Making has always required real effort. Even in the digital realm, that effort was bound by real constraints, and those constraints forced intentionality, shaping what got made and how we prioritize time and effort.
AI has changed that math significantly. The effort and constraints of making things like websites, campaigns, platforms, and interfaces have fallen to nearly zero. Anyone, anywhere, with the right prompts and the right tools can now produce what used to require months, a specialized team, and a hefty budget to accomplish.
That acceleration is remarkable, and it’s also the source of a real problem.
When anyone can make anything, the volume of things made expands enormously, and the proportion of that volume that actually matters shrinks. We are producing more today than at any point in human history, but output is outpacing value. There’s more content, more code, more campaigns, more product launches. And more noise.
Speed, it turns out, is a seductive proxy for progress. I’ve watched organizations ship faster and lose ground because it wasn’t the right thing to ship. Moving quickly in the wrong direction is still moving in the wrong direction.
Huge has been in the business of making things for more than 25 years. When we started, everything was new. The Internet was a nascent medium. The bar was to make it commercially viable; we set ours higher: make something you love. The work was hard, the technology was developing, and the standard was set by the difficulty of the work itself. Then the web matured, the tools improved, and the challenges shifted. The standard became making things people love, which meant understanding the human being on the other end of what you were building. Experience took precedence. That was a meaningful upgrade.
But we’re in a different moment now. Making something people love isn’t a high enough standard when the tools to make anything are free, fast, and available to everyone. The question is no longer whether something can be made, or even whether people enjoy it in the moment. The question is whether it matters: to the business that needs it to perform, to the people whose lives it touches, to the world it lands in.
Mattering is a demanding standard. Something matters when it creates real advantage for a business and real value for the people using it. Work that earns attention. Products people miss when they’re gone. Experiences that solve something real instead of simply reflecting a trend.
The leaders and brands I talk with most often are in the middle of figuring this out. They’ve invested in platforms, data infrastructure, and AI tooling. They’ve hired for it. But they’re finding that the gap between what the technology can do and what is actually showing up for their customers is wider than expected. The technology didn’t automatically produce things that matter, and it never does. Technology amplifies intention. Give it unclear direction and you get more, faster, of the same things that weren’t working before.