// WIRED US/UK — INTELLIGENZA ARTIFICIALE
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.”
&Truth has raised $70 million from investors and aims to eventually verify any programming language. Rival Harmonic, which was cofounded by Robinhood CEO Vlad Tenev and has received $295 million in funding, announced this week that its math-focused AI agent Aristotle supports verifying software written in C and hardware designs in Verilog. It is evaluating the technology with potential users, including chipmakers Tensordyne and Nvidia, whose venture capital arm is one of the startup’s investors.
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.
The big promise is a future where software runs more reliably with fewer security headaches. But whether AI can bring formal verification beyond the most critical systems at organizations like NASA and Apple and into widespread use remains an open question.
The technology is still in the prototyping stage. Though demand is high, it's unclear how much customers are willing to pay and how they prefer to adopt the technology. Formal verification relies on making assumptions about how computers and people interact with software, and some experts are skeptical about its ability to catch bugs stemming from user error and hardware breakdowns.
Will Wilson, who runs the bug-hunting AI software startup Antithesis, calls formal verification “a trap” for math nerds like himself. Antithesis spent millions of dollars to formally verify some of its cybersecurity defenses, a process Wilson describes as a “pain in the ass.” Yet the startup still uncovered additional errors using its own tool, and Antithesis has also found bugs in software that several of its customers had formally verified. “It can give you some assurance, but only robust exhaustive testing can prove your assurance is true,” Wilson says.
Or as Vitalik Buterin, the engineer known for creating the Ethereum cryptocurrency, put it in a blog post earlier this year, “formal verification is not a panacea.” But he and other proponents of the approach still believe it will be an important defense against AI systems launching cyberattacks and wreaking havoc.