LEA — Life Exploration Assistant

What inspired us

We were inspired by how often people have to make major life decisions without fully understanding their long-term impact. This is especially true for decisions around career, health, and timing, where the consequences are not immediate and information is often fragmented.

For example, many young women face trade-offs between career growth and long-term health or fertility, but there is no single place that helps them explore these choices in a clear and realistic way. Most existing tools either focus only on productivity or only on health, without connecting the two.

We wanted to create something that helps users think ahead by asking a simple question: what could my life look like if I make this choice today?

How we built our project

We built LEA as a scenario-based life simulation app.

At its core, the app is structured around episodes. Each episode represents a realistic life situation and contains:

a short narrative setup
multiple decision options
branching outcomes based on the user’s choice

These scenarios are stored in a structured format, allowing us to scale and add more situations over time.

The decision system follows a simple model:

[ \text{Next State} = f(\text{Current State}, \text{User Choice}) ]

Each choice updates aspects of the user’s state, such as stress, health, or career progression, which then influences future episodes.

On the frontend, we used React Native (Expo) to create a mobile-first experience. The interface is designed to feel like a guided story rather than a form, with short, natural interactions.

We also used AI tools to help generate realistic scenarios and variations, ensuring that the content remains diverse and relatable.

Challenges we faced

One major challenge was avoiding making the app feel like a questionnaire. Early versions were too rigid and felt like answering survey questions. We addressed this by shifting to a narrative-driven format with more natural language and fewer but more meaningful choices.

Another challenge was balancing realism with sensitivity. The topics we cover, such as health and long-term consequences, can easily become overwhelming. We had to ensure that the scenarios felt realistic without being alarmist, focusing on gradual changes rather than extreme outcomes.

Designing meaningful choices was also difficult. In real life, decisions rarely have a clearly correct answer. We had to ensure that each option felt valid while still leading to different and believable outcomes.

What we learned

We learned that users do not necessarily need more information, but better ways to understand and apply it to their own lives.

We also found that small, everyday decisions are easier for users to engage with, and over time, these decisions can illustrate larger patterns and consequences.

Finally, we learned that presenting decisions through storytelling is more effective than presenting them as data or instructions, as it makes the experience more intuitive and relatable.