AI for Music Producers
Aiode – AI Music UI UX Design Case Study
Spent two years improving Aiode’s UX, website, and landing pages, making music creation easier and contributing to the company’s growth.
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My Role
- AI-Focused Product Designer
- Interaction Design
- Social Media Campaign Design
- Emailer Design
- Landing Page Design
- WordPress Website Redesign & Development
- Webflow Conversion for Landing Pages
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Project Overview
Timeline
March 2024 – March 2026
Platform
Web/Desktop Application
Focus Areas
Creative workflow optimization, interaction design, AI-assisted music creation, product-led growth, and marketing assets design.
Bringing clarity and speed to a complex AI-powered music creation app
When I joined, the product was growing quickly. New features were being added, but the experience lacked structure. The platform felt fragmented, and the marketing side did not reflect the product’s strength.
Aiode Brandbook
Aiode Product Design Challenges & Solutions
1. Bringing Structure to Music Creation
Users had to move between different sections to compose, edit, and perform. This broke the creative flow.
I redesigned the experience into a single working area where users could:
- create music
- edit tracks
- manage virtual musicians
All without switching contexts.
Impact
- Reduced context switching
- Longer uninterrupted creation sessions
- ~20–30% improvement in task completion (estimated)
2. Making Features Easier to Understand
New features like Layers and Sample Remaker were added without a clear system.
I introduced a simple visual structure using color and placement:
- Layers in green
- Sample Remaker in blue
- Generated tracks in purple
This made the timeline easier to read and reduced confusion.
Impact
- Quicker adoption of new features
- Faster feature recognition
- Lower onboarding friction
- Fewer support queries
3. Reducing Effort in Key Actions
Music creation requires quick iteration. The existing flow had too many steps.
I introduced a simple visual structure using color and placement:
- Layers in green
- Sample Remaker in blue
- Generated tracks in purple
This made the timeline easier to read and reduced confusion.
Impact
- Quicker adoption of new features
- Faster feature recognition
- Lower onboarding friction
- Fewer support queries
