Agents

Stars measure interest, not usage. After a year of MindRoom, with forks of a Matrix client, two Matrix servers and a Matrix web client, plus 126 workarounds for one AI framework, my rule is: depend on what millions of projects use every day, roll your own when a library only gives you the easy part, and fork when the problem is hard and few people use the code.

For years, a Docker container was a good enough box to run code in, because getting out of one usually needed a hard-to-find bug in the Linux kernel. Now AI models are good at finding those bugs, and AI agents write the code running inside the containers. This post explains what the kernel does, how containers use it to fake a separate computer, why that is a problem now, and how six lines of code let MindRoom give its agents a stronger wall.

MindRoom grew one small group at a time at IonQ, until a company-wide demo made hundreds of people sign up in a day. What surprised me is that the heaviest users include engineers who already live in their coding agents.