Vibe coding vs spec-driven development

Last updated: August 30, 2026

Vibe coding means prompting an AI agent conversationally and accepting what comes back; spec-driven development means writing requirements, designs, and a technical plan first, then having the agent build to them. Vibe coding wins for exploration and prototypes; spec-driven wins the moment the output has to be a specific feature in a real product. Most developers need both, for different tasks.

What vibe coding actually is

The term stuck because it's accurate: you describe roughly what you want, the agent generates something, you react to it, and the code emerges from the back-and-forth. No upfront design, no written requirements, just vibes and iteration. With agents as capable as Claude Code, this genuinely works: you can go from idea to running prototype in minutes.

Vibe coding is the right mode when:

• You're exploring. You don't know what you want yet, and the fastest way to find out is to see something wrong.
• The code is throwaway. Scripts, spikes, one-off migrations, demos.
• The blast radius is small. A single function, an isolated tweak, a bug with an obvious cause.

Where vibe coding breaks

A one-line prompt underspecifies a real feature by a factor of a hundred. Which screens exist, what happens on error, who can see what, how the data is modeled: every decision you didn't make gets made by the model, silently, using plausibility as its only guide. The failure mode isn't broken code; it's a working implementation of the wrong feature. You discover the gap in code review, or after shipping, and unwinding it costs far more than deciding upfront would have.

There's a second, quieter cost: vibe-coded features leave no artifacts. Six weeks later there's no record of what was decided or why, so the next feature that touches the same area starts from archaeology.

What spec-driven development changes

Spec-driven development front-loads the decisions: write the requirements, produce reviewable mockups, approve a technical plan, and then let the agent implement against those documents. The agent is just as fast; the difference is that it's building your decisions instead of its guesses. Code review changes from "is this what I meant?" to "does this match what I approved?", which is a much easier question.

The cost is real but small: minutes of deciding per feature, which is exactly the work you were going to do anyway, just moved earlier, where changing your mind is cheap.

How to choose, per task

A rule of thumb that holds up in practice:

• Will anyone depend on this code in a month? No: vibe code it. Yes: spec it.
• Can you describe "done" in one sentence without ambiguity? Yes: vibe code it. No: the ambiguity is the spec you haven't written.
• Would a wrong guess cost more than 30 minutes to unwind? Yes: spec it.

Note this isn't a maturity ladder where real engineers only ever spec. Over-specifying a throwaway script is as wasteful as vibe-coding a billing system is dangerous. The skill is matching the mode to the stakes.

Doing spec-driven without the friction

The usual objection is that writing specs is slow and scatters artifacts across Notion, Figma, and loose markdown. That's a tooling problem, not a methodology problem. Dedicated tools generate the artifacts with the same AI you build with: we compared the current options (GitHub Spec Kit, AWS Kiro, and others) in our spec-driven development tools roundup. BuildBoard, our entry in that list, runs the loop as four Claude Code commands with a kanban board and keeps every artifact as a local file, so the spec step costs minutes, not meetings.