Jose Hurtado

Free AI-powered tools to validate designs against 168 research-backed UX principles. Cursor, v0, and Claude generate beautiful interfaces but silently break UX fundamentals — Hick's Law violations, cognitive overload, missing feedback loops. 5 free tools: AI Validator, UX Smell Detector, Flow Checklists, AI Prompts (600+), Parts Checklist. No signup needed. Principles Library ($29/yr) unlocks all 168 principles with examples and prompts. Backed by 2,098+ citations. EN/ES.

Hey Product Hunters, The "AI-powered" wave is everywhere, and it's exciting! But as builders, it makes me think: are we always pushing 'AI-First' in a way that truly benefits the user, or are we sometimes just adding AI features, potentially increasing complexity, and calling it innovation? Having spent time building a tool where AI is foundational rather than an add-on, my strong belief is that true AI-First design should fundamentally be about subtraction, not addition. The goal should be a significantly simpler, more intuitive user experience than a non-AI alternative. Based on my experience, here are some principles I focus on for genuinely AI-native products: * Automation for Simplicity: AI's power should be used to abstract away underlying complexity. It should take raw data, complicated processes, etc., and deliver a clear, simple output or actionable insight to the user. * Proactive Value Delivery: The AI shouldn't just sit there waiting for user input. It should proactively surface what's important, highlight changes, or suggest the 'next best action' without the user having to manually pull or analyze. * Built-in Adaptability: A truly AI-native product learns from the user and data patterns to adapt the experience over time, ideally simplifying onboarding and personalizing the workflow without requiring extensive manual configuration from the user. The core idea is to use AI to do the 'heavy lifting' the mundane, time-consuming tasks the user previously had to grapple with manually. The product should deliver the result, the insight, or the recommended action directly, rather than requiring the user to navigate complexity to find it. If integrating AI requires users to learn more steps or adds layers of complexity, it's likely missing the point. The real magic of AI-First is its potential to drastically lower cognitive load and accelerate time-to-value. It's less about the number of AI features, and more about how AI enables simplicity and proactive usefulness. Curious to hear your thoughts and experiences! As builders or users, what are the best examples you've seen of AI genuinely simplifying a product or workflow? Conversely, where has it added frustration? And importantly, what UX/product principles do you believe are non-negotiable when building truly AI-native experiences? Let's discuss!