Code review is carrying more responsibility than it was designed to hold, and AI-generated volume is making the mismatch impossible to ignore. Teams ask senior engineers to inspect every generated line because experience feels like the safest control. Those same engineers also own the hardest design decisions, production problems, and mentoring work. When review becomes the answer to every defect, the queue grows while human attention gets thinner.

Code review still matters because it is where teams explain choices, share context, and decide whether a change belongs in the system. This session shows how to protect that human work by moving routine evidence earlier through test-first generation, static analysis, agent self-audit against an approved plan, and repository-level signals that tell us where to look. If you write, review, or merge code, you'll leave with a practical quality stack that puts routine checks in tools and reserves human attention for design, context, and ownership. You will also have a better answer than “review everything” when your team asks how to trust AI-assisted code.