AI is not exactly IT

This article is written by a human.

While looking for job openings, I realized that something had changed—someone didn’t just build a new mechanism, but installed a new mod on the server.

A new "era" has arrived, and not everyone has realized it yet. Many still look at AI as an ordinary IT product, somewhat like a video hosting platform, an editor, or another convenient service. But this is already too narrow a view.

First, let's establish a simple point: a neural network as a product is a tool. To create it, mathematicians, programmers, linguists, biologists, and researchers from other fields are needed. Yes, a specific neural network is an IT product. But AI, in general, is already more than just one class of products. If we look at it more broadly, it’s a separate domain, comparable to IT in terms of influence but not replacing it.

AI is not just another convenient service. It’s an infrastructural shift, it’s a phenomenon. Just as electricity, the internet, and mobile communication were revolutionary at their time.

The first thing I want to say is that a user of an AI product who uses it for development is not a programmer or coder. I believe the term “vibe coder” is incorrect. The mere fact of using AI for development does not make someone a programmer, just like a channel about IT doesn’t make the author an engineer. In general, vibe coding is more about the vibe of development, not the approach. And the result of the work does not prove the profession; for example, hackers and white hackers have very similar work, but they are completely different fields, and the result is similar – they found a vulnerability.

AI is a very large field that covers many areas and can exist separately from IT. In theory, you can create an ultra-basic mechanical neural network (like typewriters and calculators), and here, mathematics and physics will dominate, not IT.

We all know the slang word it-shnik – this refers to a specialist from the IT field. They are directly involved in the process of creating IT products. They can be a programmer but not know how a processor works, how a transistor is built, or even how an interpreter/compiler works.

Against this background, I want to introduce a new slang term in this article – aishnik.

An AI specialist is a professional in the AI field. They are not necessarily a neural network developer, prompt engineer, or researcher. But they professionally solve practical tasks using AI and are embedded in processes where AI is the primary working tool. For example, in the traditional world, we had an artist who knew about colors, types of paints, styles, etc., even if they only painted anime. In the AI field, this would be an AI specialist who creates images using AI for a specific purpose, such as memes. They may know all AI tools for images, or they may know just one. This would be kind of an AI gradle.

And if you think about it, this is exactly what we were missing. It's about properly dividing the unknown that has invaded our lives. Even most developers didn't fully understand what neural networks actually are.

There is particular confusion with vibe programming. By the way, about that. Not vibe coder, but AI specialist developer. Essentially, someone who thinks and solves tasks, but no longer at the code level. This is not a separate position/specialization in IT, but rather a mixed one, because we have a lot of other directions that AI products can cover. Now we don't have to lump everyone into the vibe coder category. One produces neural slop. Another works professionally through AI.

A person can create a bot using a constructor. They can create a bot using AI. They may not know programming at all. But the result will be there. And here’s where the main point begins: the existence of a result no longer proves belonging to IT. It may prove belonging to the new AI field.

AI is not a replacement for IT; it’s automation. There are machines that assemble chairs, perform operations by eye, but there are also handmade items. Programmers should be valued more highly, like paintings by famous artists, poems, and books by legendary writers. Because the AI field is not about quality, not about uniqueness; it’s about automation, production. That is, not custom production, but mass production of acceptable results. This can be observed in articles: how a person created yet another CRUD in one day.

The issue of quality is already clear to everyone: AI gives results quickly, on a large scale, and often sufficiently well, but not yet at a level to eliminate deep engineering work. Therefore, even if AGI appears one day, IT will not die.