I came up in music before everything went fully digital.
I learned recording in analog studios where tape was finite, decisions mattered, and commitment was part of the craft. I worked across multiple eras and cities — from early multi-track systems and sampling keyboards to large-format tape, then into the digital shift that rewrote the industry entirely. I studied music business when the old rules still applied — and lived through watching them disappear.
I didn't arrive at AI as a shortcut. I arrived at it through decades of adapting to changing tools while protecting authorship.
Throughout my career, musicians have always modeled other musicians — singers studying phrasing, drummers internalizing feel, guitarists chasing tone. That's not new. What's new is that modeling has become explicit.
Today, I use AI as part of a creative feedback loop: prompting, responding, refining, and taking responsibility for the final work. While platforms introduce elements of variation and randomness, the core decisions — melody, lyrics, emotional direction, and what ultimately gets released — remain human.
Any vocals that aren't my physical voice are still extensions of my musical identity: my melodies, my words, my intent, my taste.
The tools evolve. The authorship doesn't.
