Generative AI is artificial intelligence that produces new content such as text, images, audio, video, code, or interface structures in response to input and context.
Traditional software often follows explicitly programmed rules. Generative AI can produce a new response from a prompt and context: draft a PRD, generate an interface, write code, summarize research, or create an image.
The system produces output by modeling patterns learned during training and information available at runtime.
Generative AI describes the ability to create outputs. An AI agent can additionally plan, use tools, inspect results, and take multiple steps toward a goal.
A generic model can generate a plausible settings page, but without product context it may ignore existing navigation, terminology, permissions, components, or business rules.
That gap is why professional workflows increasingly combine generation with retrieval, product memory, design systems, and validation.
Generated output can look confident while containing factual or product errors.
Large tasks benefit from structured context and iterative evaluation.
Human review remains important for consequential product decisions.
Generative AI asks: given this input and context, what useful new artifact can the model produce?
AI agent · AI product design · AI prototyping · AI prompt
Read AI for Product Design for how generative systems are used in real product workflows.