Every failed project I've seen shares the same root cause: building started before the problem was understood. Not misunderstood — not yet understood. The difference matters.
The Specification Gap
Traditional development workflows treat specifications as a phase — something you "do" before coding. You gather requirements, write a document, get sign-off, and move on. The problem is that requirements evolve as understanding deepens. A static spec becomes stale the moment it's approved.
I've adopted a different approach: living specifications that evolve alongside the codebase. Every feature starts as a structured blueprint — not a requirements document, but an evolving contract between what we know and what we're building.
How AI Changes the Equation
Large language models are remarkably good at one thing most developers overlook: asking the right questions. When I draft a specification, I use AI as a sparring partner — not to write code, but to stress-test assumptions.
Here's the workflow:
- Problem statement — Define the problem in plain language. What's broken? What's missing? What does success look like?
- Constraint mapping — Identify technical, business, and timeline constraints before proposing solutions.
- Blueprint drafting — Create a structured spec covering data models, API contracts, user flows, and edge cases.
- AI review — Feed the blueprint through an AI review pass to surface ambiguities, missing edge cases, and implicit assumptions.
- Iterative refinement — Refine until every question has an answer or an explicit "we'll decide when we know more" marker.
Why This Produces Better Software
The biggest cost in software isn't writing code — it's writing the wrong code. Every hour spent refining a specification saves days of rework downstream. When the spec is clear, implementation becomes almost mechanical: translate the blueprint into code, test against the contract, deploy.
This approach has measurably reduced the feedback cycles on my recent projects. Clients see working software that matches their expectations on the first demo, not the third.
Getting Started
You don't need a complex toolchain to adopt spec-driven development. Start with a markdown file, a clear problem statement, and the discipline to not write code until you can answer: "What exactly are we building, and how will we know it's done?"
The AI component is optional but powerful. Even a simple prompt like "Review this specification and list any ambiguities or missing edge cases" can surface blind spots that would otherwise become bugs in production.