AI Guides › Trend Watch
By Nigel Guy · 3 min read
It's easy to assume that whoever tried a tool first must be the best at using it. They have the head start, the screenshots, the confident opinions. So you measure yourself against them and feel behind. But being early and being good are different skills, and they often pull in opposite directions: early adopters are optimised for trying things, not for getting sustained value out of any one of them.
The rule: the people who get the most from an AI tool are usually the ones who adopted it for a specific job and stuck with it long enough to learn its limits — not the ones who got there first.
Early adopters tend to spend their attention on breadth. They see many tools, form quick first impressions, and move on when the next one arrives. That's valuable for mapping what exists. It's less good for building depth, because depth comes from repeated use on real work — including the dull, frustrating stretches where you learn what the tool gets wrong and how to work around it.
The person who picked up the same tool months later, used it daily for one clear purpose, and built a small, reliable routine around it often knows more about its practical value than anyone who reviewed it on launch day.
These are the habits that make someone a genuinely good user, whenever they started. None of them depends on being early.
Skip comparing yourself to people whose main output is first impressions of new tools — that's a different job from yours. Skip the pressure to have an opinion about every release. And skip treating "I've used it since the beginning" as a credential, whether it's yours or someone else's; ask what they've actually built with it instead.