Your Agent Framework Is Just a Bad Clone of Elixir
6 days ago
- #AI Agents
- #BEAM
- #Elixir
- José Valim highlights Elixir's high LLM code completion rate, citing a Tencent study where Elixir outperformed 20 languages.
- The actor model in Erlang (1986) aligns with modern AI agent models, offering solutions like isolated state and message passing.
- BEAM's lightweight processes (~2KB each) handle millions of concurrent connections, ideal for AI's long-lived sessions.
- Elixir's Phoenix framework supports 100,000+ WebSocket connections, making it suitable for AI agent chat sessions.
- Python AI frameworks (Langroid, LangGraph, CrewAI, AutoGen) are converging on BEAM/OTP concepts like message passing and supervision.
- BEAM's 'let it crash' philosophy simplifies error handling for non-deterministic AI systems via supervision trees.
- Hot code swapping in BEAM allows updates without downtime, crucial for live AI agent deployments.
- AI's shift to multi-agent systems mirrors telecom needs, making BEAM's decades-old solutions highly relevant.
- Elixir's ecosystem is filling gaps with tools like LangChain, Jido, and Tribunal for testing AI agents.
- Python and TypeScript lack runtime support for true concurrency, isolation, and fault tolerance compared to BEAM.