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"A" for "Average"

In an essay published on 2026-08-25, the author argues that large language models (LLMs) are 'big averaging machines' that produce average results by design, and that users' perception of AI quality is skewed by their own familiarity with the subject. The author notes that while AI can be a productivity boost, its output is not objectively better in unfamiliar contexts, just more impressive to those who lack expertise.

read2 min views1 publishedAug 26, 2026
"A" for "Average"
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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.

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LIVE [news/a-for-average] indexed:0 read:2min 2026-08-26 ·