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For implementers, this promise-heavy design constrains optimization opportunities. The spec mandates specific promise resolution ordering, making it difficult to batch operations or skip unnecessary async boundaries without risking subtle compliance failures. There are many hidden internal optimizations that implementers do make but these can be complicated and difficult to get right.

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Poor software quality already costs the U.S. economy $2.41 trillion per year, according to a 2022 study by the Consortium for Information & Software Quality. That number was calculated before AI began writing a quarter or more of new code at leading companies. Chris Lattner, the creator of LLVM and Clang, put it bluntly: AI amplifies both good and bad structure. Bad code at AI speed becomes “incomprehensible nightmares.” As AI generates an increasing share of the world’s critical infrastructure (financial systems, medical devices, defense, transportation), unverified code becomes a systemic risk, not just a quality problem.

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