Ask LitCharts AI

Ask AI was LitCharts' first step into AI. I designed the feature end-to-end, building a component system that went on to support three additional AI tools, driving a 75% higher conversion than the company's previous top-performing feature.

My role

I led the end-to-end design of Ask AI, from defining the interaction model to building a scalable component system. I collaborated closely with engineering and product to scope the MVP and specify future AI tools.

Expert-written guides + the power of AI

LitCharts serves millions of students and teachers looking to understand literature through expert-written guides; Ask AI made that experience smarter.

Built to scale

I designed the form to accommodate 3–4 input fields, knowing that future AI tools would need similar input patterns. This meant aligning with engineering early on on what a scalable component architecture would look like, so we wouldn't rebuild from scratch each time. 

User feedback across all stages

I mapped every state a user would encounter and designed with intention—error states written to reduce friction, and a rate-limit state that tells users why the feature is unavailable and when it resets, so they feel informed rather than just blocked.

Responsive across breakpoints

I designed using a mobile-first framework and tested across all breakpoints. The goal was that the experience felt equally native on a phone as it did on desktop.

The result

I led the end-to-end design of Ask AI, from defining the interaction model to building a scalable component system. I collaborated closely with engineering and product to scope the MVP and anticipate future AI features.

What I learned

Designing AI features requires you to design for uncertainty in a way most product work doesn't. The biggest shift for me was moving from "what does this do?" to "what does the user think this does?" and making sure those two things were as close as possible.

LET'S TALK

zainabhasan77@gmail.com

© Zainab Hasan 2026