We scan new podcasts and send you the top 5 insights daily.
AI is excellent at showing what's possible and outlining a project's scope, much like revealing a map in a video game. However, it is still the designer's job to do the actual work of building, understanding the complexities, and navigating the terrain themselves.
AI won't replace designers because it lacks taste and subjective opinion. Instead, as AI gets better at generating highly opinionated (though not perfect) designs, it will serve as a powerful exploration tool. This plants more flags in the option space, allowing human designers to react, curate, and push the most promising directions further, amplifying their strategic role.
The focus on AI making work 'faster' misses its true value for designers. The real power lies in enabling them to push ideas 'further' into high-fidelity, interactive prototypes, allowing for deeper exploration and clearer communication of intent without engineering dependencies.
Contrary to claims that "handoff is dead," designers at top companies use AI-generated prototypes as highly detailed specs. These interactive prototypes provide more information than static designs but are still handed off to developers for implementation, rather than being merged directly into production.
AI coding tools can rapidly build the first 70% of an application, but the final 30%—the complex, unique features that define your vision—will consume the vast majority of your development time. This is a critical reality check for anyone starting with these tools.
Since AI can "one-shot" a feature once it's clearly defined, the designer's core value is moving upstream. It's no longer about execution, but about navigating the ambiguity of problem framing, opportunity discovery, and stakeholder communication *before* the building starts.
It's a common misconception that advancing AI reduces the need for human input. In reality, the probabilistic nature of AI demands increased human interaction and tighter collaboration among product, design, and engineering teams to align goals and navigate uncertainty.
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.
Successfully building with AI, even using no-code tools, demands a new level of detail from product managers. One must go deeper than a standard PRD and translate a high-level vision into extremely literal, step-by-step instructions, as the AI system cannot infer intent or fill in logical gaps.
For creative work like design, AI's true value isn't just accelerating tasks. It's enabling designers to explore a much wider option space, test more possibilities, and apply more craft to the final choice. Since design is non-deterministic, AI serves creative exploration more than simple speed.
A powerful but unintuitive AI development pattern is to give a model a vague goal and let it attempt a full implementation. This "throwaway" draft, with its mistakes and unexpected choices, provides crucial insights for writing a much more accurate plan for the final version.