Most organizations never learned to specify an outcome. They discovered what they wanted by building slowly, reviewing, and correcting, and the slowness disguised the gap. Dylan Pulver, an engineering leader and founder, describes what remains once AI removes the delay. “AI can play every instrument now, it can write the code,” he says, “but what it can’t do is know what the song should sound like.”
Pulver has co-founded multiple ventures, including a business-to-business payments platform for high-risk industries, shipped marketplace apps to the app stores, and built AI systems that carry entire back-office processes end-to-end. He also produces music in a home studio, and it took him years to recognize the two as one occupation.
Holding the Finished Version in Your Head
A session in Logic contains a hundred tracks, effects everywhere, and settings on everything. Pulver says the real skill is diving in regardless, tweaking and shaping, while keeping the finished song in mind throughout. Software presents the identical condition; a build at its midpoint is messy in every direction, and the builders who succeed are the ones eager to reach into it.
What makes that tolerable is knowing the destination, because chaos only reads as failure to someone who cannot picture the resolved state. This capacity was always the difference between senior builders and merely competent ones, and it stayed hidden while execution took long enough that everyone attributed the difficulty to the labor.
The Listener Is the Only Judge
Nobody hears the hundred tracks; they only hear one song. Pulver holds his products to the same standard, observing that nobody sees the code while everybody feels the result. Maintaining that discipline is harder than it appears, since effort inside a system is invisible from outside it and teams argue endlessly about components users will never encounter. Architectural elegance, clever approaches, and difficult problems register with nobody beyond the people who built them. Only the experience reaches the customer.
Components That Do Not Compete
Pulver describes a mix as a puzzle of frequencies, with bass holding the low end, guitars occupying the middle range, and vocals needing room to cut through. The craft lies in making everything mesh, carving space with equalization and ducking one sound so another can breathe.
Software poses the same puzzle, where every component requires its own lane and clean seams with its neighbors. His formulation names the failure exactly. Great systems, like great mixes, do not compete with themselves. Components contending for the same responsibility produce the software equivalent of a muddy recording: technically complete and indistinct throughout.
Specification Became the Constraint
Taste is a scarce resource, in Pulver’s assessment, and the builders who thrive will think like engineers and work like artists. The organizational implication is sharper than the individual one. A company that discovered its requirements through slow iteration had a functioning process, however inefficient, because each review cycle refined an outcome nobody could state at the outset.
Compress the build to hours, and that refinement disappears along with the delay, leaving teams generating enormous volumes of work against specifications they never disciplined themselves to write. This is why so many AI initiatives produce output that technically satisfies the request and satisfies nobody.
Pulver’s prescription addresses this; he urges asking the artist a question first, meaning what this should feel like when finished, and then engineer toward the answer. A machine capable of building anything returns very little to an organization that cannot say what it wants. To learn more, connect with Dylan Pulver on LinkedIn.
