Beyond Patchmageddon: The AI Vulnerability Crisis Is an Engineering Challenge, Not Inevitable Doom
AI writes vulnerabilities into code and finds them faster every quarter, while fixing them still moves at human speed. You can’t hire your way out of that gap, and another scanner only makes it wider - more findings, not more fixes. JP Morgan’s Michael Cembalest calls it “Patchmageddon.” I don’t see it as inevitable doom. I see it as an engineering problem the industry has been approaching the wrong way.
The mistake is fixing vulnerabilities one at a time. In practice, many findings share one fix - ten alerts can come from a single outdated base image, and a recurring bug is often one missing guardrail. Group the work by the change that fixes it, and AI can reason about the whole group, generate a fix a developer will actually accept, and verify it shipped. That’s what my team builds with Cycode’s Context Intelligence Graph.
But clearing the backlog is only half the job. The other half is making sure the same mistakes don’t come back: every fix becomes a rule that scanners enforce and that AI coding assistants follow when they write new code. Prevention moves upstream, to the moment code is written.
That’s where I think security has to go: not more alerts, but a system that gets safer the more it’s used.