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North Carolina's extensive highway system serves as a vital link for commerce, with thousands of commercial trucks transporting goods across the state every day. While this steady flow of freight supports local businesses and the broader economy, it also increases the risk of devastating collisions involving large trucks and passenger vehicles. Because of the size and weight of commercial rigs, these accidents often result in severe injuries that leave victims facing long recoveries, financial hardship, and complex legal questions.

Chicago is a city defined by movement, from its busy expressways and crowded intersections to the constant flow of commuters, delivery vehicles, and commercial traffic that keeps the region running. With so many people sharing the road every day, accidents can happen in an instant, leaving victims to cope with physical injuries, financial uncertainty, and questions about what comes next. In a legal environment where many firms handle a significant number of personal injury claims, success depends on more than experience alone.

I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU. This walkthrough gives the agent two independent witnesses: Together, they turn AI code verification into an experiment with two independent checks.