context-driven-development

Context-driven development treats project context as living documentation that guides AI-assisted work. It maintains canonical artifacts like product.md, tech-stack.md, and workflow.md to ensure team alignment and reduce miscommunication between product goals and technical decisions.

To synchronize context artifacts, run the context setup to analyze your existing codebase. The workflow handles cross-artifact consistency, validating and evolving product.md, tech-stack.md, and workflow.md to keep context up to date.

Yes, living documentation supports both greenfield and brownfield projects. It provides clear tracks for starting new projects or analyzing existing codebases, ensuring context creation and maintenance apply regardless of project maturity.

The best way to align AI behavior is establishing a repeatable workflow using context artifacts. By treating product.md, tech-stack.md, and workflow.md as canonical references, you inform AI decision-making and governance throughout the development lifecycle.

Context lifecycle management is applicable to Conductor-driven projects. It coordinates context creation, validation, evolution, and synchronization, requiring this environment to establish clearly defined lifecycles and ensure cross-artifact consistency.

Context artifacts may be unnecessary for simple, short-lived projects where maintaining living documentation outweighs the benefits of AI alignment. If your project lacks complex product goals or evolving tech stacks, the synchronization overhead provides limited value.