Spec-Driven Development promises reliable, specification-led software generation, but in practice I found the workflow slow, heavy, and less effective than iterative prompting. This post walks through a real-world test using Spec Kit and explains why traditional AI-assisted development still outpaces SDD by a wide margin.

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Spec-Driven Development (SDD) proposes using detailed specifications as the source of truth for AI agents to generate code. Testing this approach with Spec Kit on a real feature rebuild revealed significant drawbacks: excessive markdown generation (2,500+ lines), long agent execution times (33+ minutes), and 3.5 hours of review overhead. Traditional iterative prompting proved 10x faster, completing the same work in 8 minutes of agent time with minimal review. The workflow felt like a return to waterfall methodology, producing duplicative documentation without improving code quality or reducing bugs. While SDD presents interesting ideas worth discussing, the practical implementation through Spec Kit doesn't capitalize on AI's strength of making code cheap and fast to produce.

Putting Spec Kit Through Its Paces: Radical Idea or Reinvented Waterfall?

It didn’t result in better code or fewer bugs

Are agents better at writing markdown or code?

<p>I agree, I think that the code should be a source truth, every direction should from the source code.</p>
