Google Opal Gets Interactive AI Workflow Upgrade

Enterprise AI teams have been building agents the hard way: wiring models, tools, and logic into brittle chains that break the moment the input shifts. Google just erased that approach. With a single update to Opal, what it calls an “agent step”, the platform transforms static drag-and-drop workflows into something fundamentally different.

Builders no longer dictate sequence. They define a goal. The agent decides the rest: which model to invoke, which tool to pull, when to generate video with Veo, when to prompt the user for clarification.

What emerges is not just a feature but a working reference architecture for three capabilities that will define enterprise agents in 2026: adaptive routing, persistent memory, and human-in-the-loop orchestration. And all of it rests on the rapidly improving reasoning of frontier models like Gemini 3. This is the inflection point.

Better models don’t just make agents faster; they make agent design simpler, more fluid, and radically more capable. The old blueprint is off the rails, and Google just showed everyone the new one.