This acceleration requires specifications: precise descriptions of what the software must do. As AI takes over implementation, specification becomes the core engineering discipline. Writing a specification forces clear thinking about what a system must do, what invariants it must maintain, what can go wrong. This is where the real engineering work has always lived. Implementation just used to be louder.
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The intuition behind this mechanism is best illustrated by Wason’s (\citeyearwason_failure_1960) rule discovery task. When asked to discover a hidden rule governing number triples (e.g., 2-4-6), participants overwhelmingly proposed triples that fit their current hypothesis (e.g., testing 8-10-12 to confirm “increasing even numbers”) rather than triples that would defy it. Because the true rule was simply “increasing numbers,” these positive tests appeared to confirm people’s more restrictive hypotheses.
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