Exceptional AI user experiences, like Claude Code, are not just a better interface or "harness" on an existing model. They are a "symphony of improvement" where the interface is co-designed in parallel with the model, anticipating its new capabilities to create a seamless whole.

AI will soon create a unique user interface for every individual, adapted to their needs. For designers, this means shifting from creating fixed systems to defining flexible boundaries within which form and function can blend, balancing personalization with brand identity and usability.

At a research-led company like OpenAI, a designer's role expands beyond packaging existing technology. They must envision what the technology *should* do to solve user problems, thereby setting a vision that helps direct future research and engineering efforts.

Simply building what users ask for can trap a product in old paradigms, like reinventing Photoshop's lasso tool for an AI context. A successful strategy involves staying slightly ahead of user adoption, introducing new capabilities that fundamentally change their workflow, and guiding them toward a more efficient future.

At OpenAI, the first question is "Can we solve this with the model (tokens) instead of pixels?" This treats the AI as the primary design material, pushing designers to think about interaction and behavior before creating bespoke user interfaces.

OpenAI is developing a "dynamic user interface library" designed so the AI model can interpret and compose UI elements itself. This forward-thinking approach anticipates a future where the model assembles bespoke interfaces for users on the fly.

With AI, designers are no longer just guessing user intent to build static interfaces. Their new primary role is to facilitate the interaction between a user and the AI model, helping users communicate their intent, understand the model's response, and build a trusted relationship with the system.

Building text or voice-first AI agents means discarding years of UI-based product development principles. Without the "crutch" of a visual interface, product managers must solve novel challenges in reliability, user education for new mental models, and creating a magical experience through conversation alone.

Building a true AI product starts by defining its core capabilities in an AI playground to understand what's possible. This exploration informs the AI architecture and user interface, a reverse process from traditional software where UI design often comes first.