back and forth, and convene a meeting yourself to pull an agent in and have it present its work. It is closer to a Zoom call for agents than a chat log.
The effect, for me, is that I can hand an unfinished idea to Alfred, the beekeeper, and get a WhatsApp update while it is being researched or pushed forward. That is the real unlock. Not automation. Staying meaningfully involved in far more ideas than I have hours for.
I have been an automation nut since college, if a task repeats, I want it gone. Hiveclaw started as the thing that finally let me act on a notebook of ideas I had been carrying since the iPhone 3G and never had the hours to build.
At around 4am I was fixing a bug from the couch, pushed a change, and fell asleep waiting on the build. By 7am Alfred had sent a stack of WhatsApp alerts: the OpenAI credit was gone and tasks were failing. While testing I had switched on multi-provider fallback across OpenAI, Claude and Gemini without the spend guard I had intended to pair it with. Agents were opening channels and talking past each other, and when a token limit failed, the notification about the failure consumed more tokens. That loop fed itself. It ate a month of budget in about three hours. I cancelled a meeting that morning and rebuilt cost control properly: OpenClaw's heartbeat now runs through a custom LLM proxy that, when credits are exhausted, decides whether any real work is actually outstanding. Non-essential work no longer cascades to another provider; state is saved and the system waits. The lesson is the whole design principle now, spend limits and task state belong in the runtime, not in a hopeful audit script bolted on afterwards.
Live, and paid, with generous token allowances included. The next step is opening it up: letting people bring their own OpenAI or Anthropic credentials and run it themselves, and possibly relaunching the CLI so it can run locally.