MVP – Tree Search to Spark Curiosity
Hi Everyone,
I have been working on this MVP site:https://curiouslearn.zypedu.in/home
Please let me know what you think of it ?
Not all searches are created equal.
Each platform shapes the way we think, search, and learn.
Google – Great for quick answers and transactional queries. Usage pattern: Users skim multiple links, jump between tabs, and often leave with half-answered questions. Fact: According to Nielsen Norman Group, users spend only 10-20 seconds on a web page before bouncing.
ChatGPT – Excellent for natural conversations and contextual answers. Usage pattern: Users ask a question and get an answer, but often don’t dive deeper unless they know what to ask next. Fact: Studies show most ChatGPT conversations end within 1-2 turns, limiting depth.
Perplexity AI – Blends conversational search with sources. Usage pattern: Great for citation-backed answers, but still follows a flat Q&A format without a structured path for exploration.
But what if you don’t know the right questions to ask? What if you want to go beyond surface-level answers and truly learn a topic in depth?
That’s where Tree-Search Learning comes in.
Inspired by algorithms used in decision-making and AI, Tree Search doesn't stop at one question. It unlocks a path of meaningful follow-up questions, like a personal mentor guiding you through layers of understanding.
Perfect for:
Curious learners who want to master a topic
Students doing deep research
Professionals exploring new domains
Anyone who loves to learn, not just skim
Try it out live – generate your AI-powered curiosity tree.