Context-Aware AI Trip Planner

Overview

Independent web prototype · 1 month

I designed and built a trip-planning exploration around a short natural-language request, such as “Three days in Paris.” The interface then presents planning context and choices that can be refined as the trip takes shape.

My role covered interaction design and frontend implementation using Figma and Windsurf. The case demonstrates the prototype and design rationale; it does not establish a measured reduction in planning effort.

The Design Question

Early trip planning often begins with incomplete intent. I explored how to let someone start with a destination and duration, then refine priorities without completing a large configuration form first.

Key Design Decisions

Reveal detail as it becomes useful

Progressive disclosure keeps the starting task small. More context appears when it helps the next decision.

Trade-off: hidden detail must remain discoverable, particularly for people who want to set constraints at the start.

Make inferred context inspectable

The design surfaces trip context and explicit planning choices rather than asking users to accept an opaque itinerary.

Trade-off: a simpler first interaction increases the importance of correcting assumptions later. Automatic adaptation needs to stay predictable.

Keep the interface focused on decisions

I prioritized choosing a direction and refining it over displaying every possible feature. The prototype explores how layout and information density could follow emerging priorities.

Outcome & Next Steps

The deliverable is a web prototype showing the input-to-planning flow. Next, I would observe whether people can correct a misunderstood request, find their constraints, and explain why the interface changed.

Those checks would determine whether adaptation helps the task or makes the experience harder to predict.