Why Fixing Vulnerabilities in Code Beats Patching in Production

A recent example highlights a common developer habit: pulling a base image like node:20-slim without checking it. That single image can carry over a dozen known vulnerabilities, some of them critical. If caught early in the code, the fix is trivial, a one-line change before anything is deployed. If caught after the code is already running in production, the same fix becomes a major operation involving patching every live container, coordinating across teams, and scheduling maintenance windows, all while an incident team scrambles to work out whether attackers already found the flaw.

This cost gap between fixing issues early versus late has always existed, but artificial intelligence is now making it far more urgent. AI tools can scan open source code, spot unpatched vulnerabilities, and build working exploits in minutes rather than days. This means the gap between a vulnerability being disclosed and it being actively exploited is shrinking fast. Simply patching faster is not enough because organisations are still limited by how quickly they can safely roll out changes to live systems.

The more effective approach is to reduce risk at the source, before code ever reaches production. Fixing an issue in code is cheaper because the change only needs to happen once, rather than being repeated across every system the flawed code touches. It is also easier because developers still remember the context of the code they just wrote, rather than having to relearn old work months later.