How We Work: the Studio's AI-Driven Process

We often get asked: "do you really write code with neural networks?" We do. And that's exactly why our process is stricter than a classic studio's, not looser. When code is generated in minutes, the only thing separating a product from a landfill is the discipline around the generation. Here's how ours is built.

The Spec Leads

Every piece of work starts with a document, not with code. We write down what we're building: behaviour, boundaries, done criteria, an explicit list of what we won't do. The spec is reviewed by the client and by our agents — yes, agents too: they're excellent at finding contradictions and asking uncomfortable questions while an edit costs a minute, not a week.

This isn't bureaucracy, it's economics. Code became cheap — what stayed expensive is the decision of what exactly to build. A mistake in that decision, multiplied by generation speed, turns into a mountain of working "wrong thing". The spec is the cheapest way to catch it early.

Agents Execute

Generation runs as a pipeline: tasks are cut from the spec, each driven by an agent in a short loop — plan, code, self-check. Several tasks run in parallel; what takes a classic team a sprint often fits into a day here.

But speed isn't the main thing agents give. The main thing is reproducibility. An agent doesn't get tired, doesn't "forget what we agreed", doesn't do worse work on Friday than on Tuesday. With the process set up right, quality stops depending on the performer's mood — for the first time in the history of the craft.

A Human Is Accountable

Not a single line reaches the client without human review. The engineer isn't checking "is it prettily written" — agents do that better than us — but holds what a machine can't yet be trusted with: architectural decisions, module boundaries, risks and edges that didn't make it into the spec.

The engineer's role here has shifted from "writing" to "designing and accepting". It's the same evolution we preach in our teaching: an architect and reviewer instead of a code typist.

Quality as a Gate

"Works" is proven here, not asserted. Every behaviour from the spec is covered by a test; the test run, linters and validation are an automatic boom gate no task passes around. A red test isn't a nuisance — it's a bug caught before production.

That's why "fast with neural networks" and "reliable" don't contradict each other here: generation provides the speed, and the gates — which neither human nor agent can bypass — provide the reliability.

What This Means for the Client

Transparency: the spec reads in half an hour, and everything that will be built is visible in it. Speed: the first working scenarios in the first days, not "we'll show you in two months". Predictability: changes go through the same cycle — spec, generation, gates — so the budget doesn't creep with every "could we also".

This is what development looks like when AI is the backbone of the process, not a fashionable label. We build our clients' products this way — and teach engineers and vibe-coders the same craft in our course.