What is spec-driven development? Why specs matter in the Claude Code and Codex era

What AI coding tools cannot tell you

Claude Code and OpenAI Codex can read a codebase, edit files, run commands, and help ship features from a prompt. The speed is real.

But after using these tools for a while, a pattern appears. AI agents are strong at the *how* of writing code. They still need to be told what to build, what to leave out, and where to stop. That is the job of a spec.

A prompt is an instruction, not a specification. Saying "build a login feature" will get you something. But which authentication method should it use? What should happen on failure? How does it relate to the existing user table? Without answers to those questions, the AI makes choices that may look reasonable but miss the team's intent.

Vibe coding works until it doesn't

Vibe coding means moving quickly with rough prompts and shaping the output as it appears. It is useful for prototypes and personal projects. It gets ideas off the whiteboard fast.

The problem is continuity.

• When the team reviews the output, there is no clear basis for judgment
• When someone adds a feature, no one remembers why the first version made its choices
• When the PoC moves closer to production, it becomes hard to separate intentional design from incidental implementation choices

Every vibe-coded PoC eventually needs a spec written after the fact. Starting with even a lightweight spec reduces that rework.

What spec-driven development means

Spec-driven development, or SDD, puts the specification before the implementation and uses that spec as the primary input to an AI agent. Spec Kit is one example of tooling built around this idea.

The spec does not need to be a heavy Word document or spreadsheet. A lightweight Markdown file is enough if it gives humans and AI agents the same assumptions. Three things matter most.

1. What you are building: scope and purpose
2. What you are not building: exclusions and the reasoning behind them
3. How decisions are made: errors, edge cases, and priorities

With those in place, Claude Code or Codex can implement with intent rather than assumption. Reviews also become easier because the question becomes concrete: does this match the spec?

The gap between meetings and specs

In many teams, specs do not get written for a simple reason. Turning meeting decisions into a usable document slows the momentum to start building.

AI meeting tools record conversations. But a record meant for reviewing a meeting is not the same as input for development. A readable summary is helpful, but it is not automatically a spec that Claude Code or Codex can act on.

v2p is designed to close that gap. From the decisions made in a meeting, it generates Markdown for specs, design notes, and tasks, plus prompts that can be used for mocks and PoCs. When the meeting ends, the starting point for the next AI development session already exists.

What changes when you have a spec

Passing a spec to Claude Code or Codex changes the work in practical ways.

• Better implementation quality: the AI guesses less and follows intent more closely
• Faster review: the team can ask whether the result matches the spec
• Easier handoff: another developer or AI session can continue with context
• Less rework: fewer "that's not what we meant" moments after the PoC

In AI-driven development, writing code is becoming less of a bottleneck. Clarifying the spec is becoming more important. Once the spec exists, implementation can move much faster. Without it, the human review cost keeps growing.

The takeaway

Spec-driven development is not bureaucracy for the AI era. It is the foundation that lets AI agents move quickly in the right direction.

You do not need heavy documentation. You need a lightweight Markdown file that captures what was decided and gives both humans and AI agents the same starting point.

Visit the service page to see how v2p turns meetings into input for AI development.