Why spec-driven development is the missing piece for AI coding

The pattern we see everywhere

Most teams that try coding agents get stuck at the same place: the agent produces something plausible, the developer half-reviews it, and the codebase slowly fills with code no-one fully understands.

The teams that break through do one thing differently: they write specs.

What a good spec looks like

A good spec answers three questions before the agent writes a line of code:

• What exactly should this change do, in terms a reviewer can verify?
• How should it fit into the existing code - which files, which patterns, which conventions?
• What must not change - the invariants, the public API, the tests that must still pass.

Why this works

With a spec, the agent has something to be right or wrong against. Reviews get sharper. Regressions get caught. And the developer stays in the loop as the architect, not the typist.