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Value of General IT Knowledge

Terry Critchley

If you watch enough Western films (cowboys etc.), you will have come across a mountain man, henceforth called "M." This rugged person lived in the mountainous areas of the USA and made his living by obtaining animal pelts to sell to the fashionable ladies in the East.

M was the master of his territory and knew enough about the flora, fauna and geology of the land to know what to eat and what not to eat, steer clear of the wild animals, trap them and to avoid falling into holes or off cliffs. He also knew the weather patterns very well.

There were botanists, naturalists and geologists who visited these mountain areas for study purposes and their knowledge far exceeded that of M in their respective areas of study, although they did not know the territory’s geography and weather vagaries as well as M.

In their diverse studies at various times, the flora expert fell off a cliff, the geologist was poisoned by a plant and the fauna expert died of cold on their respective expeditions. M found them and gave them each a decent burial, with the usual two wooden sticks tied in the shape of a cross on their graves. He also said the few words from the bible over each grave.

So, what has this to do with it IT, I hear you ask? Everything is the answer. The flora, fauna and geology people represent specialists without a general underpinning knowledge of the IT "territory." The vagaries of the weather, the abundance of animals and plants represent the jobs in IT. The jobs "mutate," like the weather changes, and other perils lurk in areas of knowledge outside their own.

The visitors would have been sensible to ask M to accompany then on their visits or study the territory and its "contents" well before embarking on their, ultimately fatal, expeditions. It never ceases to amaze me when I examine the curricula of specialist courses that there are either no prerequisites, or very minor ones, just as M felt when he saw these "dudes" on his territory. The IT equivalents of these deaths is the 70% failure rate of IT projects.

Cybersecurity

It never ceases to amaze me when I examine the curricula of specialist courses that there are either no prerequisites, or very minor ones. I feel that that the analogy above makes the case for having general IT knowledge, even for someone who wishes to specialize in an area of IT, such as Cybersecurity or Cloud computing.

I have seen an advertisement for a cybersecurity course along the lines; "Become a cybersecurity expert in 16 hours with our course; $99, was $299," followed by the story of an accountant who took it an became an expert. This is La La Land, and may explain the fact that the "bad guys" seem to have the upper hand.

Image
Critchley

Figure 1: Cybersecurity: All These Areas are Vulnerable

Cloud Computing

Cloud computing is data center computing on steroids, the latter environment dragging people into the general work and knowledge that surrounds that computing environment, giving them a broader knowledge of it. It is advantageous to learn about that environment before entering it, is it not?

Image
Critchley

Figure 2: The Cloud Computing Ecosphere Scope

It should be self-evident that this environment, whatever role one has, that a broad knowledge of its composite nature is necessary to succeed.

Application Development

School computer education, and to some extent University, suggest that computing is about coding (in Python) and computational thinking. What one is supposed to be thinking about is not made clear. 

The application development environment comprises (among other things):

  • Coding in one or more languages
  • Security aspects of applications
  • The whole process of design/ code/test/recode, often called CI/CD – continuous improvement/continuous deployment
  • Methodologies – agile, scrum, DevOps, DevSecOps and others
  • Project management, milestones, reviews and other controls

Incidentally, "test" in the diagram above is not a single item but includes unit tests, integration tests and functional tests and there may be other tests depending on the work in hand, up to 16 in fact. 

Image
Critchley

In short, development is much, much more than coding, which may come as a surprise to many people and organizations. Remember also, that "development" is only part of the IT application ecosphere.

Summary

Long experience in IT, both at the coal face, in the trenches, researching and writing about IT leads me to the conclusion that there is a need for a form of general IT education outside anything on offer today. The latter comprises mainly computer science (CS), "IT Fundamentals," specialisms and "boot camps."

None of these cover the IT terrain which characterizes modern workplace IT, which has always evolved and which today is seeing a tectonic shift caused by AI (artificial intelligence) and its derivatives. One will look in vain for coverage of high performance and mainframe computing, graphics. IoT, edge computing and key methodologies which make IT projects tick.

It is time for a change.

Download the full paper: The Case for General Information Technology Training

Hot Topics

The Latest

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

We just surveyed 300 frontend and mobile engineers across 16 countries, and the finding that keeps sticking with me isn't the one about AI. It's this: 74% of engineering teams rate themselves in the "middle" of the observability maturity scale. Not reactive, not strategic. Stuck in the middle. They have dashboards, they have tracing, they have alerts. And yet when something goes wrong, they still can't tell you why ...

In MEAN TIME TO INSIGHT Episode 25, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses  AI's impact on the Wide Area Network (WAN) ... 

Application performance monitoring (APM) dashboards are only as useful as what they are configured to measure. The default setup covers obvious failure modes such as downtime, error spikes, and latency breaches, but it does not cover everything. Some failures produce no alerts or anomalies. The dashboard stays green while users experience a broken product. Here are six signs that is happening ...

The race to deploy AI is largely over. Most enterprises have entered it. The question now is not whether artificial intelligence is running inside the organization. The question is whether anyone is genuinely responsible for what it does. That is not a technical question. It is a leadership one. And most organizations are not yet structured to answer it honestly ...

A new analysis of 250 real-world queries across common retail tasks, such as product pricing, availability, ratings, shipping and specifications, reveals systemic inefficiency at the heart of web-based AI agents. On average, 97.9% of the data retrieved by agents from live web pages is irrelevant to the query being answered. Specifically, the average page ingested ran nearly 9,000 characters, while the average answer was just 32 characters, resulting in a noise-to-signal ratio of 278:1. Price queries were the most extreme outlier, with noise rates approaching 99.5%. That's not a rounding error. That's a structural problem ...

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

Value of General IT Knowledge

Terry Critchley

If you watch enough Western films (cowboys etc.), you will have come across a mountain man, henceforth called "M." This rugged person lived in the mountainous areas of the USA and made his living by obtaining animal pelts to sell to the fashionable ladies in the East.

M was the master of his territory and knew enough about the flora, fauna and geology of the land to know what to eat and what not to eat, steer clear of the wild animals, trap them and to avoid falling into holes or off cliffs. He also knew the weather patterns very well.

There were botanists, naturalists and geologists who visited these mountain areas for study purposes and their knowledge far exceeded that of M in their respective areas of study, although they did not know the territory’s geography and weather vagaries as well as M.

In their diverse studies at various times, the flora expert fell off a cliff, the geologist was poisoned by a plant and the fauna expert died of cold on their respective expeditions. M found them and gave them each a decent burial, with the usual two wooden sticks tied in the shape of a cross on their graves. He also said the few words from the bible over each grave.

So, what has this to do with it IT, I hear you ask? Everything is the answer. The flora, fauna and geology people represent specialists without a general underpinning knowledge of the IT "territory." The vagaries of the weather, the abundance of animals and plants represent the jobs in IT. The jobs "mutate," like the weather changes, and other perils lurk in areas of knowledge outside their own.

The visitors would have been sensible to ask M to accompany then on their visits or study the territory and its "contents" well before embarking on their, ultimately fatal, expeditions. It never ceases to amaze me when I examine the curricula of specialist courses that there are either no prerequisites, or very minor ones, just as M felt when he saw these "dudes" on his territory. The IT equivalents of these deaths is the 70% failure rate of IT projects.

Cybersecurity

It never ceases to amaze me when I examine the curricula of specialist courses that there are either no prerequisites, or very minor ones. I feel that that the analogy above makes the case for having general IT knowledge, even for someone who wishes to specialize in an area of IT, such as Cybersecurity or Cloud computing.

I have seen an advertisement for a cybersecurity course along the lines; "Become a cybersecurity expert in 16 hours with our course; $99, was $299," followed by the story of an accountant who took it an became an expert. This is La La Land, and may explain the fact that the "bad guys" seem to have the upper hand.

Image
Critchley

Figure 1: Cybersecurity: All These Areas are Vulnerable

Cloud Computing

Cloud computing is data center computing on steroids, the latter environment dragging people into the general work and knowledge that surrounds that computing environment, giving them a broader knowledge of it. It is advantageous to learn about that environment before entering it, is it not?

Image
Critchley

Figure 2: The Cloud Computing Ecosphere Scope

It should be self-evident that this environment, whatever role one has, that a broad knowledge of its composite nature is necessary to succeed.

Application Development

School computer education, and to some extent University, suggest that computing is about coding (in Python) and computational thinking. What one is supposed to be thinking about is not made clear. 

The application development environment comprises (among other things):

  • Coding in one or more languages
  • Security aspects of applications
  • The whole process of design/ code/test/recode, often called CI/CD – continuous improvement/continuous deployment
  • Methodologies – agile, scrum, DevOps, DevSecOps and others
  • Project management, milestones, reviews and other controls

Incidentally, "test" in the diagram above is not a single item but includes unit tests, integration tests and functional tests and there may be other tests depending on the work in hand, up to 16 in fact. 

Image
Critchley

In short, development is much, much more than coding, which may come as a surprise to many people and organizations. Remember also, that "development" is only part of the IT application ecosphere.

Summary

Long experience in IT, both at the coal face, in the trenches, researching and writing about IT leads me to the conclusion that there is a need for a form of general IT education outside anything on offer today. The latter comprises mainly computer science (CS), "IT Fundamentals," specialisms and "boot camps."

None of these cover the IT terrain which characterizes modern workplace IT, which has always evolved and which today is seeing a tectonic shift caused by AI (artificial intelligence) and its derivatives. One will look in vain for coverage of high performance and mainframe computing, graphics. IoT, edge computing and key methodologies which make IT projects tick.

It is time for a change.

Download the full paper: The Case for General Information Technology Training

Hot Topics

The Latest

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

We just surveyed 300 frontend and mobile engineers across 16 countries, and the finding that keeps sticking with me isn't the one about AI. It's this: 74% of engineering teams rate themselves in the "middle" of the observability maturity scale. Not reactive, not strategic. Stuck in the middle. They have dashboards, they have tracing, they have alerts. And yet when something goes wrong, they still can't tell you why ...

In MEAN TIME TO INSIGHT Episode 25, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses  AI's impact on the Wide Area Network (WAN) ... 

Application performance monitoring (APM) dashboards are only as useful as what they are configured to measure. The default setup covers obvious failure modes such as downtime, error spikes, and latency breaches, but it does not cover everything. Some failures produce no alerts or anomalies. The dashboard stays green while users experience a broken product. Here are six signs that is happening ...

The race to deploy AI is largely over. Most enterprises have entered it. The question now is not whether artificial intelligence is running inside the organization. The question is whether anyone is genuinely responsible for what it does. That is not a technical question. It is a leadership one. And most organizations are not yet structured to answer it honestly ...

A new analysis of 250 real-world queries across common retail tasks, such as product pricing, availability, ratings, shipping and specifications, reveals systemic inefficiency at the heart of web-based AI agents. On average, 97.9% of the data retrieved by agents from live web pages is irrelevant to the query being answered. Specifically, the average page ingested ran nearly 9,000 characters, while the average answer was just 32 characters, resulting in a noise-to-signal ratio of 278:1. Price queries were the most extreme outlier, with noise rates approaching 99.5%. That's not a rounding error. That's a structural problem ...

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...