Prompting AI agents without a strict framework increases an individual's code output but leads to inconsistent standards. This makes code reviews a nightmare for teams, creating a collaborative bottleneck that cancels out the initial speed advantage.
To successfully steer autonomous coding agents, specifications must be exhaustive. They need to go beyond feature requirements to include service boundaries, data models, documented "gotchas" from legacy systems, and even operational and security requirements.
In an AI-assisted workflow, Spec-Driven Development (SDD) redefines the engineer's role. Instead of reviewing code implementation, teams focus on creating and approving detailed specifications as the primary collaborative artifact, leaving technical checks to specialized agents.