The Spec Is the Hard Part

Description

Stop pairing with your AI and start briefing it. I gave an agent a spec and walked away: 218 commits, 334 test files, zero reverts, and a finished project inside a week. It built the wrong thing exactly as often as my spec was vague, and never otherwise.

Most developers using AI coding tools are still writing code alongside the agent - guiding it, fixing its mistakes, re-prompting when it drifts. The autonomous loop pattern flips this: you write a specification, an AI plans the work, then implements, tests, and commits each task one at a time. Fresh context every iteration. Validation gates that enforce real test coverage. If it fails, it reverts and tries again. The human writes the what. The machine handles the how.

But this only works when the specs are good. Vague acceptance criteria produce vague code. Missing edge cases become missing tests. Ambiguous data models become implementation guesswork. The spec is where quality is won or lost, and most developers have never been taught to write one.

In this talk, I'll walk through real specs that worked and real specs that failed, and share the patterns that separate specs an AI can build from and specs that waste everyone's time. The talk builds one app live, four times, from four progressively better specs.