Towards Data Science is a community-powered publication that showcases work in data science, machine learning and artificial intelligence. Every day newcomers, seasoned researchers and industry practitioners publish tutorials, research notes and real-world case studies that help the field move forward.

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Before building AI products, organizations must define clear objectives, establish measurable KPIs, and assess risk tolerance. Many teams skip this planning phase, leading to misaligned expectations and inadequate evaluation. Success requires systematic testing rather than relying on anecdotal feedback or "vibes." LLMs' nondeterministic nature makes upfront planning especially critical—teams must understand potential failure modes and decide if they can accept the inherent unpredictability. Setting evaluation criteria before development prevents gaming metrics and ensures measurement validity.

Advance Planning for AI Project Evaluation