AI Doesn't Need Your Programming Language

Why the future of code is simpler than you think — and why that matters for everyone, not just non-English speakers.

The Question Nobody's Asking

Here's something odd about the current AI coding revolution: we're using AI to generate JavaScript, Python, TypeScript — languages that were designed for humans to write. But humans aren't writing the code any more. The AI is.

So why are we still optimising for human writability?

The answer, of course, is that humans still need to read the code — to verify it, debug it, and maintain it. But here's the thing: the languages we use make that harder than it needs to be. A hundred lines of React with hooks, closures, and async/await is not easy for a human to verify. It wasn't easy when a human wrote it. It's certainly not easy when an AI wrote it and you're trying to decide whether to trust it.

What if the AI wrote in something simpler?

The Case for Simpler Languages

This isn't about dumbing things down. It's about recognising that the economics of code have changed.

AI makes fewer mistakes in constrained grammars. Give an LLM a language with a small, consistent vocabulary and no syntactic ambiguity, and its error rate drops dramatically compared to JavaScript or Python. Fewer mistakes means less debugging, less rework, less cost.

AI uses fewer resources with simpler output. Generating 30 lines of readable script costs less in tokens than generating 200 lines of framework code that does the same thing. At scale, this is a real cost difference.

Humans can actually verify simple code. This is the critical point. The value of AI-generated code is zero if you can't tell whether it's correct. A non-specialist can look at:

on click SaveButton

begin

    put the content of NameField into Name

    rest post Name to `/api/save`

    set the content of Status to `Saved`

end

...and know exactly what it does. Try that with the equivalent React component.

Simple languages can be made fast. A high-level scripting language that compiles to WebAssembly or C would be indistinguishable in performance from today's mainstream languages for most applications. The simplicity is in the surface syntax, not the execution model.

Where This Is Heading

Let me make a prediction that might be uncomfortable:

Before long, most code will be written by AI and validated — if at all — by humans. The role of the human shifts from author to reviewer. And reviewers need readable code far more than authors do.

When that happens, the value proposition of complex languages changes. JavaScript's flexibility, Python's ecosystem depth, TypeScript's type system — these are advantages for human authors. For AI authors with human reviewers, they're liabilities. They increase the surface area for errors and make verification harder.

What you want instead is a lingua franca — something simple enough that AI rarely gets it wrong, readable enough that humans can verify it at a glance, and powerful enough to build real applications. The complex languages don't disappear, but they move to the edges: systems programming, performance-critical code, specialised domains. The broad middle — the apps, the tools, the dashboards, the automations — gets written in something more like natural language.

This isn't science fiction. It's already starting.

AllSpeak: A Working Example

— overview, primer, and AI manual

AllSpeak is named after the Asgardian ability to communicate in any language. It started as an English-only scripting language called EasyCoder. The multilingual architecture was added in April 2026 with AI assistance.