AI coding agents like Antigravity, Cursor, and Claude Code have collapsed the financial cost of building software. A working prototype now takes an afternoon. But the psychological cost of skipping discovery has not dropped, and that is the problem this article is built around.
The core argument draws on a 2013 study by Viswanathan et al. on sunk cost in engineering idea generation. Participants who spent the most effort building physical prototypes produced ideas with measurably less novelty and variety. The authors call this Design Fixation. The article applies that finding directly to AI-assisted development: even when the financial investment is low, seeing a functional prototype triggers the same sunk cost response. Teams stop looking for evidence they are wrong and start looking for evidence they are right, at exactly the moment they need to stay open.
The piece goes further than diagnosing the problem. It pulls in the Design Science framework from Johannesson and Perjons, the original Lean Startup MVP literature, and the concept of the Minimum Viable Experiment to argue that the solution is structural, not motivational. The MVE is positioned not as a time-saving tool but as a cognitive firewall against premature fixation. It also reframes the role of UX teams: the pitch can no longer be saving engineering hours. It has to be protecting brand equity and market credibility. The full article is worth reading for the concrete strategies it outlines on using AI tools within a design science cycle rather than in spite of one.
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