# "A" for "Average"

> Source: <https://stitcher.io/blog/a-for-average>
> Published: 2026-08-26 05:01:51+00:00

# "A" for "Average"

Written on 2026-08-25Ask AI to write something in a language I're familiar with, and… well I'm never super impressed. Yes, it works, yes it needs finetuning and polishing. That's fine though, it can be a huge productivity boost to help get you started.

Ask AI to write something in a language I don't know, and… my mind is blown 🤯. "How can it possibly be that something *I* don't understand, AI does so flawlessly??"

Now, taking that first experience into account, how big do you think the chances are that AI just *happens* to be a master in a technology I don't know, while it was average in a technology I do know?

Or… could it be that the quality of both contexts is the same, but *I* simply am more impressed by one of them because *my* understanding of that second context is much more limited? It's like a magic trick that's impressive as long as you don't know how it works.

What I find crucial to remember in this era of AI is that LLMs are essentially big averaging machines. They predict the next word based on what's most likely within a context. That is it. Don't get me wrong: we can do amazing things with simple technology; we can even turn something as simple as 1 and 0 into whole computer systems. The point isn't that AI is either good or bad, the point is that — by design — it will lead to an average result at best.

Of course, "average" — by definition — means that some people will be *below* average, just like me when it comes to using a language I don't know. That doesn't make the result objectively better though. It's still average, overall.

Let's not forget that.