What is Spec-Driven AI?

Explained

Spec-driven AI connects requirements documents, policy YAML, and tool schemas to prompts, retrieval corpora, and eval suites. Changes flow from the spec so behavior stays traceable for governance and safer iteration than prompt-only tinkering.

Further reading

• AI Design Platforms: The Four Pillars of Autonomous Product Innovation
• AI-Native Application Development: A C-Suite Guide

Related terms

• API Interface that allows different systems to communicate; key for integrating AI models.
• Prompt Input text that guides a model's response.
• Retrieval Search phase that fetches relevant documents or passages for a query.
• Guardrails Runtime constraints and policies that keep LLM outputs safe and on-brand.
• Acceptance Criteria Testable conditions that define when a feature or model output is “done” and correct.
• AI Bill of Materials Inventory of model lineage, datasets, dependencies, and licenses for an AI system.