AI Product Development Glossary

Key terms used across AI-assisted planning, vibe coding, and implementation workflows.

Vibe Coding

A development style where humans guide intent and constraints while AI systems generate and refine implementation paths.

A structured document that defines product goals, user flows, technical architecture, and delivery requirements.

A focused definition of the smallest viable release that tests core assumptions with real users.

A visual representation of interface layout and content used to validate design intent before coding.

A node-based visual model that organizes product domains, components, and relationship logic.

A text-based diagram syntax commonly used to generate flowcharts and architecture visuals from structured text.

Model Context Protocol, a standard for connecting AI agents to tools, context sources, and external capabilities.

An API model for persistent AI interactions using threads, tools, and long-running workflow states.

A stateless API pattern where each response is generated from the current prompt and explicit context payload.

A response contract enforcing JSON schema shape so generated data can be validated and consumed reliably.

The design of instructions, constraints, and examples that improve model response accuracy and consistency.

A pattern where external documents are retrieved and injected into model context to ground responses in real sources.

An orchestrated process where multiple AI agents perform specialized tasks and hand off outputs across stages.

Artifacts prepared for engineering execution that reduce ambiguity between planning and implementation teams.

Generative Engine Optimization, the practice of improving visibility and citation likelihood in AI answer engines.

Google-generated summary answers that synthesize multiple sources directly on the search results page.

Google’s quality framework for Experience, Expertise, Authoritativeness, and Trustworthiness in content evaluation.

A push-based indexing protocol that notifies search engines quickly when URLs are created or updated.

The preferred URL for indexing when multiple pages contain similar or duplicate content variants.

Structured metadata in formats like JSON-LD that helps search engines interpret page meaning and entities.