How I’m Using Google Opal for Even More AI Automations

The last time I opened Opal to start a new build, something in the interface had quietly changed. The Generate step, the one I'd used a dozen times to pick Gemini or Imagen or Veo, now had a new option sitting right above the familiar model list, simply labeled "Agent." No blog post had landed in my inbox announcing it. It was just there, waiting to be clicked.

That small addition turned out to be a genuinely different way of building with this tool, and it's the reason this article exists. If you haven't built anything with Opal yet, go read Building AI Automations with Google Opal first; it walks through the Editor, the three original step types, sharing your app, and debugging with the Console in full, and everything here assumes you've got that foundation already. This piece picks up exactly where that one left off: what's changed since, and a full second build that specifically puts the new pieces to work.

A Fast Recap, for Anyone Catching Up

Opal is Google Labs' no-code tool for turning natural language into working AI mini-apps, built on top of an internal framework called Breadboard, created by Google engineer Dimitri Glazkov. You describe what you want in plain English, Opal turns that description into a visual, editable workflow of connected steps, and you can share the finished app with a public link — no server, no deployment pipeline, no code. The mechanics of the Editor, the App preview, the Console, and version history are all covered thoroughly in the first article, so this piece won't repeat that ground. What follows is everything that's arrived since.

What's Actually Changed Since Then

The short version: Opal stopped being just a tool for wiring together fixed, manually chosen models, and started being able to make some of those choices itself. In February 2026, Google Labs shipped what it calls an agent step, and it's a meaningfully different way of building than the original three-step model of User Input, Generate, and Output.