Inspiration

I wanted a tool that helps people think, not one that simply hands out answers or teaches how to "copy". Most AI chats and tutorials solve problems directly, but I needed a brainstorming buddy that teaches how to reason. That idea became LogicHinter. Then I expanded the same concept for students and created StudyHinter—a playful, adaptive study companion.

What it does

LogicHinter guides users through code algorithm and gives insightful links once a correct option is chosen - without giving away solutions. StudyHinter generates quizzes, images, explanations, and difficulty-adaptive learning paths. Both apps turn AI into a structured, hint-driven teacher rather than a solution generator.

How I built it

I built a reusable FastAPI + React skeleton, added Gemini reasoning engines, designed strict prompt/validation pipelines, and wrapped everything in spooky, atmospheric Halloween UI. Two full applications—LogicHinter and StudyHinter—were generated from one clean architectural skeleton.

Challenges I ran into

Ensuring AI never reveals full solutions

Keeping JSON outputs structured and reliable

Integrating image enrichment and fallbacks

Designing two distinct apps from one codebase

Matching the Halloween theme without harming usability

Accomplishments that I'm proud of

Built two complete apps from one skeleton

Created a hint-only reasoning engine that actually teaches

Designed polished spooky UI with smooth interactions

Achieved consistent, production-ready AI behavior

Delivered a versatile system usable for coding, studying, and more

WhatI learned

Specs + strict prompts create predictable AI outputs

Reliable AI apps need validation layers and fallbacks

One skeleton can support multiple, fully unique applications

Good design enhances clarity—even with spooky themes.

Kiro works well when provided with screenshots and textual prompts.

What's next

Add more subjects and learning modes.

Turn LogicHinter into a full coding-interview coach.

Add multiplayer quizzes for StudyHinter.

Expand the skeleton into a general “hint-based learning engine”.

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