All tools are fundamentally decision-making aids. A great tool, like a color picker, isn't just about precision; it's about providing a quick feedback loop to compare options and a safety net (like undo) to explore changes without fear. This allows users to dial in their choices effectively and without destructive consequences.
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Reducing the number of clicks is a misguided metric. A process with eight trivially easy clicks is better than one with two fraught, confusing decisions. Each decision burns cognitive energy and risks making the user feel stupid. The ultimate design goal should be to prevent users from having to think.
The obsession with removing friction is often wrong. When users have low intent or understanding, the goal isn't to speed them up but to build their comprehension of your product's value. If software asks you to make a decision you don't understand, it makes you feel stupid, which is the ultimate failure.
When using "vibe-coding" tools, feed changes one at a time, such as typography, then a header image, then a specific feature. A single, long list of desired changes can confuse the AI and lead to poor results. This step-by-step process of iteration and refinement yields a better final product.
Early versions of Figma failed to gain traction because designers, its target users, fundamentally didn't trust the tool's own subpar visual design. This meta-problem highlights that for a tool to be credible to its expert users, its own execution must embody the principles it espouses. A redesign was the key to unlocking user trust and adoption.
The ultimate goal of interface design, exemplified by the joystick, is for the tool to 'disappear.' The user shouldn't think about the controller, but only their intention. This concept, known as 'affordance,' creates a seamless connection between thought and action, making the machine feel like an extension of the self.
When products offer too many configurations, it often signals that leaders lack the conviction to make a decision. This fear of being wrong creates a confusing user experience. It's better to ship a simple, opinionated product, learn from being wrong, and then adjust, rather than shipping a convoluted experience.
Open-ended prompts overwhelm new users who don't know what's possible. A better approach is to productize AI into specific features. Use familiar UI like sliders and dropdowns to gather user intent, which then constructs a complex prompt behind the scenes, making powerful AI accessible without requiring prompt engineering skills.
For highly commoditized interactions like text editor undo or canvas pinch-to-zoom, users have powerful, ingrained expectations. Failing to match these conventions doesn't make a tool feel "different"; it makes it feel fundamentally unusable and broken, regardless of its other features. Innovation should be focused elsewhere.
When exploring UI solutions, use a tool like Magic Patterns and its "Inspiration Mode" to generate multiple, distinct design approaches from a single prompt. By asking the AI to "think expansively and make each option differentiated," product managers can quickly explore a wide solution space and avoid getting stuck on a single initial idea.
The promise of AI shouldn't be a one-click solution that removes the user. Instead, AI should be a collaborative partner that augments human capacity. A successful AI product leaves room for user participation, making them feel like they are co-building the experience and have a stake in the outcome.
