The Engineer Who Stopped Thinking: Why We Are Losing the Ability to Analyze and What to Do About It

When I was just starting my career, my first mentor — Gennady Nikolaevich Podoprigora — told me a phrase that I have remembered for life and mentally repeat every time I face a complex task: "An engineer is not a person who knows everything. An engineer is someone who knows where to look, how to analyze, and how to apply information correctly." Almost nineteen years have passed working in and around field service, and I see more and more clearly how few specialists today, even those with many years of experience, meet this definition. They cannot find what they need, they do not analyze the data they obtain, and, most sadly, they are unable to apply knowledge in practice.

Helplessness in the Face of Documentation

This problem became especially apparent when I helped a business partner conduct interviews for engineering positions. People with experience, with resumes listing dozens of projects, could not answer elementary questions. Not tricky problems with a catch, but basic things that anyone who has ever worked with industrial equipment should know. Logic failed them. The simplest cause-and-effect relationships could not be established. And this is not an isolated case — it is systemic.

The same picture repeated itself at technical seminars and training sessions. I provide the audience with complete information, give them a real task from practice, and show them exactly where in the documentation to find the solution. We have just reviewed it together; the pages have not yet cooled from being flipped through. But as soon as I ask them to find the answer on their own — silence. People look at the documents as if seeing them for the first time. They cannot extract what is needed, cannot correlate what they have read with the task at hand, and cannot take the next step.

Narrow Specialization: A Comfortable Swamp or the Path to Degradation

Working for many years with foreign partners, I have noticed an important feature: specialists abroad are, as a rule, narrowly focused. An engineer working with instrumentation, for example, may have no idea what communication channels to use to transmit a signal to the "middle" level of automation. A temperature sensor specialist knows nothing about pressure sensors. They were not taught this, and they see no need for it. The European system of higher technical education has historically been oriented towards narrow specialization, and a bachelor's degree obtained under the Bologna Agreement is comparable in depth to secondary specialized education. The Russian system, on the other hand, has always trained a broad-profile specialist capable of solving diverse tasks.

Here, in the post-Soviet space, the situation was different for a long time. A classic instrumentation and automation engineer knew everything and could work with any more-or-less similar equipment. They understood principles rather than memorizing instructions for a specific model. They saw the system as a whole, not just a fragment of it. But now, when conducting training sessions, I sadly observe how this breadth is disappearing. People are increasingly taught narrowly focused disciplines. One step to the right, one step to the left — and the specialist no longer understands what is in front of them. They need a new course, a new certificate, a new permission. They are incapable of figuring it out on their own.

Yes, I understand the objections. When you have a lot of knowledge and spread yourself across dozens of areas, it is difficult to become a "mega-specialist" in any one thing. But that is not required. It is a false dilemma. The vast majority of industrial equipment operates on the same physical principles, is built according to similar logic, and very often is manufactured at the same factories, just with different nameplates. It is enough to understand the fundamental principles of operation, to see the logic of processes — and any equipment becomes accessible and understandable. Narrow knowledge is, of course, necessary, but it is acquired when you actually encounter a specific task. And here we return to my mentor's phrase. If you have a foundation, if you know how to search, analyze, and apply information, you will cope with any equipment, any system, any non-standard situation. If you cannot cope, then you are not a specialist at all.

In Western practice, there is the concept of the "T-shaped engineer" , proposed back in 1991. The stem of the "T" symbolizes deep expertise in one narrow area, while the top crossbar represents a broad outlook that allows collaboration with experts from other disciplines and the application of knowledge beyond one's specialization. The irony is that Western companies today are actively seeking precisely such specialists — with depth in one area but with the ability to understand adjacent fields. IBM, GE, and Procter & Gamble deliberately recruit engineers with T-shaped skills, expecting them to solve technical problems across the entire organization. Meanwhile, we, having a historically developed culture of broad engineering thinking, are beginning to drift into a dead-end narrowness.

Artificial Intelligence: A Crutch That Atrophies Thinking

I cannot ignore another factor that, in my opinion, exacerbates the situation. We live in an era when artificial intelligence is taking on more and more intellectual tasks. Research shows a worrying trend: developers using AI assistants tend not to critically evaluate the generated code and are worse at assimilating new knowledge. When working with AI, interaction becomes less intensive, covering only a narrow range of topics, and the main focus is solely on the finished result, not on the process of achieving it. Programmers tend to accept AI suggestions without critical evaluation, assuming in advance that everything will work exactly as intended. This leads to the accumulation of "technical debt" — errors that are not immediately visible but will create colossal problems in the future.

Modern language models already demonstrate results comparable to experts in dozens of subject areas, including engineering. Experts sometimes cannot distinguish a project created by a computer from a project created by humans. The classic engineering role is shifting: the engineer of the future must become not the one who directly solves the problem, but the one who sets the task for AI, monitors the result, and bears responsibility for it. But this requires that very fundamental understanding of physics, mathematics, and computational systems that allows one not just to use AI but to understand the limits of its applicability and possible errors. Without this foundation, the engineer turns into an operator pressing buttons without understanding what is happening inside the black box. And when I see in training sessions how people cannot find an answer in documentation because they are used to receiving ready-made solutions, it frightens me. If you cannot think without AI, you cannot verify whether AI has made a mistake. And it does make mistakes. Often. And the consequences of these mistakes in industry are measured not in broken apps but in destroyed equipment, halted production, and — in the worst case — human lives.

What to Do: Returning to the Roots

My mentor needed neither neural networks nor smart assistants to instill in me what I consider the main quality of an engineer. He had a simple method that I still use and recommend to everyone who wants not just to be called a specialist but to be one.

When you encounter unfamiliar equipment or a non-standard task, take three steps. First — find the information. Do not wait for someone to hand it to you on a silver platter. Open the documentation, the operating manual, the technical datasheet. Everything you need is already there — manufacturers write these documents precisely so that an engineer can figure things out. Second — analyze. Do not skim the documentation looking for familiar words. Read carefully. Compare what you read with what you see physically in front of you. Understand how the system works as a whole before diving into its specific component. Third — apply. Test your hypothesis. Take a measurement, send a test signal, change a parameter, and observe the system's response. Act consciously, understanding what you are doing and why.

These three steps seem obvious, yet it is precisely the inability to perform them that I observe in most "specialists" today. And they are precisely what distinguish a real engineer from an operator who only knows how to press buttons in a set sequence.

Conclusion

We stand at a dangerous crossroads. On the one hand, technologies are becoming more complex, and it seems that narrow specialization is unavoidable. On the other hand, it is precisely now, when systems are becoming increasingly integrated, that it is critically important to see the big picture, understand interconnections, and be able to analyze information coming from multiple sources. A narrow specialist who does not understand the context becomes a hostage to their narrowness. They are helpless as soon as the situation goes beyond the instructions. And situations always go beyond the instructions.

Fundamental knowledge, systems thinking, and the ability to work with information — these are what distinguish a true engineer. If this foundation exists, the specialist will cope with any equipment, any system, any task. If it does not exist, what you have before you is not an engineer but a person who has simply memorized which buttons to press. And unfortunately, there are more and more of such "specialists" today. Let us not join their ranks.