Agentic delivery has a context problem. A product decision must survive through architecture, data models, specifications, prompts, tests, security controls, and code. As the product evolves, these artefacts can retain different versions of the truth.

Product Definition as Code (PDaC) is an open technique that treats product definition as an architectural asset: structured, versioned, linked, and changed explicitly. Instead of asking teams and agents to reconstruct the product from tickets, documents, and conversations, it provides a shared semantic layer for delivery, quality, and governance.

This session shows how product rules, actors, journeys, boundaries, requirements, and quality constraints form that layer; how Product Changes preserve the reasoning behind evolution; and how dependency checks expose divergence before it becomes costly rework.

The result is clearer context for AI agents, keeping product, architecture, security, and QA aligned as the system changes.