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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

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

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When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

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Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

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

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...