music application
Using AI to Turn a Vague Product Vision into a Working Prototype
A complex concept became a functional, high-fidelity product prototype that could be experienced, tested, and explained clearly.
See it liveClient
Music Unfolded
Services
- Brand Design
- Product Design
- Agentic Prototyping
Industries
- Music & Entertainment
Date
What if every song came with its own documentary?
The Project
Not a podcast.
Not commentary.
Not Wikipedia.
A synchronized narrative experience that unfolds while the song is playing.
Every track becomes a story, a time capsule, a cultural artifact ... an emotional experience.
The listener doesn’t just hear the song.
They Unfold it.
Not commentary.
Not Wikipedia.
A synchronized narrative experience that unfolds while the song is playing.
Every track becomes a story, a time capsule, a cultural artifact ... an emotional experience.
The listener doesn’t just hear the song.
They Unfold it.
The Challenge
The Challenge
Music platforms have made listening more accessible, but they have flattened much of the context that once surrounded recorded music.
The product challenge was to determine how rich information could be surfaced without interrupting the listening experience.
The product challenge was to determine how rich information could be surfaced without interrupting the listening experience.
Turning an Ambitious Idea into a Buildable Product
My Approach
I began by framing the product as a zero-to-one challenge, using AI-assisted research to define the content structure, product behaviour, and interaction logic. From there, I built high-fidelity prototypes in Cursor and Claude Code, testing states, timing, transitions, and content hierarchy in a working experience. The prototype became more than a visual demonstration: it helped clarify the product direction, expose edge cases, and give engineering a much more concrete foundation for implementation.
From Product Vision to Working Intelligence
What This Proved
This process transformed an abstract product strategy into a working interaction model that could be experienced, evaluated, and refined in real time.
AI accelerated both exploration and prototype fidelity, allowing me to move beyond static screens and demonstrate how the product would actually behave across content, states, timing, transitions, and edge cases.
By defining this logic as a reusable system, the prototype created a clearer direction for the product and gave future design and engineering decisions a much stronger foundation.
More broadly, the work reflects how the designer’s role is evolving: today, the right tools allow people with strong ideas to engage much more deeply with logic, behaviour, data, and implementation, elevating design into a more technical and consequential discipline.
AI accelerated both exploration and prototype fidelity, allowing me to move beyond static screens and demonstrate how the product would actually behave across content, states, timing, transitions, and edge cases.
By defining this logic as a reusable system, the prototype created a clearer direction for the product and gave future design and engineering decisions a much stronger foundation.
More broadly, the work reflects how the designer’s role is evolving: today, the right tools allow people with strong ideas to engage much more deeply with logic, behaviour, data, and implementation, elevating design into a more technical and consequential discipline.
Contact
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