Aura Music

Client

Personal Project—Product Development

Role

Product Design

Year

2025

Creating a AI Sound Companion: Aura Music Born from my personal need as an aspiring songwriter who struggled with the time, complexity, and cost of traditional music learning, this project tackles the issue of creative friction. Existing AI tools automate the whole song, but I wanted a product that acts as an intelligent, collaborative producer. One that helps refine my idea while simultaneously teaching me music theory. Utilizing my expertise in conversational AI, I designed Aura Music to take a vague musical spark and, through conversational prompts, structure it into an editable sketch. Over two intensive weeks, I took this personal need from a concept to a high-fidelity prototype, proving a seamless, guided path for songwriters to finally bring their ideas to life.

Watch Prototype Walkthrouh Video 🎶

PROBLEM

The creative friction for aspiring musicians is too high.

Beginner and aspiring songwriters, like myself, frequently stall in the early stages of music creation.
We have musical ideas but lack the consistent time, space, and technical knowledge to transform them into structured sketches.

Current solutions often fall short:

Traditional Lessons are costly and incompatible with demanding work/life schedules.
Existing AI Music Generators offer instant, full songs but remove the musician from the creative process, offering little control or opportunity for personal growth.

This results in countless musical ideas being abandoned, leaving the musician feeling stuck on the basics and overwhelmed by complex music theory. There is a clear need for a tool that bridges the gap, allowing musicians to maintain their creative ownership while providing intelligent, supportive guidance.

•Suno
•Artlist
•ElevenLabs
•Producer AI
•OpenBeat AI
•many more…

TASK OBJECTIVE

To design and prototype Aura Music, an AI-powered co-creation platform that serves as a personal music producer and theory mentor.

The objective was to create an easy-to-use, conversational interface that allows an aspiring musician to:

Develop an Idea: Quickly turn a nascent musical spark (like a voice memo or simple concept) into a structured, editable musical sketch.
Maintain Creative Control: Integrate the user's "musicianship" by offering collaborative guidance instead of instant, full-song generation.
Facilitate Learning: Provide relevant, context-specific music theory insights to build the user's knowledge base as they create.

Ultimately, the goal was to reduce creative friction and help users progress their music from initial thought to a complete, shareable voice memo/prototype sketch for future development.

PROJECT OUTLINE, DURATION, and PROCESS

✨ Project Outline & Scope

Project Focus: UX Research, Concept Development, Conversational AI Model Design, Information Architecture, Wireframing, High-Fidelity Prototyping, and Visual Design.
Core Features: Conversational AI Producer (Idea Interpretation), Sketch Generation & Editing, Music Theory Integration, Voice Memo/Draft Saving.
Target User: Beginner to intermediate musicians/songwriters with full-time jobs who need an efficient, guided, and educational music creation process.

⏱️ Project Duration

Total Time: 2 Weeks (Concept to High-Fidelity Prototype)

Phase	Duration	Focus
Phase 1: Planning & Structure	1 Week	Problem validation, goal setting, core features, information architecture, and low-fidelity wireframes.
Phase 2: Design & Refinement	1 Week	High-fidelity visuals, UI design, interaction refinement, and final prototype creation.

🛠️ Process & Tools

The project followed a rapid ideation and prototyping process, heavily leveraging AI for strategic support and design solutions.

Step	Detail	AI/Tool Utilization
1. Ideation & Concept	Defining the core user need (my own experience) and articulating the concept of an AI "producer."	Google Gemini: Refined the initial idea into a formal project proposal and defined core user profiles.
2. Structural Design	Creating the user journey, site map, and structural layout of the app's key screens.	Google Gemini: Assisted with UX writing, user journey mapping, and conversational flow definition.
3. Wireframing & UI	Sketching out core functions and developing lo-fi and mid-fi wireframes to solidify the interaction model.	Google Stitch: Used to explore and validate structural UI solutions when facing design bottlenecks.
4. Visual & Prototyping	Applying visual style, designing high-fidelity screens, and creating the interactive prototype.	Google ImageFX: Used for visual inspiration and creating background/asset elements for the final design.
5. Post-Project	Preparing the concept for implementation.	Currently vibe-coding and seeking a development partner to bring the prototype to life.

🧠 Key Takeaways from the Project

AI is a Co-Pilot, Not a Replacement for Creativity:
The core challenge was designing an AI experience that supports human creativity rather than replacing it. I learned that for tools targeted at creators, the interface must prioritize control and iteration over instant, full-automation. The conversational model was crucial for achieving this balanced, human-centered interaction.

The Value of Conversational UX in Complex Domains: Music theory and composition are intimidating subjects. By framing the interaction as a dialogue with an "AI Producer," I learned how a conversational UI can effectively simplify complex tasks. It allows users to express intent in natural language, enabling the AI to retrieve and apply vast musical knowledge without overwhelming the user with menus or jargon.
Leveraging AI for Rapid Prototyping and Strategic Design: This project demonstrated the power of treating generative AI (like Google Gemini and Stitch) as a strategic design partner. Using it to validate proposals, refine UX writing, and solve UI structural problems significantly accelerated the entire process. This validated a more agile, AI-augmented design workflow, allowing me to complete a robust concept and prototype in just two weeks.