Prompt-Driven Development (PDD) is best described as an emerging methodology. It treats the prompt as first-class development artifacts, shaping how software is designed, built, and evolved in AI-assisted environments.
Prompts as Primary Artifacts
In PDD (Prompt-Driven Development), prompts replace ad-hoc instructions and scattered comments. They capture intent, constraints, and context in a structured, reusable form. Well-crafted prompts become the authoritative source that guides AI tools consistently across coding, testing, and documentation tasks.
Human Intent, AI Execution
PDD separates responsibility clearly. Humans define goals, rules, and quality expectations through prompts. AI systems execute implementation details. This division improves clarity, reduces rework, and allows developers to focus on architectural and business decisions rather than mechanical coding.
Iteration Through Prompt Refinement
Change management shifts from rewriting code to refining prompts. Adjusting wording, constraints, or examples incrementally steers outcomes. This enables rapid experimentation while maintaining control, traceability, and alignment with evolving requirements.
Pragmatic Bridge between SDD and Vibe Coding
Experimenting with GenAI-driven development highlights Prompt-Driven Development as a pragmatic bridge between Spec-Driven Development and Vibe Coding. It enables deliberate, detailed upfront thinking while delegating full execution to AI. From there, teams can either iterate conversationally or refine prompts and regenerate outcomes.
The real insight is that no single approach fits all cases: each project demands its own blend of methodologies, often achieved by decomposing larger initiatives into smaller, independently optimized efforts.
