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Defining project requirements before implementation requires a structured discovery phase to clarify ambiguities and establish a clear MVP scope. This approach guides AI through task definition, self-driven technical research, and divergence-convergence to prevent rework and ensure alignment.

Structuring product discovery effectively involves using a diverge-converge strategy to capture initial ideas and evaluate technical options. This method ensures future evolution and edge cases are considered before locking down the MVP scope for agile development.

Applying an action-before-asking approach prioritizes self-driven research and context gathering over immediate user questions. This ensures AI proactively investigates technical options and edge cases before requesting user input for requirement definition.

Python3 is required as a dependency to run this collaborative requirements discovery process. The environment relies on python3 to execute the scripts that guide AI through task-first requirement capture and structured divergence-convergence strategies.

Using this requirements discovery process for a new user authentication feature helps clarify ambiguities and explore technical options. It guides AI to define a clear MVP scope through structured divergence-convergence, preventing rework and ensuring alignment.