🔗 Why I moved from Python to Elixir for AI work, and what I found on the other side.

A few months ago, Alessandro Usseglio Viretta transitioned from Python to Elixir for his AI projects, citing frustration with Python's async/await model. He highlighted the challenges of orchestrating concurrent processes in Python, where bugs from incorrect event loop management can be subtle and hard to reproduce. In contrast, Elixir's design, built on the BEAM Erlang virtual machine, provides a more reliable structure for concurrent tasks without the pitfalls of event loops, allowing for seamless handling of long-running processes. Viretta's experience with his AI email-based ghostwriting agency, Aleik, illustrates the efficiency of Elixir in managing LLM calls, emphasizing that Elixir's immutable data structures and clean retry semantics make it an excellent choice for scaling AI systems. While Elixir may lack in some machine learning tooling compared to Python, its robust architecture suffices for that orchestration without the async complications.