Testing and proof are complementary. Testing, including property-based testing and fuzzing, is powerful: it catches bugs quickly, cheaply, and often in surprising ways. But testing provides confidence. Proof provides a guarantee. The difference matters, and it is hard to quantify how high the confidence from testing actually is. Software can be accompanied by proofs of its correctness, proofs that a machine checks mechanically, with no room for error. When AI makes proof cheap, it becomes the stronger path: one proof covers every possible input, every edge case, every interleaving. A verified cryptographic library is not better engineering. It is a mathematical guarantee.
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In an analysis by energy consultancy Wood Mackenzie, researchers noted that the nearest historical analogue would be the 1970s, when an oil supply crisis sparked downturns in several countries around the world. Unlike that period, however, the world is now much less reliant on oil, the analysts noted. To create a similar scale of global economic crisis, they wrote, oil prices would need to reach around $200 a barrel.