trellis-brainstorm

MVP requirements discovery is structured through a multi-step workflow that seeds a PRD, gathers auto-context, performs technical research, and iterates via high-value questions to converge on a feasible scope.

Brainstorming product requirements with AI is guided by a collaborative workflow that enforces task creation, research-driven options, and one-question-at-a-time inquiries to ensure clear alignment before implementation.

Yes, you can use AI to generate a PRD and define MVP scope. The workflow explicitly seeds an initial PRD, conducts in-depth research, and applies a Q&A loop to converge on the final MVP boundaries.

Collaborative requirements discovery works by orchestrating task creation and PRD seeding upfront, followed by sequential high-value questions and technical research to align AI coding workflows with MVP scope.

No specific dependencies are required to start AI-driven requirements discovery. The workflow operates independently to guide task creation, PRD seeding, and MVP scope convergence without external components.

Structured brainstorming workflows for PRD generation are unnecessary for trivial changes with predefined scope, as the enforced research, Q&A loops, and MVP convergence steps are designed for complex feature investigations.