Figma CEO Dylan Field predicts we will look back at current text prompting for AI as a primitive, command-line interface, similar to MS-DOS. The next major opportunity is to create intuitive, use-case-specific interfaces—like a compass for AI's latent space—that allow for more precise control beyond text.

Current text-based prompting for AI is a primitive, temporary phase, similar to MS-DOS. The future lies in more intuitive, constrained, and creative interfaces that allow for richer, more visual exploration of a model's latent space, moving beyond just natural language.

The primary interface for managing AI agents won't be simple chat, but sophisticated IDE-like environments for all knowledge workers. This paradigm of "macro delegation, micro-steering" will create new software categories like the "accountant IDE" or "lawyer IDE" for orchestrating complex AI work.

While chatbots are an effective entry point, they are limiting for complex creative tasks. The next wave of AI products will feature specialized user interfaces that combine fine-grained, gesture-based controls for professionals with hands-off automation for simpler tasks.

The future of data analysis is conversational interfaces, but generic tools struggle. An AI must deeply understand the data's structure to be effective. Vertical-specific platforms (e.g., for marketing) have a huge advantage because they have pre-built connectors and an inherent understanding of the data model.

AI is best understood not as a single tool, but as a flexible underlying interface. It can manifest as a chat box for some, but its real potential is in creating tailored workflows that feel native to different roles, like designers or developers, without forcing everyone into a single interaction model.

The next frontier for conversational AI is not just better text, but "Generative UI"—the ability to respond with interactive components. Instead of describing the weather, an AI can present a weather widget, merging the flexibility of chat with the richness of a graphical interface.

AI chat interfaces are often mistaken for simple, accessible tools. In reality, they are power-user interfaces that expose the raw capabilities of the underlying model. Achieving great results requires skill and virtuosity, much like mastering a complex tool.

Chatbots are fundamentally linear, which is ill-suited for complex tasks like planning a trip. The next generation of AI products will use AI as a co-creation tool within a more flexible canvas-like interface, allowing users to manipulate and organize AI-generated content non-linearly.