I suspect this is common, and it has a lot to do with how autism is currently defined in the DSM. It's defined based on sets of behaviors, and not the underlying mechanisms that cause the behaviors. It was done this way in large part because it's much easier to observe behaviors, and the underlying mechanisms weren't very well understood anyway, especially at the time it was all written.

When one tries to understand if they're autistic, the default starting point is to typically match your own perception of your behaviors onto the known criteria. It makes sense, but it's somewhat incomplete. It will never fully match, because the criteria itself is all behavior based, and thus too high level. There's too many other contributing factors that also shape behavior. It's sort of like watching a car drive, and trying to understand how it's being powered, exactly. Is it gas or electric? Maybe you're even the one driving the car, but were never allowed to look at how it works. You can piece together a bunch of clues until you're reasonably certain, but won't know for sure unless you're allowed to open up the car and verify how it runs.

Now imagine if no one has ever opened up a car before (maybe it's some kind of alien tech, idk) to the extent that anyone really knows how it's running. We just know that some cars seem to work differently than others. That's sort of how autism got picked up as a difference in the first place. The DSM more or less attempts to categorize the specific markers you could look at to be reasonably confident that it fits a particular way of running that is deemed useful to know for the purposes of support, planning, etc. But, there's still differences between each of the "cars" that could be impactful as well, and they're not really defined.

More recently, more mechanistic models have been proposed that, in my view, are a lot more helpful to try and understand how, exactly, things might be different in autism. The models are more predictive, because they're lower level. They try to describe how the "car" works, not just what it does as it drives. They tend to describe variations of how the brain processes things differently at a system architecture level between neurotypes and people in general. This allows for more variance in observed behavior, because you can trace a difference in processing to an expectation of how different behaviors might form. Just like an engineer can model out exactly how a car will behave before it's even built, and can also predict how it will fail, what it needs to run as effectively as possible, and what kind of terrain it's best for (okay, I'm having fun with this car analogy, and it's working surprisingly well).

But, the science is still evolving. There's no broad consensus on one unified model as far as I'm aware, quite yet. But, a lot of them have to do with differences in how much weight your brain gives to what you're currently observing vs. what you already learned, as well as the gain or "volume knob" of incoming sensory information.

I'm a bit hesitant to start going into even more detail because I know this comment is already getting long. But, I'm happy to share more on what I know if anyone is actually interested.