The ‘Pain in the Ass’ Math That Could Save Vibe Coding From Itself

Stanford researcher Chuyue Sun and her fellow computer scientists developed an AI tool that completed an engineering project in less than half a day for under $500, compared to the five months it took three highly skilled experts to do the same work manually. The dramatic reduction in time and cost, which Sun reported in a recent paper, is among the early results that are awakening an obscure field of coding and mathematics known as formal verification.

For decades, developers have envisioned using math to prove that their software is bug-free. This process is long and laborious, requiring engineers to write precise statements about the goals of their software and convert their code into formulas that can be validated. While companies already run sophisticated tests to identify as many flaws in their software as possible, they rarely shell out for formal verification, which can catch even more erratic behavior.

Now, a wave of startups is betting that generative AI will make formal software verification both practical and essential. Among them is &Truth, which Sun joined in August and publicly launched on Thursday. Sun’s research demonstrated the technology’s potential by using AI to verify part of the code that encrypts conversations in the messaging app Signal.

“Bridges, buildings, they don’t collapse because people did math before constructing them,” says Ilya Sergey, &Truth’s chief science officer. “Why don’t we do the same for code? The technology to mathematically reason was all there, just difficult to scale.”

And just last week, Anthropic and the verification startup Theorem jointly announced they had used AI to assist in finding bugs in open source software that trillions of tests had failed to detect. They also introduced an add-on for Claude to help other developers with verification. Costs of the initial project were not disclosed.