SDD vs Vibe Coding: Why Specs Make AI Development Scale
"Vibe Coding" — describing features informally to AI — creates technical debt at scale. The bottleneck has shifted from writing code to validating whether AI-generated code is correct.
AI tools are getting better at writing code every month. The remaining problem: verifying that what they write matches what you actually want.
The Core Difference
Without SDD: idea → describe in chat → AI writes code → (hope it's right)
With SDD: idea → spec → approve → AI implements → validate → done
The difference is not about AI capability. It is about the clarity of the contract between you and your AI agent.
What Vibe Coding Gets Right
Vibe Coding is genuinely good for some things:
- Rapid prototyping — exploring an idea quickly, before committing to a design
- Small, isolated tasks — "add a console.log here" or "fix this typo"
- Learning — understanding a codebase or technique without production stakes
For these cases, informal descriptions work fine. The AI is smart enough to fill the gaps.
Where Vibe Coding Breaks Down
At production scale, informal descriptions create compounding problems:
1. No shared understanding. The spec lives in someone's head or scattered across chat logs. When the original developer leaves, the intent is lost.
2. No verification. How do you know it is done? You re-describe and hope the AI implemented what you meant, not what you said.
3. No traceability. When something breaks, which chat message caused it? Which session changed the behavior?
4. Drift. The AI's implementation diverges from the original intent over time, and no one notices until something breaks in production.
How SDD Solves All Four
Planu's Spec Driven Development workflow addresses each problem directly:
| Problem | SDD Solution |
|---|---|
| No shared understanding | Spec is a written contract, approved by both developer and AI |
| No verification |
validate tool checks implementation against the spec |
| No traceability | Every change is linked to a spec ID |
| Drift | Drift detection compares current code against the approved spec |
The Competitive Landscape
| Approach | Has Spec | Has Validation | Has Traceability |
|---|---|---|---|
| Vibe Coding | No | No | No |
| Kiro (AWS) | Yes | Partial | Partial |
| Planu | Yes | Yes | Yes |
Kiro targets AWS and enterprise teams. Planu is language-agnostic, tool-agnostic, and works entirely locally — no cloud required.
Planu is Not Anti-AI
This is worth being explicit about: Planu does not slow down AI development. It makes AI development reliable.
The spec takes two minutes to write and approve. The validation step takes seconds. What you get in return is confidence — the kind that lets you ship AI-generated code to production without a manual code review.
"You have already accepted that AI can write code. Planu ensures it writes the right code — by giving your AI a precise blueprint to follow instead of a vague chat description."
Getting Started
If you are already using Claude Code, Cursor, Windsurf, or any MCP-compatible AI tool, adding Planu takes one command:
npx @planu/cli install
Then describe a feature to your AI. Instead of writing code immediately, it will create a spec first. You approve it. It implements. You validate. Done.
That is the entire workflow. No configuration, no overhead, no new tools to learn.
Planu — Spec Driven Development for AI coding agents. Get started
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