Personalized AI Mentor
Role: Founder, Product Designer, UX Strategist, Concept Creator
Platform: Desktop Web App
Timeline: 2024 | (Research → System Design → Prototype)
Keywords: AI/LLM, UX Strategy, Conversational UX, EdTech, Narrative Design, HCI
Summary
GAUDI is a conceptual AI driven platform designed to reimagine how architecture students receive feedback, mentorship, and guided learning. Built as a self initiated case study, GAUDI explores how large language models and conversational UX can bridge the gap between architectural theory and hands on design practice.
The project showcases my ability to design intelligent systems, apply emerging technologies to user needs, and deliver a premium, narrative driven user experience, all crucial for product teams at scale.
[This case study showcases my ability to translate AI and emerging technologies into emotionally resonant, system-level user experiences, a crucial strength for teams building future facing educational or creative platforms.]
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Architecture education is often limited by inconsistent feedback, rigid curricula, and a lack of personalized mentorship. Students struggle to:
Receive actionable design critique
Understand their growth over time
Connect abstract theory to real design execution
Traditional platforms provide static resources. Studio time is limited. Personalized mentorship is rare.
With the advancement of AI and conversational interfaces, there is a powerful opportunity to:
Deliver individualized feedback
Build reflective design habits
Align personal growth with architectural history
GAUDI proposes a new model: mentorship as a scalable, intelligent, and emotionally resonant product experience.
In user interviews with 10 architecture students, 80% said they lacked consistent feedback and didn’t know if they were “getting better.” one student shared: “I just want someone to tell me what’s working in my design, and where I need to grow.”
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The platform was structured to simulate a long term academic journey; integrating learning, critique, and emotional self-reflection over time. The product was built on four core design principles:
1. Mentorship as Interface
The entire UX is designed as a dialogue, with a mentor that adapts to the student’s tone, skill level, and goals.
2. Narrative Learning Timeline
Users progress through architectural eras, Classical to Parametric, guided by point cloud portraits of iconic architects.
3. Feedback Looping
Design uploads generate contextual critique (form, spatial logic, clarity). All feedback is saved, categorized, and reflected on.
4. Reflection Infrastructure
A built in Notebook helps students journal, revisit feedback, and even forecast their own design evolution.
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Typography: Inter (UI), Open Sans (body), inspired by editorial architecture journals
Color: Charcoal (#121212), Deep Blue (#0C1F3F), Neon Blue Glow (#37C2FF)
Layout: 12 column grid, 8px spacing, flexible components for cards, feedback blocks, and chat
Metaphors: Particle systems and point cloud visuals to represent the “dematerialization” of architectural space
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Defined product scope and system logic
Designed the conversational UX and tone personas
Created user journey, interface flows, and UI in Figma
Built narrative learning framework across historical eras
Crafted point-cloud visual metaphors and feedback structures
Led competitive and LLM use-case analysis
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AI Mentor Persona System Inspired by how students relate to different studio professors, the mentor adapts tone and language to match learning style.
Design Upload & Feedback Loop Upload triggers contextual feedback, visually mapped to design categories like proportion, clarity, and spatial logic.
Timeline Navigation Encourages long term growth by framing progress within architectural history (from Classical to Parametric).
Notebook for reflective journaling, portfolio building, and AI summarized feedback
Design Forecast tool that predicts style direction and future readiness based on design input
Minimal dark mode UI using deep blue, charcoal, and glowing accent tones
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‘‘A 1st year student uploads a modernist house. The AI mentor critiques spatial rhythm and references Corbusier. Over time, the student builds a portfolio of feedback notes, patterns, and self reflection entries. exporting it as a design growth report.’’
A student begins by selecting their skill level, learning goals, and aesthetic interest (e.g., Parametric, Brutalism)
As they upload work and receive AI feedback, their progress is plotted across a historical timeline of architectural styles
The AI mentor adapts over time, providing thematic suggestions, quotes from past architects, and reflective critique prompts
Students can export their journey as a visual PDF portfolio or share notebook entries for academic reviews
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Delivered a fully interactive prototype and high-fidelity design system using Figma
Created a strategic UX case study demonstrating full-cycle thinking from problem definition to interface aesthetics
Project praised by design mentors and peers for its originality, scalability, and narrative-driven interaction model
Used this case to apply to senior-level product and UX design roles at design-led companies and tech innovators
Selected as a standout concept and Received 20+ messages from peers asking if it will launch