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Average Is All You Need

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Why This Matters

This article highlights how large language models (LLMs) are democratizing access to creating and managing 'average' content and data tasks, making previously complex or expensive processes more accessible and efficient. For the tech industry and consumers, this shift signifies a move towards more user-friendly, AI-powered tools that can handle routine tasks, freeing humans to focus on more creative or strategic work.

Key Takeaways

April 13, 2026 · 6 min read · Editorial

Average Is All You Need

LLMs will make more of your average stuff. And that's OK.

This is not going to be much of a hot take but whether we like it or not, whether we want to admit it or not: LLMs have eaten the world.

They first had a go at creative fields where they essentially made everyone capable of publishing an average text with some average ideas for an average audience, but incredibly fast and easy. Whereas before, average was expensive in terms of both time and effort, average became cheap.

Software is now getting the same treatment. Very likely other fields are going to experience the same average treatment; and bets are high on everything text and based on descriptive textual semantics (IP, lawyers, translators, Marvel movies...)

Now there is nothing inherently bad about average stuff, it sits, by definition, in the middle of the normal distribution of stuff. It is in fact amazing that anyone can now create average things whereas before they had to fight hard for sub-par; they now have to settle for average or do better and try to think about it.

I can't draw. But now, I still can't draw, but better.

Data is the same problem, but better.

Here is the thing about data: your intuitive knowledge of what you want from it is much higher than average. You know what is in your organisation's data and you can likely "feel" what is hidden in it. You just do not necessarily know how to get the information out of it effectively; most people do not write SQL that well, do not understand syncing strategies that intuitively, do not know how to generate charts that nicely.

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