AI is rapidly rewriting the world's software at unprecedented scale. Code Metal recently raised $125 million to rewrite defense industry code using AI, while Google and Microsoft report that 25-30% of their new code is AI-generated. AWS used AI to modernize 40 million lines of COBOL for Toyota. Microsoft's CTO predicts that 95% of all code will be AI-generated by 2030.

This transformation is already underway. Anthropic built a 100,000-line C compiler using parallel AI agents in two weeks for under $20,000. It boots Linux and compiles major databases like SQLite and PostgreSQL. But here's the critical gap: no one is formally verifying these AI-generated systems. Andrei Karpathy admitted he rarely reviews AI code diffs anymore, accepting the default "Accept All" option. Nearly half of AI-generated code fails basic security tests, and newer models aren't significantly more secure than their predecessors.

The problem extends beyond accidental errors. Heartbleed, a single OpenSSL bug, exposed millions of users' private communications and cost hundreds of millions of dollars to remediate. Now AI generates code at a thousand times the speed across every software layer, while our verification methods remain unchanged. Traditional code review, testing, and manual inspection missed Heartbleed for two years. AI-generated code creates new supply chain attack surfaces where adversaries can inject subtle vulnerabilities through poisoned training data or compromised model APIs.