Spec Driven Development: What It Fixes (and Breaks)
Spec Driven Development: What It Fixes (and Breaks) AI coding agents are great, but they have a knack for drifting. Left alone, they reinterpret vague prompts, quietly expand scope, and ship code that technically works but nobody actually asked for. Spec driven development is the attempt to fix that by making the specification, not the prompt, the source of truth the agent has to work from. It…
Spec-driven development aims to prevent AI coding agents from misinterpreting vague prompts and creating code that doesn't meet the intended requirements. It does this by making the specification, not the prompt, the source of truth for the agent. The seven-phase workflow consists of constitution, specify, clarify, plan, tasks, implement, and analyze, each with a human review gate to prevent the agent from running off with a bad interpretation.
The specification phase focuses on writing detailed requirements that can be unambiguously tested, often using EARS notation for clarity. The plan phase breaks down the specification into a sequence of work tasks, while the implement phase has the agent write the code. The final analyze phase checks the output against the specification before it is shipped.
While the tooling landscape includes GitHub Spec Kit, AWS Kiro, and manual processes, the effectiveness of spec-driven development depends on applying the appropriate level of ceremony to tasks based on their risk level. Overly detailed specifications for trivial changes or skipping review gates can turn the process into unnecessary paperwork rather than a safety net.
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