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Every few months, someone in the AI or distributed systems space announces a new framework for running concurrent, stateful agents. It has isolated state. Message passing. A supervisor that restarts things when they fail. The BEAM languages communities watch, nod, and go back to work.
This keeps happening because process-based concurrency solves a genuinely hard problem, and the BEAM virtual machine has been solving it since 1986. Not as a library. Not as a pattern you adopt. As the runtime itself.
Thirty thousand people saw that and a lot of them felt it. The Python AI ecosystem is building agent frameworks that independently converge on the same architecture — isolated processes, message passing, supervision hierarchies, fault recovery. The patterns aren’t similar to OTP by coincidence. They’re similar because the problem demands this shape.
This post isn’t the hot take about why Erlang was right. It’s the guide underneath that take. We’ll start from first principles.
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