How Can We Make AI-Generated Code Provably Safe at Scale?

AI can now write code faster than any team can review it, and tests only check the cases someone thought to write down. Formal verification used to be too expensive for anything except avionics and crypto libraries, but LLMs are changing that by drafting the specs, invariants, and proofs that were too slow for humans to write by hand. This episode looks at what verification actually guarantees, where it quietly fails, and why the builder's real job moves from reviewing code to writing the specification. Produced by VoxCrea.AI This episode is part of an ongoing series on governing AI-assisted coding using Claude Code. 👉 Each episode has a companion article — breaking down the key ideas in a clearer, more structured way. If you want to go deeper (and actually apply this), read today’s article here: 𝐂𝐥𝐚𝐮𝐝𝐞 𝐂𝐨𝐝𝐞 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 At aijoe.ai, we build AI-powered systems like the ones discussed in this series. If you’re ready to turn an idea into a working application, we’d be glad to help.