Your Agent Framework Is Just a Bad Clone of Elixir (georgeguimaraes.com)

José Valim recently highlighted Elixir as the optimal programming language for AI, referencing a Tencent study that found Elixir had the best code completion rate for large language models (LLMs), surpassing languages like C#. He argues that the actor model established by Erlang in 1986 is essential for modern AI frameworks, as it provides the necessary architecture for handling the asynchronous, long-lived connections typical of AI agents, which traditional web frameworks struggle with. The BEAM virtual machine, designed for managing millions of concurrent calls, offers built-in features such as lightweight processes, message passing, fault tolerance, and hot code swapping, which are crucial for the unique demands of AI workloads. As the AI community increasingly relies on frameworks that mimic the actor model, the advantages of using Elixir become apparent. While many Python-based frameworks attempt to replicate these features, they often lack the efficiency and robustness that BEAM inherently provides, such as preemptive scheduling and isolated state management. This architectural foundation allows AI agents to operate more reliably under unpredictable conditions without the extensive defensive coding typically required in Python. Valim’s insights suggest that adopting Elixir for AI development isn't just a trendy choice but a strategic decision rooted in practical, proven infrastructure tailored for the complexities of AI applications in real-time environments.