February 19, 2026
Paging the 1980s: Erlang wants its crown back
Your Agent Framework Is Just a Bad Clone of Elixir
Grandpa’s phone tech crashes the AI party, and the comments are chaos
TLDR: An Elixir advocate says Erlang’s old design fits today’s AI agents, citing a study where AI code tools scored highest on Elixir. Comments erupt: Elixir vets cheer, Node fans push back, history buffs “actually” the claims, and many call agent frameworks bloated and unnecessary
Elixir diehards are having their victory lap after José Valim claimed the language is the secret sauce for AI “agents,” those chatbots that run long tasks and talk to other apps. A Tencent study even showed AI code tools performed best on Elixir problems, edging past C#. The author’s big flex: the decades‑old Erlang/Elixir world (running on the BEAM virtual machine) already solved today’s long, slow, many‑users‑at‑once problems—think telecom calls, WhatsApp, Discord. Cue the meme: “AI agents are just the actor model with better branding.”
Then the comments lit up. One camp cheered, calling Elixir a natural fit for long chats and crashes you can survive. Another camp fired back hard: mccoyb basically said the Node.js dunk “cannot be a real protest,” arguing the critique is overblown. The history cops arrived—bitwize went full “Ackshually…” to say Erlang didn’t invent the model in the first place. Skeptics like simianwords asked why we even need agent frameworks when smart models can already call tools, calling the stacks bloated (LangChain, we’re looking at you). Others, like randomtoast, backed the core idea but warned real‑world agents are mostly waiting on slow APIs anyway. Meanwhile, one heckler called Phoenix/LiveView “super bloated,” sparking a side feud over whether Elixir is lean magic or a chonk. BEAM me up, drama gods
Key Points
- •A Tencent-cited study reported Elixir achieved the highest LLM code completion accuracy among 20 languages; Claude Opus 4 scored 80.3% on Elixir tasks vs. 74.9% for C#.
- •The article argues Erlang’s actor-style concurrency (via the BEAM) aligns with modern AI agent patterns: isolated state, message passing, supervision, and fault recovery.
- •AI agent interactions create long-lived (5–30s), concurrent sessions that strain traditional short-request web frameworks like Rails, Django, and Laravel.
- •BEAM provides lightweight (~2KB) isolated processes, per-process garbage collection, preemptive scheduling (~4,000 reductions), and transparent distribution across nodes.
- •Phoenix (Elixir’s web framework) with Channels and LiveView is cited as handling 100,000+ concurrent WebSocket connections; BEAM powers systems like WhatsApp and Discord.