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Too Fast to Design
Designers risk stagnation if they accept AI’s first 'reasonable' solution rather than using it to expand the scope of the problem.
What: Albert Patrashku argues that because AI is highly efficient at providing acceptable solutions, it discourages the critical 'uncertainty' phase of design. Designers should use AI to challenge assumptions rather than settle on the first result.
Why it matters: The danger of AI isn't that it performs poorly, but that it performs 'good enough' to shut down deeper exploration prematurely.
Takeaway: Next time an AI provides a design solution, use the output as a starting point to ask: 'What other explanations exist for this problem?' and 'What assumptions am I taking for granted?' before finalizing your direction.
Original article
Design work often requires sitting with an ambiguous problem rather than jumping to a fix, like resizing a button instead of asking why people aren't clicking it. AI tends to shortcut that stage, turning a vague brief into a flow, screen, and text within seconds. That halts exploration not because the answer is wrong, but because it's reasonable enough to accept, so AI works best widening the question first.
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