Spec Driven Development — We’ve Been Doing It All Along
Spec Driven Development might sound like a formal methodology cooked up in a software engineering textbook, but honestly? If you’ve ever written a prompt to an AI agent and gotten something useful back, you’ve already been doing it.
What Is It, Really?
At its core, Spec Driven Development is the idea that you define what you want to build before you start building it. You write out the behavior, the expected inputs and outputs, the edge cases — all of it — and then you let the implementation follow from that spec.
In traditional development, this might mean writing an OpenAPI schema before touching any backend code, or defining your component interfaces before wiring up state. But in the age of AI-assisted development, the spec often looks a lot like a well-crafted prompt.
Vibecoding and the Art of the Good Prompt
This is where it gets interesting. Spec Driven Development is, in my opinion, a core part of what people mean when they talk about “vibecoding.” The connection is simple: a good prompt produces a good result. A vague, half-baked idea handed to an AI agent will get you a vague, half-baked result. But if you take the time to think through what you actually want — the structure, the behaviour, the constraints — the output quality goes up dramatically.
I’ve experienced this firsthand working with Claude Code. The more precise and deliberate I am about describing what I want, the more useful what comes back actually is. It’s not magic — it’s specification.
The Iterative Loop You Didn’t Know You Were In
Here’s something I find genuinely exciting about the way spec-driven development plays out with AI agents: you don’t need to have your spec perfectly figured out from the start. You just need a relative idea of what you want to create.
From there, AI agents enable a kind of rapid iteration that changes the whole dynamic of prototyping. Whether you’d even call it a traditional iterative process is debatable — it moves fast enough that you can produce multiple working versions in the time it used to take to get one off the ground. You try something, it’s not quite right, you refine the spec slightly, and you try again. The feedback loop is tight in a way it simply wasn’t before.
Why I’m a Fan
What I love most about Spec Driven Development — especially when combined with AI tooling — is the creative freedom it unlocks. Traditionally, the time cost of building a prototype acted as a filter on your ideas. You’d self-censor before even starting, because you knew how long it would take to find out whether something worked.
That constraint is largely gone now. Producing a working prototype is fast enough that you can afford to explore. You can follow a hunch, test it, and discard it without it costing you a sprint. That shifts the bottleneck from implementation back to ideas, which is where it should be.
Spec Driven Development gives structure to that creative process — not to limit it, but to make it actionable. And when AI agents are in the loop, that structure becomes the language you use to direct them effectively.
We’ve been doing it all along. Now we’re just getting better at it.