bmad-create-architecture

You can document AI architecture decisions using a structured, collaborative workflow that guides stepwise discovery and tracks progress. This approach provides templates and references to coordinate multiple AI agents, reducing ambiguity and ensuring repeatable implementations across teams.

The best way to structure a collaborative architecture workflow is by using stepwise discovery combined with frontmatter-driven progress tracking. This mechanism coordinates multiple AI agents and human input across multiple steps to generate consistent design artifacts and document outcomes.

To start the step-based architecture decision process, provide a workspace containing the architecture workflow files, load your input documents, and initiate the stepwise discovery. The workflow uses frontmatter state to track progress and programmable prompts to guide each decision.

Yes, you can use this architecture workflow to coordinate multiple AI agents and human input. It provides structured design guidance that satisfies requirements for a documented workflow, frontmatter state, and programmable prompts across multiple steps to maintain consistency.

Yes, this architecture workflow supports programmable prompts across multiple steps. It uses frontmatter-driven progress tracking and artifact generation to guide architecture decisions, ensuring repeatable implementations and consistent outcomes across teams.

You need a structured workflow for architecture decisions when experiencing decision paralysis or needing to ensure AI agent consistency at scale. It provides collaborative design guidance, tracks progress via frontmatter, and documents outcomes to enable repeatable implementations across teams.