Why Elixir Is the Smartest Stack Choice at Every Stage of Your Startup

From MVP to Series A to millions of users - one stack, zero rewrites, infinite scaling.

I've spent over a decade building software products from scrappy MVPs shipped under impossible deadlines to large-scale systems serving millions of concurrent users. I've worked across various stacks, scaling different architectures and products, across industries, and across every stage of company growth. After watching the same patterns play out over and over, I now run an Elixir agency and that's not an accident. The stack you choose at the beginning determines what you can afford at every stage after, and Elixir is the rare technology that optimizes for all three: build fast, iterate faster, scale without compromises.

This time I wanted to highlight Elixir from a business perspective, and to help me do that, I invited Klaudia Bryl from Appunite to co-author this article. Klaudia has spent the last 8 years working in business development for technical companies. Over that time, she's had a front-row seat to how technology shapes and sometimes completely transforms businesses. She's met founders at every stage of the journey, from scrappy early-stage startups to companies navigating serious scale. She's heard the doubts about choosing Elixir, a relatively niche technology and the fears that come with that decision. But she's also seen what happens when that bet pays off.

Stage 1: MVP. Ship Faster With AI on Your Side

At the MVP stage, what matters is speed. How fast can you go from idea to something users can touch? This is where most founders default to Rails, Django, Next.js or other familiar tools with big ecosystems.

But the landscape has shifted. In 2026, most code will be written with AI assistance, and this changes the agenda entirely.

A recent study by Tencent evaluated AI code generation across 20 programming languages and 30+ models. Elixir had the highest completion rate of any language 97.5% of problems were solved by at least one model. Claude Opus 4 scored 80.3% on Elixir, compared to 74.9% for C# and 72.5% for Kotlin. José Valim wrote an excellent breakdown of why this is the case in his article Why Elixir is the best language for AI the reasons are structural: Elixir’s immutability makes code easier for AI to reason about locally, its documentation culture ensures high-quality training signal, and a decade of stability means there’s no confusion in the training data about what works and what doesn’t.

In practical terms, this means your AI-assisted development workflow, whether through Claude Code, Cursor, or Codex, produces more correct Elixir code on the first pass than nearly any other language.

For a seed-stage team of two or three engineers, that speed translates directly into success.

Even before AI changed how code gets written, Elixir was already giving early-stage teams a real edge when it came to moving fast and validating ideas. And here is real life story from Klaudia:

That's exactly what happened with Allegro Lokalnie — a platform launched by Allegro, one of Poland's biggest e-commerce players. Having already established a strong foothold in the B2C space, Allegro wanted to explore a new direction: a C2C marketplace that would make it easy for everyday people to buy and sell between themselves. Before committing fully, they needed to test the concept and validate their business assumptions quickly. Appunite's team recommended Elixir to build the MVP.

The reasoning was straightforward: Elixir was built with high-scale, high-traffic applications in mind, making it a natural fit for any product expected to handle a large number of concurrent users from day one.

Stage 2: Growth phase. Development Velocity and Efficiency When It Matters Most

You’ve found product-market fit. You’ve raised your round. Now the pressure shifts: ship features fast, hire without breaking things, and prove the business can scale.

This is where most early stack decisions start to hurt. The quick-and-dirty MVP codebase resists change. New hires take weeks to get productive. Every feature touches everything. Technical debt compounds silently until it's the dominant line item in your sprint.

Elixir is built for sustained velocity and that velocity has a direct impact on your headcount and burn rate.

A smaller team that delivers more. Elixir's tooling lets a single developer ship features that would require a frontend engineer, a backend engineer, and a DevOps engineer to coordinate an entire stack. In practice, 3-5 Elixir engineers consistently deliver what takes 10-15 on a typical JavaScript or Python stack. For a company watching its burn rate, that's the difference between 24 months of runway and 8.

Infrastructure that stays simple and cheap. Most growing startups accumulate costly third-party services as they scale: Redis for caching, Kafka for messaging, Sidekiq for background jobs, a separate server for real-time features. Elixir doesn't need any of them - its BEAM runtime provides all of this out of the box. Your infrastructure stays lean: a web server and a database. Fewer vendor contracts, lower cloud spend, and fewer things that break at 2 AM.

But what if you didn't start with Elixir? You chose a different stack early on, and now you're starting to feel its limitations. Elixir looks appealing, but the idea of a migration or a full rewrite feels daunting. That's a completely understandable concern; it's one of the most common things decision-makers bring up.

Here's the thing: with the right partner, a rewrite doesn't have to be a big-bang event. It can be done iteratively, in manageable pieces, without putting your product at risk. And as we've touched on earlier, a small, lean Elixir team can deliver what would take a much larger team in other technologies. If you want to dip a toe in before committing, a proof of concept or a limited pilot can be a low-risk way to see how Elixir fits your product's specific needs.

Here are some migration case studies worth studying:

Bleacher Report - Rewrote from Ruby on Rails to Phoenix. Reduced AWS instances from 150 to 5, which is probably the most dramatic infrastructure savings story in the Elixir ecosystem. They also reported being able to work with smaller teams and reduced complexity. Appunite article

Pinterest - Moved their notification system to Elixir. They reported a tenfold drop in codebase size from 10,000 lines to only 1,000 while also cutting server requirements by half. Elixir forum

Bet365 - Switched from Java to Erlang and Elixir, which allowed them to scale more easily and handle over 6 million HTTP requests and more than 500,000 database transactions per second. Elixir forum

Stage 3: Scaling. The Stack That Was Literally Designed for This

You've done the hard work. Your product is stable, your users are loyal, and you've got a growing list of ideas for what comes next. This is where Elixir's origins become your competitive advantage.

The BEAM virtual machine wasn’t built for web apps. It was built by Ericsson in the 1980s to run telecom switches systems that handle millions of concurrent connections, can’t go down, and need to be updated without stopping. The requirements were 99.999% uptime (five minutes of downtime per year) and the ability to hot-swap code in production.

That’s the runtime your Elixir app runs on.

The companies that have stress-tested this at extreme scale tell the story clearly. Discord handles over 150 million monthly active users on Elixir, with millions of concurrent WebSocket connections. They chose it specifically because the BEAM’s lightweight process model let them reduce server count while improving performance. WhatsApp, running on the BEAM via Erlang, served 2 billion users with a famously small engineering team at one point, roughly 50 engineers for the entire backend. Pinterest migrated their notification system to Elixir and reported a 10x reduction in codebase size while halving their server requirements.

These aren’t theoretical benchmarks. These are production systems handling real traffic at scales that break most stacks.

And the scaling is architectural, not just performant. The BEAM’s supervision trees mean your system self-heals when a process crashes, its supervisor restarts it automatically, without affecting the rest of the application. Distribution is built into the runtime, so clustering across nodes doesn’t require a service mesh or orchestration layer. You scale horizontally by adding nodes, and the BEAM handles the coordination.

One question founders and CTOs often raise is vendor lock-in a legitimate concern, but probably less of a problem than you think.

Elixir consistently ranks among developers' most loved languages, and Phoenix (its web framework) has repeatedly topped Stack Overflow's most loved frameworks list. The community is active, the documentation is thorough, and the language itself has a relatively gentle learning curve. There's a good chance your existing developers would actually enjoy picking it up and the strong ecosystem means they won't be left figuring things out on their own.

For a startup hitting growth inflection, this means you’re not scrambling to re-architect. You’re not migrating from a monolith to microservices under fire. You’re not hiring a platform team to manage the infrastructure your application team can’t handle anymore. You’re adding capacity to a system that was designed from the ground up to accept it.

Circling back to Klaudia’s Allegro Lokalnie example - today, it’s a profitable, Elixir-powered platform handling millions of visits a week and hundreds of thousands of active users a month. The whole thing is maintained by just a few developers. That kind of result doesn't happen by accident. The platform's former CTO has pointed to the decision to use Elixir as a pivotal one that allowed the team to achieve strong performance and scalability without bloating the team or the codebase. The architecture was flexible from day one, making it possible to pivot quickly and ship new features without the need for costly rewrites.

You can also take a look at our keynote with David at CyanView from Code BEAM Europe 2025 where we explained the entire company journey from the ground up and how Elixir was and is a great companion helping us to tackle remote camera control and shading complexity in the broadcast world. 

The Key Takes

Strip away the technology and look at the numbers:

AI-native development means faster iteration. When your AI tools produce correct code more often on the first pass, your effective engineering velocity increases without adding headcount. In a funding environment where capital efficiency matters, that’s leverage.

One stack from MVP to scale means zero rewrite costs. A typical startup rewrite runs 6-12 months and consumes most of the engineering team. At Series A burn rates, that’s €500K-€2M in opportunity cost features you didn’t ship, markets you didn’t enter, competitors you didn’t outpace.

Smaller teams mean lower burn. The BEAM’s concurrency model and Phoenix’s all-in-one approach let 3-5 engineers do the work that requires 10-15 on a conventional stack. WhatsApp proved this at the extreme end. Your startup proves it every sprint.

Less infrastructure means lower cloud bills. When Bleacher Report went from 150 AWS instances to 5, that wasn’t just an engineering win, it was a line item that dropped off the P&L. Your infrastructure scales sub-linearly with your user growth instead of exponentially.

We’ve watched too many startups burn runway rewriting systems or have issues with further scaling that should have been built right the first time. The stack you choose at the beginning isn’t just a technical decision; it's a financial one that compounds at every stage. Elixir is the rare choice that gets all three stages right.

We hope you discovered Elixir from different business perspectives and learned that Elixir is a proven and battle-tested stack for any stage of your startup or company! Thank you, Klaudia Bryl from Appunite, once more, for co-authoring and shedding some light on your real-life Elixir introduction case study!