Morgan Erdman

Mirror

Conversational AI Project

Year

2026

Duration

7 weeks

Overview

Most students don't choose the wrong major because they lack information, but because they lack self-knowledge, or because they're quietly performing someone else's expectations.

Mirror is an AI-powered career and major advisor that builds a real psychological profile of each student through natural conversation, not generic quizzes. It asks the questions a great mentor would ask, remembers the answers, and delivers tailored recommendations grounded in real data.

Most students don't choose the wrong major because they lack information, but because they lack self-knowledge, or because they're quietly performing someone else's expectations.

My Role

Product Designer: I owned this end to end. The problem, the concept, the research, the visual direction, and every decision about how the product would work.

AI Interaction Designer: I designed how the user talks to the AI. The persona, the conversation flow, the guardrails, and the system prompt behind all of it.

Design Engineer: I built and refined the interface and backend in code, primarily in Cursor and Claude Code.

Product Designer: I owned this end to end. The problem, the concept, the research, the visual direction, and every decision about how the product would work.

AI Interaction Designer: I designed how the user talks to the AI. The persona, the conversation flow, the guardrails, and the system prompt behind all of it.

Design Engineer: I built and refined the interface and backend in code, primarily in Cursor and Claude Code.

Outcomes

90% Accuracy

Nearly all tested users who already had a chosen major reported that Mirror accurately gave them similar majors/careers to what they chose.

Discovery

A problem of identity, not information

Who did I want to help?

I wanted to help students who feel lost, who changed their major, or who got pushed into a path that never felt like theirs. My target users were 17 to 20, of any background.

When I researched the existing career and major quizzes, they all had the same flaw. They ask you to self-select interests from a list, then hand you a generic result. The students who need help most are the ones who don't yet know what they like.

I wanted to help students who feel lost, who changed their major, or who got pushed into a path that never felt like theirs. My target users were 17 to 20, of any background.

Listening to real students

I interviewed six students who had either switched majors or faced outside pressure around their choice.

The same themes came up again and again. Family expectations shaped their decisions. They didn't feel like they knew themselves well yet.

Almost none of them had used a career quiz, because the ones that exist felt too shallow to bother with..

I interviewed six students who had either switched majors or faced outside pressure around their choice.

The same themes came up again and again. Family expectations shaped their decisions. They didn't feel like they knew themselves well yet.

Almost none of them had used a career quiz, because the ones that exist felt too shallow to bother with..

Turning interviews into direction

Two clear signals shaped Mirror. Students wanted something conversational, not a button-clicking quiz. And they wanted to watch it understand them, so their answers didn't disappear into nothing.

I built two personas from these insights and used them as a gut-check for every design decision that followed.

Two clear signals shaped Mirror. Students wanted something conversational, not a button-clicking quiz. And they wanted to watch it understand them, so their answers didn't disappear into nothing.

I built two personas from these insights and used them as a gut-check for every design decision that followed.

Design

Working backwards on purpose

Refining in Cursor

I knew exactly the look and feel of the interface that I wanted, including fonts, colors, even layout before ever touching any tool.

Taking a new approach

I'd always worked wireframes, then Figma, then dev. This time I flipped it: I wrote a concept, turned it into a PRD, and used Claude Code to build the whole app first, then refined subtractively. I knew the tradeoffs of skipping wireframes, but I was confident I could refine from an existing design.

It was a test of my UX brain. Could I look at a finished, imperfect interface, pinpoint what was wrong, and iterate? I split the PRD into nine phases, and created a markdown file explaining how to implement each phase so the build checked in at every step instead of vanishing into one giant prompt.

Fixing the results page

The first results page was an information overload. I knew my users had shorter attention spans, and I knew it needed to be overhauled to displayed only the things that were important to the user.

Conversation

Crafting a intuitive AI experience

Designing the conversation

This was the heart of the project, and the first time I had ever designed an interaction with an AI.

I designed Mirror's persona to feel like a warm, grounded mentor. The conversation moves through three phases, but the user never sees a label or feels a transition. From their side, it just feels like a really good conversation.

Tuning the AI itself

Getting the conversation right took real iteration. Early on, Mirror asked too many follow-ups and lost track of where the user was. I also caught it leaking its internal reasoning into the visible chat, which I fixed in the system prompt.

Model choice mattered more than I expected. I tested across models and stuck with Opus, since its reasoning followed the system prompt far more reliably than the others.

Questions that reveal, not interrogate

Instead of asking "do you like math," Mirror asks scenario-based questions that surface personality without the user realizing they're being assessed. Things like walking through your ideal free Saturday, or how you'd handle two teammates who disagree.

Watching yourself take shape

As the conversation goes on, a profile sidebar fills in live: values, work style, interests, pressure flags. It gives users a sense of progress without a progress bar. You're not on question 12 of 20. You're watching a portrait of yourself form.

Keeping it in scope

I scope-locked Mirror to career and major advising only. When users go off-topic, it redirects warmly but firmly, like a focused mentor who stays on task because they care, not a system hitting a wall.

Delivery

The final build

The conversation

You can check out the interactive PDF here, or play around with the final organizational chart below!

The conversation

A one-on-one chat that opens warmly, asks layered questions, references what you said earlier, and never feels like a form.

Recommendations based on real data

Two to four tailored career paths, each one explaining why it fits by pointing to specific things you said. Salary ranges, job outlook, and AI replaceability are pulled from real sources, not made up.

A document to advocate with

Users can export a PDF of their profile and recommendations. This was deliberate. Many students are navigating family pressure, and a well-reasoned, data-backed document gives them something real to bring into that conversation.

Reflection

My Key Learnings

What did I learn?

Designing for AI is designing a personality.

This was my first time shaping an AI interaction, and most of the work lived in the system prompt, not the UI. Tone, pacing, when to push, and when to back off were all design decisions.

A finished build is just the starting point.

Building the whole app first and refining backwards felt strange at first, but it sharpened how I spot experience problems in something that already exists. The real product came from the iteration, not the first generation.

Thanks for Reading!

Check more of my projects, or reach out if you want to learn more about them!