The author proposes a structured workflow for machine learning projects, moving away from ambiguous discovery meetings towards a defined strategy. This framework involves a 4-phase, 9-skill core process, supplemented by three practical extensions, to guide projects from initial AI problem identification to a scoped and viable Minimum Viable Product (MVP). The aim is to ensure that ML discovery efforts are grounded in concrete strategy rather than vague discussions. AI
IMPACT Provides a structured approach for teams to manage AI projects, ensuring clearer strategy and a defined path to MVP.
RANK_REASON The item describes a workflow for managing ML projects, which is a tool or methodology rather than a core AI release or significant industry event.
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