AI coding agents have made code generation fast. But faster code generation doesn’t automatically mean faster product delivery. The bottleneck has moved upstream into requirements and specifications, and downstream into testing and verification.
This datasheet explains how Spec-Driven Development (SDD) addresses that shift by turning engineering knowledge into explicit, deterministic structures AI coding agents can act on reliably. It also shows how Jama Connect® provides the governed Product Context Layer for SDD, connecting requirements, risks, tests, models, code repositories, reviews, approvals, verification evidence, and change history.
In this datasheet, learn how SDD and governed product context help engineering organizations:
- Understand what’s required to move from human-centered coding workflows to SDD.
- Give AI coding agents deterministic context to understand product intent, dependencies, and change impact.
- Maintain traceability, version history, reviews, approvals, and verification evidence as AI-assisted work progresses.
- Retrieve the specific product context an AI task requires instead of passing large requirements documents into prompts.
- Keep engineers in control while connecting AI coding agents to the existing engineering toolchain.
Download the datasheet to learn what changes when AI coding is no longer the bottleneck, and how governed product context provides the foundation for SDD.
