As collaboration with generative models becomes more common, certain interface patterns that facilitate this interaction are beginning to take shape. These are not passing fads, but solutions that respond to a new design logic: the interface is no longer just an execution space, but an environment for dialogue between human and machine. These are some of the most representative patterns:
Prompt builders and interactive editors
The prompt has become the new language of AI interaction design. But writing a good prompt isn't always intuitive. That's why many tools have begun to offer visual builders: structured fields, contextual examples, c level contact list buttons to adjust style or tone, automatic suggestions... Instead of a blank text box, the interface acts as a creative guide, helping the user better formulate their intention.
Adaptive workspaces
Collaboration with AI requires flexibility. That's why we're increasingly seeing modular interfaces that reorganize themselves according to the flow: first I write, then I edit, then I compare variants… Some platforms even adjust the layout based on the type of task (quick draft, deep edit, review). These adaptive environments help maintain user attention and minimize friction.
Previews and variants
When an AI generates multiple possible outcomes, the interface must facilitate comparison and choice. Displaying variants side-by-side, allowing switching between versions, or even zooming in on key changes has become common practice. This pattern not only provides control but reinforces the sense of co-creation: the user doesn't receive a single proposal, but rather a range from which to decide.
Co-editing and on-the-fly suggestions
In many tools, AI no longer waits for the user to finish typing before intervening: it suggests things as they type, completes fragments, and suggests improvements in real time. This pattern, inherited from autocomplete , is becoming more sophisticated and contextual. The challenge here is balancing intervention and autonomy: a good suggestion should not interrupt or intrude, but rather integrate naturally into the user's flow.
These patterns aren't static or definitive. They evolve alongside the models' own capabilities and the maturity of users. But they all point in the same direction: interfaces that not only allow you to do things with AI, but are specifically designed to do them well .