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.

As AI accelerates software development, basic functionality becomes table stakes. Figma's CEO contends that differentiation and winning now depend entirely on design, craft, and a strong point of view, as 'good enough' products will no longer succeed.

A truly "AI-native" product isn't one with AI features tacked on. Its core user experience originates from an AI interaction, like a natural language prompt that generates a structured output. The product is fundamentally built around the capabilities of the underlying models, making AI the primary value driver.

The end state for enterprise AI is a unified, conversational agent serving as the primary interface for a brand. This "digital concierge" will handle sales, support, and other interactions, potentially replacing websites and mobile apps as the main customer touchpoint.

Figma's CEO believes AI will create the "10X designer." As AI automates basic design tasks, making "good enough" the new baseline, the premium on true craft and system-level thinking will skyrocket. Designers who can leverage AI to execute a holistic product vision will become indispensable leaders and key drivers of a company's success.

Beyond its technical capabilities, OpenAI's app ecosystem within ChatGPT functions as a new distribution platform. For founders, this creates a strategic opportunity to build apps that serve as an interface layer to their product, opening a novel and potentially powerful channel for user acquisition and growth.

Instead of building a single-purpose application (first-order thinking), successful AI product strategy involves creating platforms that enable users to build their own solutions (second-order thinking). This approach targets a much larger opportunity by empowering users to create custom workflows.

The primary channel for discovery is shifting from search engines (SEO) to AI-powered "answer engines" like ChatGPT. Product Managers are now responsible for this new distribution channel, requiring a strategy to ensure their brands and products surface in AI-generated responses.