For the last few years, much of the discussion around AI-assisted programming has concentrated on models. Which model generates the best code? Which one understands the largest repository? Which one makes fewer mistakes? Which one has the largest context window? Those questions still matter, but something more interesting is happening.The infrastructure surrounding coding agents is starting to assume that the model is not the component that should ultimately be trusted. Instead, increasingly sophisticated systems are being built around models to control what they can access, what operations they can perform, how those operations are approved, and how their results are verified.