I’m CTO of a scale-up called Zappi and have switched the company from Ruby to Elixir, meaning all new backend services are now Elixir. I had nudged a few teams to try it over the last few years, and all those projects have been successful. But I had held off making it a requirement because Elixir has a ramp up time that can be hard to accept under the pressure of urgent delivery. But I think AI changes that.

The point of this post is to articulate a feeling of Elixir being at an inflection point in terms of business value, and LLMs are a big part of it. Here’s why:

• Syntactic quirks are much less of a problem when you’re pairing with an agent. Code readability is now much more important than knowing when to use keyword lists, maps or structs.
• Old ideological battlegrounds like Phoenix Contexts fade into the background because you can breeze past that. Again, readability trumps the issue of having to make hundreds of decisions (decision fatigue) that are more stylistic at the early stages.
• Claude is stupidly good at Elixir – arguably better than any other language (see Dashbit blog post).
• The type system, formatting and warnings (or just mix precommit) give good quality feedback to the LLM allowing an agent to quickly recover – this will just get better. But the type system isn’t a gargantuan puzzle like it is in Rust – a lovely balance between quick to create and quick to fail.
• I think (my gut) that the functional/immutable combo lends the LLMs to better default architecture (less slop).

Obviously, productivity in all languages is increased by Claude and friends. But I don’t think the benefits are equal. I think code writing fluency is now less important than code reading fluency (Ruby is quick to write, harder to read because of “where does this come from” etc). Go is verbose to read (to me), etc.

In the Dashbit blog post, José refers to “local reasoning” as a key hypothesis to how LLMs are able to create quality Elixir solutions. But the “local reasoning” argument applies to humans too, and I feel as the role of “judgement” becomes ever more important with AI, Elixir becomes ever more compelling.

Finally to the main point (and with apologies): I think the Elixir value prop has always been a bit hard for me to articulate to the average developer: what does “let it crash” mean to someone who hasn’t read details about OTP? Is it the best tool for ML or should we use Python? Liveview or React + REST?

But for me, the value proposition of Elixir is clear: Elixir is the productivity language of this new era. Choose it if you want to deliver fast and reliably.

Yes, there is resilience, concurrency, processes, types, Liveview, the BEAM, etc. Those are the common talking points (and real advantages), but I think there is an opportunity to reframe Elixir more simply in terms of productivity. It is a language in which a single engineer can deliver an extraordinary amount of value in an afternoon.

It is a productivity language for the Agentic era – easy for LLMs to write, easy for humans to read.

This is why I am now comfortable going all in on this language at Zappi. Optimising for productivity is a defensible no-brainer, and the productivity is real.

I hope this framing is useful to anyone considering Elixir!