Most engineers don’t review transpiled output or minified bundles. They review the source and trust the pipeline. At some point, that output became a black box. Validation moved up a level. Nobody held a ceremony about it.

The same shift is happening with agentic code generation. And most delivery systems haven’t adjusted.

Dave Farley recently explained the Nyquist-Shannon Sampling Theorem in the context of software delivery[1]. To reliably detect change, you must sample at twice the frequency of the change itself. If AI increases code output volume, and humans remain the primary sampling layer, review doesn’t scale. The human becomes the bottleneck by design.

The METR study[2] found developers using AI tools were 19% slower on average. The code changed. The delivery system didn’t. That mismatch is where the cost accumulates.

So where does validation move?

Three places. Contracts define expected behaviour before anything is written. External test coverage confirms the implementation meets those contracts. Runtime monitoring catches what slips through both. Together, they replace the pull request as the primary quality gate.

Teams on the frontier are already redesigning around this. They’re not reviewing every line of generated code. They’re investing in interface definitions, automated coverage thresholds, and production observability. The checkpoint moved.

If your team’s primary validation mechanism is still a pull request review, that process was built for a world where implementation speed was the constraint. It probably isn’t anymore.

Audit where your validation actually sits. That’s where to start.

[1] https://www.youtube.com/watch?v=XavrebMKH2A [2] https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/