I was trying to think of an analogy for a problem that has become very widespread these days.
The basic idea is that when you play a sport at an amateur level, you can get away with a lot of mistakes / sloppiness, and win by athleticism alone. But as you scale it up, and reach higher levels of difficulty, these same mistakes will cripple you and prevent you from advancing: you'll lose to people who may be less talented, but know how to do things properly.
And if you go on for too long that way, you'll be in a situation where you'll have to choose between being stuck at whatever point you max out at, and never progressing in the future, or being forced to go back to fundamentals and relearn everything from scratch, a very expensive and time-consuming process.
The reason why a good instructor is so harsh on these things isn't because they're mean or out to get you specifically (at least, not in most cases) but because weeding these mistakes out early saves a ton of time later, and at a small cost, compared to allowing them to fester.
The same is true for language acquisition, and really most types of learning in general.
Ironically enough, this can mean that sometimes the worst players at higher levels are the most gifted or talented ones, at the amateur level-- their raw talent allows them to avoid getting punished for mistakes, which means they never bother learning, and this in turn cripples them when they move up to a new level of difficulty where these trivial things actually do matter. (See the whole gifted student -> pizza deliverer pipeline for proof in another subject.)
The way that I see it being relevant for science is that often people with high IQs but no actual knowledge can experience a ton of success in life, without bothering to formally study anything. Unfortunately they then assume that the same combination of 'intuition + raw intelligence' will help them in building mental models or solving problems at much higher levels. But they are actually crippled by naive assumptions and sloppy habits which-- due to their lack of experience-- they cannot even detect (though a trained professional could), and so they are doomed to spend their time crashing into predictable walls, and getting stuck there forever.
Look at the ongoing and probably never-ending inflationary meltdown, or the AI bubble-- ultra-expensive models are constructed by pseudo-experts who congratulate themselves for their visionary genius, only to fail in the most basic and predictable ways.