AI tools are evolving quickly, yet their integration into product design workflows is still ambiguous. Nikita Samutin outlines four core design stages—analytics, ideation, prototyping, and visual design—highlighting where AI fits effectively and where it falls short. Despite the availability of curated AI tool lists, the challenge lies in their practical application for productivity. A common issue faced by designers is that AI often produces clichéd ideas due to a lack of contextual nuance. By promoting a focused approach in providing relevant documentation, AI can generate more relevant outputs.
AI does not know the specifics of your product or the full context of your task, which limits its ability to generate creative ideas effectively.
Submitting an overload of documentation to AI can lead to vague and unfocused answers, known as the 'lost in the middle' problem.
Current-generation AI can process thousands of words, but longer inputs increase the risk of missing critical information, particularly content buried in the middle.
A simple, repeatable workflow that integrates AI into stages like ideation and visual design can significantly boost productivity for product designers.
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