A Socratic teaching tool that follows curiosity, not curriculum
As a student, I was trained to play the formal education game—flashcards, diagrams, fastidiously organized notes. But as a 32-year-old, I’m disappointed by the knowledge and understanding I’ve retained over time. And without the familiar game of formal education to play, I’m often at a loss for how to learn new topics that are interesting but intimidating to me. AI has the potential to change the way people learn, and existing tools show promise. But I’m still dissatisfied—these tools often dump knowledge on me without helping me integrate it into my understanding. --- I built Stella to…
In plain words
Stella is an AI learning tool designed for adults tackling subjects that interest but intimidate them. Rather than delivering information directly, it uses Socratic questioning to guide learners through curiosity-driven exploration. The tool separates thinking spaces and emphasizes genuine understanding over information dumping, helping users integrate new knowledge meaningfully instead of relying on traditional study methods like flashcards or memorization.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
As a student, I was trained to play the formal education game—flashcards, diagrams, fastidiously organized notes. But as a 32-year-old, I’m disappointed by the knowledge and understanding I’ve retained over time. And without the familiar game of formal education to play, I’m often at a loss for how to learn new topics that are interesting but intimidating to me. AI has the potential to change the way people learn, and existing tools show promise. But I’m still dissatisfied—these tools often dump knowledge on me without helping me integrate it into my understanding. --- I built Stella to explore how thoughtful UX can transform AI interactions into genuine learning experiences. Instead of optimizing for information delivery, Stella optimizes for learning through curiosity. Some key design decisions that emerged from testing: 1. Separated thinking spaces: Most AI chats blur the line between user and AI thoughts. Stella's chat interface creates distinct spaces for communication, encouraging users to reflect on their own thinking before engaging with AI responses. 2. Socratic dialogue patterns: Rather than just delivering answers, Stella guides users to discover knowledge gaps and build on existing understanding. This creates more durable learning moments. 3. Interest-aware conversations: Users can highlight interesting concepts, and Stella adapts the conversation to explore these areas more deeply. Learning follows natural curiosity rather than a predetermined path. Early users have reported unexpected learning moments—from a Computer Science PhD finally understanding “weak form” to a doctor exploring what it is about Quaker philosophy that inspires her work. --- Technical implementation focuses on thoughtful UX that extracts practical value from existing LLM capabilities. Stella uses Claude for dialogue but innovates in how these interactions are structured and presented. The interface is built in React, with a backend that adjusts to user interest and existing understanding. Some interesting challenges solved: - Balancing guidance vs. independent thinking - Tracking the user’s level of interest and curiosity - Creating meaningful conversation paths that lead to new understanding --- I’m currently looking for feedback from: - Educators interested in AI learning tools - Developers exploring new UX paradigms for AI - Curious minds who enjoy deep learning conversations Currently opening Stella for limited beta testing. Looking for 20–30 people who want to explore topics deeply and provide feedback on the learning experience. If you're interested in trying it out, sign up here: https://krelb9yoq56.typeform.com/to/Ild6JaQD I'm particularly interested in hearing how the interface affects how much you actually learn and retain compared to traditional LLM chatbots. Happy to discuss more in the comments!
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