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The AI product development lifecycle has seven distinct stages: problem validation, data discovery, approach selection, prototyping, MVP development, production deployment, and continuous optimisation. Unlike traditional software, every stage is iterative and data-dependent — and 80% of AI products fail because teams skip or rush the early foundations. Here’s how to navigate each phase correctly. According…