Why I'll never go back to vibe coding: A developer's case for spec-driven development

There's a moment every developer using AI coding tools knows well. You fire off a prompt, the model generates exactly what you need, and you think: this is the future. Then, twenty prompts later, the same model produces code that contradicts what it wrote an hour ago. You haven't changed. Your prompts haven't got worse. But something has broken down. For months, I relied on "vibe coding": describing what I wanted and iterating until it worked. This felt productive until I realised most of my time was spent course-correcting AI output instead of building.

On a greenfield project for a client, our team adopted spec-driven development (”SDD”) using the Breakthrough Method for Agile AI Driven Development (”BMAD”) method. Instead of jumping straight into code, we wrote detailed specifications upfront — user stories with acceptance criteria, architecture decisions documented before implementation. The same AI that struggled with vague prompts produced consistent, accurate code when given a structured spec.

The model hadn't improved. My input had.

This article covers that transition: what vibe coding actually costs you, what changes with spec-driven development, and the honest tradeoffs. For anything beyond throwaway scripts, SDD streamlines AI coding by reducing inconsistency and rework.

Open your IDE, describe what you want, iterate until it works. That's vibe coding — and it's how most developers start with AI tools.

It works brilliantly at first. Utility function? One prompt. Scaffold a component? Nailed. The feedback loop is immediate, and you feel like you're shipping at twice your normal speed. The problems creep in gradually. Around the twentieth prompt, the model starts suggesting patterns that conflict with its earlier recommendations. You re-explain your authentication approach for the third time. The AI imports a library you explicitly ruled out.

This is context collapse. Every model has a context window, and as it fills with conversation history, the model's recall degrades. You're not prompting worse — the context is getting noisier.

The insidious part: each correction feels minor in the moment. But across a feature, those micro-corrections compound into hours of rework. That's the hidden tax on vibe coding — you pay it slowly, so you never see the bill.

Spec-driven development inverts the workflow. Instead of describing what you want through conversation and hoping the AI maintains coherence, you write a detailed specification upfront — then hand the AI a focused, self-contained task.

The difference in output quality is immediate. Where vague prompts led to unreliable results, clear specs yielded consistent, accurate code. You've replaced a noisy conversation with a bounded context.

Our team uses BMAD, one of several SDD frameworks. In BMAD, requirements flow from a central Product Requirements Document (PRD) into epics, and then into user stories, with each layer including explicit acceptance criteria and technical constraints. Other tools, such as GitHub Spec Kit or Kiro, use a similar structure. Ultimately, what matters most is the rigor of writing specs before code, regardless of the chosen framework.

The insight I didn't expect: chunking matters more than comprehensiveness. Hand the AI a large spec, and you get verbose, meandering output. Break it into focused pieces — one story, one acceptance criterion — and quality improves dramatically. A 500-token focused spec leaves room for reasoning. A 3,000-token document recreates the noise problem in a different form.

The spec makes AI output predictable.

Spec-driven development has real costs, chiefly a longer feedback loop. Writing specs before coding takes time, but this investment up front reduces rework later.

The AI tends to be verbose. More context means more output. I've seen it generate sprawling code where something leaner would do. You learn to be explicit about constraints: "minimal implementation," "no abstractions beyond what's specified."

And sometimes SDD genuinely isn't worth it. Quick scripts, throwaway prototypes, one-off utilities — if you're building something you'll delete tomorrow, vibe code it. The overhead of a spec exceeds the rework you're avoiding.

SDD front-loads the thinking. With vibe coding, requirements emerge through rework; in SDD, they're defined upfront.

When you invest in SDD, projects with long-term maintenance or shared ownership benefit from predictable code quality, fewer errors, clearer team communication, and reduced rework throughout development.

You don't need a full framework to start. BMAD, Spec Kit, Kiro — these help at scale, but the core habit is simpler: write down what you want before you prompt.

A minimal spec isn't a formal document. It's a few lines that answer three questions: What is this thing supposed to do? What are the constraints? How will I know it's done?

For a single function, that might be five lines in a comment. For a feature, a short markdown file. The format matters less than the discipline of thinking before prompting.

Here's what I'd suggest for getting started:

Pick one small feature on your current project. Before opening your AI tool, spend ten minutes writing: a one-sentence description of what you're building, three to five acceptance criteria, and any technical constraints that matter (libraries to use, patterns to follow, things to avoid).

Then hand that to the AI instead of your usual conversational prompt. Compare the output quality.

That's the whole experiment. If it works, expand the practice. If you want more structure, explore BMAD or similar frameworks — they formalise what you've already started doing.

The shift isn't about adopting a methodology. It's about recognising that the spec is the product. The code is just the AI's implementation.

AI coding tools aren't going anywhere. They're getting better, faster, more capable. But the fundamental problem of context remains: the model only knows what you give it, and how you give it matters.

Vibe coding works until it doesn't. The speed is real, but so is the hidden rework. Spec-driven development trades immediate feedback for consistent output — and for anything beyond throwaway code, that trade is worth it.

I didn't adopt SDD because I wanted more process. I adopted it because I got tired of fighting the same context collapse on every project. Writing specs felt like overhead until I stopped spending hours untangling AI-generated inconsistencies.

The tools will keep evolving. Spec-driven development is how you stay in control.