Belgium-based software developer and technology founder Bernard Lambeau has created a new programming language called Elo, and he did it with a non‑human partner at his side: Anthropic's Claude Code.

Instead of treating AI as a disposable code generator, Lambeau leaned on Claude Code in a sustained "pair programming" mode. Elo is not just a project that happens to use AI here and there; it is a language whose design and implementation were developed with an AI programming assistant continuously in the loop.

For teams exploring how to integrate AI into serious engineering work, Elo provides a concrete, named example of what AI‑assisted language creation can look like.

What actually happened

From the available information, a few key facts stand out:

  • Bernard Lambeau is a Belgium‑based software developer and founder of several technology companies.
  • He created a new programming language named Elo.
  • Throughout the development of Elo, he used Anthropic's Claude Code as an AI programming assistant.
  • The workflow was explicitly framed as "pair programming" rather than sporadic prompting.

That combination matters. Elo is not just another language announcement; it is an instance of a professional developer treating an AI coding assistant as a standing collaborator on a foundational tool.

Why this is different from casual AI code use

Most developer exposure to AI assistants so far has been tactical: ask for a snippet, refactor a function, generate boilerplate. Elo, by contrast, anchors AI directly in the language‑creation loop.

While the underlying technical details of Elo are not described here, the process signal is clear: the AI was present not only to help write code, but to accompany a human expert as they made structural and architectural choices about a new language.

For engineering organizations, that suggests a shift in where AI might add value:

  • Earlier in the lifecycle: from implementation back into design and experimentation.
  • Deeper in the stack: not just app‑level code, but core tools, languages and platforms.
  • Closer to expert workflows: used by a founder and experienced developer, not only by juniors trying to move faster.

Elo is therefore less important as a specific technology, and more important as a visible case study of a new way of working.

A cautious read: what we do not know yet

The Elo story also has clear limits. The available information tells us:

  • Who: Bernard Lambeau, a developer and founder.
  • What: a programming language named Elo.
  • How: developed with Claude Code as an AI pair programmer.

It does not tell us:

  • How mature Elo is, or whether it is used in production systems.
  • How responsibility was divided between Lambeau and Claude Code in practice.
  • How Elo compares to existing languages in performance, safety or expressiveness.
  • Whether other developers have adopted it, or whether it remains primarily a personal or experimental project.

Those gaps mean Elo should not be read as proof that AI‑designed languages are superior, safer or faster to build. Instead, it is best interpreted as an early, well‑named example that this kind of workflow is moving from theory into practice.

Why it matters for practitioners

Even with those caveats, Elo's origin story has several practical implications.

  1. AI pair programming is expanding its scope. If AI assistants can meaningfully contribute across the life of a language project, they can almost certainly help teams design internal domain‑specific languages, meta‑programming tools, or custom frameworks.

  2. Expert developers are adopting AI in core work. Lambeau is described as both a software developer and founder of several technology companies. His choice to work in pair programming mode with Claude Code suggests that AI is being pulled into serious, foundational work by people who could build without it.

  3. Process innovation may be as important as technical innovation. The key novelty here is not simply "a new language exists" but "a new language was built with AI as a standing collaborator." For organizations, that hints at a competitive angle: teams that learn to structure effective AI pair programming workflows may explore more designs, faster.

  4. Evaluation practices will need to catch up. When AI helps shape something as foundational as a language, teams will need clearer practices for review, validation and ownership. Elo flags the need for those practices but does not yet answer them.

What to watch next

Elo itself might remain a niche experiment or grow into an actively used tool. Either way, it points to several signals worth tracking:

  • Community formation around Elo. Does the language gain contributors, documentation and real‑world projects, or does it remain primarily a personal artifact of the Lambeau‑Claude collaboration?
  • More AI‑credited languages and tools. Elo is notable because the role of Claude Code is acknowledged. Watch for future languages, frameworks or compilers that explicitly credit AI pair programmers in their origin stories.
  • Patterns and guardrails for AI‑assisted design. As more teams pull AI into design‑level work, best practices around review, testing and risk management will become essential, especially when the output is a language other developers may depend on.
  • Shifting expectations for developer skills. If AI pair programming becomes normal for designing core tools, developers may be expected not just to "use" AI, but to orchestrate it effectively: framing problems, critiquing suggestions and integrating AI‑generated ideas into coherent systems.

Elo, and the way it was built, is worth following not because it guarantees a new mainstream language, but because it captures a turning point. A named, experienced developer has used an AI programming assistant in pair programming mode to create an entire language. Regardless of Elo's eventual popularity, that workflow is likely to become increasingly common as AI coding tools mature and developers grow more comfortable inviting them into the heart of their craft.