Context-Driven Development Workflow

Context-Driven Development Workflow (CDDW) is a practical, operational workflow for structuring software development as a continuous learning process in AI-assisted engineering environments.

CDDW is designed for a world in which AI agents perform a significant portion of implementation work, with humans retaining responsibility for meaning, coherence and intent.

The problem CDDW addresses

Software development inevitably produces learning. Traditional workflows treat that learning as incidental and disposable.

As AI accelerates implementation, this leads to:

• Design drift
• Lost rationale
• Fragmented concepts
• Agents operating on outdated assumptions

CDDW treats learning as a first-class artifact that must be explicitly captured, reviewed and consolidated into authoritative context.

Relationship to Context-Driven Engineering

CDDW builds on the conceptual foundation of Context-Driven Engineering (CDE).

Where CDE provides a worldview and conceptual framework, CDDW provides one concrete operationalization of those ideas in day-to-day development work.

Adopting CDDW does not require full adoption of CDE, and CDE does not mandate CDDW.

Status

CDDW is an experimental workflow.

Its core concepts and document responsibilities are already being exercised in real projects, while operational details continue to evolve through use.

The workflow is usable today, but not frozen.

Learn more

The authoritative definition of CDDW, including its documents and rules, lives in the public GitHub repository:

https://github.com/symbolicmatter/context-driven-development-workflow

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Context-Driven Development Workflow is developed and published by Symbolic Matter, a research-driven studio exploring the intersection of software design, meaning, and emerging AI-assisted development practices.