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Requirement discovery for AI coding workflows is streamlined by capturing ideas immediately upon task creation, researching technical choices before asking questions, and converging on a defined MVP scope to ensure shared understanding before implementation.

The best way to define MVP scope for complex tasks is through a diverge-to-converge approach that expands thinking through research and high-value questions, then narrows down to the essential features needed for the minimum viable product.

Collaborative requirement research reduces low-value questions by adopting an action-before-asking approach, which means researching technical choices and seeding PRDs first to provide context, ensuring only high-value questions remain.

Yes, you can use this approach to create task directories and seed PRDs immediately upon task creation, capturing initial ideas and structuring the requirement discovery process before moving into the implementation phase.

You should use collaborative requirement discovery techniques when developing new features or handling complex tasks with unclear requirements, ensuring the team reaches a shared technical understanding before coding begins.