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AI & Enterprise

Why system-first engineering matters for agentic AI

As agentic AI moves beyond support to execute tasks inside workflows, trust becomes unavoidable. The risk comes less from AI acting alone than from engineering workflows that fail to express system-level behaviour in an executable form. System-first engineering, implemented through model-based design, provides shared, executable system models across mechanical, electrical and software domains. Deterministic, repeatable verification and simulation reduce dependence on hardware testing and allow changes to be assessed early against system-level criteria.

AI & Enterprise

AI beats law professors in blind law school test with 75 percent win rate

Artificial intelligence received higher ratings than human law professors in an experiment comparing the quality of answers to law students’ questions, a study found. In a blind review involving U.S. law school professors, AI-generated responses were judged better overall. Researchers recruited 16 professors and used 40 representative contract law questions, collecting 2,918 evaluations. In head-to-head comparisons, AI answers won about 75 percent of the time and were less often deemed educationally harmful.

Industry

Tesla FSD safety claims questioned; some internal AI staff say they do not trust it

A Reuters review found Tesla’s promoted safety statistics for its Full Self-Driving (FSD) system were based on a comparison using different crash measures. Researchers and former Tesla staff interviewed were sceptical of claims that FSD is up to 10 times safer than human drivers. Some former data labelers and an autonomy engineer said they would not trust the system. The review also cited reports of testing and mapping practices and growing regulatory scrutiny.