For the past few years, AI-assisted database development has followed a fairly comfortable model. A developer describes a requirement. The AI generates SQL. The developer reads it, changes what looks wrong, and decides whether to run it. That workflow has kept one important boundary intact: AI can suggest an action, but a human still decides whether it reaches the database. However, that boundary is beginning to disappear with agentic AI. Today, AI systems can inspect schemas, run queries…