The AI Velocity Trap: Shipping Faster Without Breaking More

LLMs and coding agents have made it dramatically easier to produce code. But if every velocity gain also increases regressions, incidents, and error rates, we have not improved software delivery; we have only moved the bottleneck downstream. I'll explore: Why AI-assisted velocity is a liability without stronger feedback loops. How agents can harden the lifecycle before, during, and after code is written. How an agent team can verify plans, inspect changes, challenge assumptions, and catch issues before human review. How deployment awareness and production monitoring change the role of coding agents. How teams can ship faster without turning every release into a reliability gamble. The new SDLC loop: moving from requirements → build → verify → observe → repeat.