In AI product development, interpreting user intent is a critical challenge—especially when users are exploratory or vague. How do you guide users effectively without overwhelming them? For a long time, most SaaS products have been “expert systems”: the workflows and user inputs were strictly predesigned by developers. If you wanted to tell the system your preferences, you’d fill out a form or select predefined options. Essentially, the user adapted to the tool. But in the AI era, I see a fundamental shift: the system should actively adapt to each user. Instead of a rigid, form-based flow, AI-driven products can accommodate fluid, natural inputs—letting users express their intent however they like. This is a step beyond “user-friendly”; it’s what I call “human-like” design, where the software meets people on their terms. Join the Discussion: I’d love to hear from you! If this perspective resonates with you, feel free to share your thoughts, ideas, or examples in the comments. To spark discussion, here are a few questions to those great makers and marketing master in product hunt I’m curious about: - How do you build systems that guide users without overwhelming them, especially when users aren’t sure what they want? - Have you implemented frameworks or strategies to make AI systems adapt to users in real-time? What worked, and what didn’t? - What’s your approach to validating whether your AI truly captures user intent, instead of forcing users to adapt to preset flows? - Do you know of any products or tools that have successfully achieved this kind of “human-like” adaptability?