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The Crystal Ball Lies Sometimes: Verifying AI Before You Trust It
Even enchanted mirrors occasionally reflect impossible futures. Artificial intelligence has rapidly become one of the most productive tools ever placed into the hands of software engineers. It can explain unfamiliar concepts, generate working prototypes, refactor decades-old code, write unit tests, summarize documentation, and even identify subtle defects that would otherwise escape notice. After spending only a few weeks working alongside modern AI systems, it becomes difficult to imagine returning to a workflow that depends entirely on search engines, reference manuals, and trial-and-error. Yet every experienced engineer eventually encounters a moment that changes the relationship. Perhaps the generated code compiles perfectly while quietly introducing a race condition. Perhaps an API appears…


