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The actor model that Erlang introduced in 1986 is essentially the agent model that AI frameworks are rediscovering in 2026. Python and TypeScript AI frameworks like LangGraph, CrewAI, AutoGen, and Langroid are independently converging on patterns—isolated state, message passing, supervision hierarchies, fault recovery—that the BEAM virtual machine has provided natively for decades. The post compares each framework's approach to OTP primitives, explains why BEAM's preemptive scheduling, per-process garbage collection, supervision trees, and hot code swapping are uniquely suited to long-running multi-agent workloads, and argues that Python/TypeScript can only approximate ~70% of these capabilities due to fundamental runtime limitations. The author also introduces Tribunal, an LLM evaluation framework for Elixir, and points to Jido and Elixir's LangChain as production-ready agentic tooling.

Your Agent Framework Is Just a Bad Clone of Elixir: Concurrency Lessons from Telecom to AI

A squad for Elixir developers to come together and discuss with each other, ask and answer questions about Elixir.
Do also checkout the other BEAM related squads for Gleam and Erlang!