Personal experiment · Brand & Product · 2026
TUNER_01
Find the still point.
A small personal experiment. I wanted a tuner that is quick to understand, focused on the essentials and still has a character of its own. The result is TUNER_01: a minimal Android app with a large note, a clear pitch trace and a deliberately distinctive visual language.
- Contribution
- Concept, brand & interaction design. AI-assisted prototyping.
- Context
- Personal project / 2026
- Status
- Functional Android prototype
01Product
The note first. Stillness after.
The note leads. Frequency and cents follow. Inside the tuning tolerance, the measurement block closes. No green checkmark, no confetti.
01 / Tension
02 / Stillness
02Identity
Two colours. One clear character.
Signal orange, a heavy note and technical mono typography. An interface that feels like an instrument, not a dashboard.
LESS
NOISE.
MORE
NOTE.
Presentation only / PAPER
Grotesk / Note
Aa / E♭ / 01JetBrains Mono / Readings
A4 = 440 Hz / ±05¢Tension → Stillness
03Interaction
Less on the screen. More room to tune.
The trace gets space. Everything else stays within reach, but outside the live measurement view.
One screen. No jumping.
Fixed positions for readings and trace. Additional options open on a separate page.
Pause is visible.
Only the trace freezes. Measurement and status stay live.
Start first. Ask when ready.
Four short steps. Microphone access is only requested after an explicit action.
04In context
For the moment before playing.
Status & Learning
Reduction is not about the number of features. It is about hierarchy.
Designed and built as a native Android prototype. External usability and accuracy testing are still pending.
Implementation & image credits
My contribution: concept, visual identity and interaction design. The native Kotlin and Jetpack Compose implementation was developed with AI-assisted coding support.
The screens are native Paparazzi UI renders with scripted detector values. They show interface states, not measured microphone accuracy. Pitch detection in the prototype runs locally on the device.
The two photo mockups were AI-generated and composited with the native app interface. They illustrate the product context and are not photos from user testing.
