Why Learning Elixir (and programming) Still Matters in the AI Era

For a while now, it feels like nobody talks about programming languages anymore.

Everywhere you look, it’s AI agents, workflows, and tools that can write code almost instantly. The language underneath the code feels invisible almost irrelevant.

So it’s fair to ask:

Why learn a language like Elixir now?

Especially when AI can autocomplete functions, generate examples, and even explain errors.

What Confused Me When I First Met Elixir

Coming from a JavaScript background, diving into Elixir felt like stepping into a whole new world. It wasn’t just the syntax it was the way of thinking.

Concepts like immutability, pattern matching, and functional programming weren’t just unfamiliar; they actively challenged how I was used to writing code.

In JavaScript, I could change a variable whenever I wanted. In Elixir, that same idea felt almost wrong. I had to retrain my brain to think in terms of transforming data instead of changing state.

Functions became first-class citizens, recursion replaced loops, and I realized that side effects were something to be carefully managed, not ignored.

Even simple things like updating a map or handling a conditional made me pause and ask:

“Am I approaching this the Elixir way, or am I forcing JavaScript habits onto it?”

It was confusing. Sometimes frustrating. But it was also the kind of confusion that forces you to build better mental models for programming.

What Made Me Doubt Learning Elixir in the AI Era

What made me doubt learning Elixir wasn’t even Elixir itself it was programming languages in general.

With AI being able to write code, autocomplete logic, and suggest solutions, I started wondering if spending time learning a new language still made sense.

I kept asking myself:

Should I focus on learning a programming language, or should I focus on other things AI can’t easily replace?

From that mindset, learning Elixir felt risky. It’s not as mainstream as JavaScript, and it doesn’t dominate AI conversations.

But that doubt revealed something important.

The hard part wasn’t typing code it was understanding what the code is doing and why it’s structured that way.

AI could generate solutions, but it couldn’t give me intuition. It couldn’t replace the mental shift required to reason about state, failure, and concurrency.

What AI Doesn’t Fully Replace

When I tried to figure out what AI didn’t help me with while learning Elixir, I realized something uncomfortable I couldn’t point to a clear example yet.

Not because AI was doing everything, but because I was still early in the learning process.

AI could explain syntax, generate examples, and suggest solutions. What it couldn’t do was make things feel intuitive immediately.

I still had to sit with concepts like immutability and functional thinking until they slowly made sense.

That gap between seeing an answer and actually getting it is where learning still happens.

AI can shorten the distance, but it can’t skip it.

Learn the Right Way

If there’s one thing I’d tell someone unsure about learning a programming language today, it’s this:

Learn the right way. Learn the basics syntax, core concepts, and mental models then move on to implementation.

Don’t skip the foundation.

AI can fill in code snippets and autocomplete logic, but it can’t replace understanding. That understanding knowing why things work is what makes code reliable and systems easier to reason about.

Learning Elixir isn’t just about writing functions. It’s about training your brain to think clearly about data, state, and failure skills that will still matter no matter how advanced AI becomes.

I am still kinda new to the elixir space looking forward to writing more about elixir and my learning generally