Here We Go Again

Tonight at dinner, I stumbled into an uncomfortable truth about technology, identity, and change.

For years, I resisted network automation.
Not because I thought it was useless, I couldn’t learn it, or I thought networks should never evolve.

I resisted network automation because I loved building networks by hand.

I loved crafting configurations line by line. I loved the feeling of expressing intent directly in the CLI. There is an art to crafting configs by hand. I didn’t just configure a router; I’d bring an entire system to life. Routing and redundancy protocols, policy, traffic engineering, security boundaries, and service delivery. It felt like craftsmanship.

Writing the configs was the fun part.

Then automation arrived, and they said, “Stop doing the fun part manually.” Instead of crafting configurations, they were abstracted away into templates, variables, YAML files, Python scripts, and pipelines.

I understood the point.
Consistency.
Scale.
Repeatability.
Reduction of human error.
Infrastructure as code.
Intent-based everything.

Cognitively, I understood the benefits.
But emotionally?
It felt like someone was taking my craft away from me.
A craft I worked long and hard to master.

Tonight, sitting with a group of network automation practitioners, the conversation shifted toward large language models and AI-generated code. I asked if they were using LLMs to generate code for their automation practice.

They tensed up.
Their faces grimaced.
They looked at each other, seemingly for permission to be candid, before opening up to me.

“No, we don’t like coding with AI.”

My curiosity piqued. I dug deeper.
They didn’t avoid LLMs because the tools were bad, the output wasn’t useful, or the models occasionally hallucinated.

They said, “Writing the code is the fun part.”

They talked about:
Creativity.
Solving problems with their own hard-earned knowledge.
The satisfaction of building something by hand.
How generating code with AI removes the most satisfying part of coding.

Then it hit me.
We are the same.
The reasons I resisted network automation for years are the same reasons developers (and other knowledge workers) resist AI-assisted anything. 

The traditional network engineer says:
“Automation steals the craft of networking.”
The traditional developer says:
“LLMs steal the craft of coding.”

Different professions.
Different tools.
Identical cognitive biases.
Identical emotional responses.

Maybe resistance to technological change isn’t about technology at all.
Maybe the root cause of our resistance to change is how our brains are designed.
Could our disdain of change be hardwired?

We Protect Identity

Throughout history, one reason we resist change is our attachment of mastery to identity.

Henry Ford famously said, “If I asked people what they wanted, they would have said faster horses.”
Imagine being a master horseshoe maker, watching the world shift beneath you. Their resistance to change would come from watching a lifetime of hard-earned expertise slowly lose its place in the future.

A veteran network engineer doesn’t just know BGP.
They became someone through years of learning BGP.

A developer doesn’t just write code.
They derive meaning from the act of problem-solving.

When a new abstraction layer appears, it doesn’t merely threaten workflow efficiency. It threatens our source of competence, pride, creativity, and identity. That’s a much deeper psychological effect than most technology conversations acknowledge.

The Endowment Effect of Expertise

Daniel Kahneman’s work on cognitive bias helps explain this. One of his findings is the endowment effect: humans assign more value to things simply because they own them. But ownership is not limited to physical objects.

We become psychologically attached to:
- workflows
- methods
- tools
- expertise
- mental models
- professional rituals

A CLI artisan values manual configuration because years of effort created emotional ownership. A developer values handwritten code because it represents hard-earned capability.

The resistance is not logical. It’s an emotional attachment disguised as a technical preference.

Status Quo Bias Disguised As “Professional Standards”

Another powerful force is status quo bias; our tendency to prefer existing systems simply because they are familiar. What’s fascinating is how often we rationalize this bias as wisdom.

We say:
“People need to understand fundamentals first.”
“Automation creates dangerous abstraction.”
“AI-generated code will create bad engineers.”
“Nobody should trust black boxes.”

Sometimes those concerns are valid, but often they’re defensive reactions from professionals whose brains associate familiarity with safety.

Humans confuse: “this feels uncomfortable” with “this is wrong.”

From Our Cold, Dead Hands

What struck me most tonight was that both groups, traditional network engineers and automation developers, fear the same thing: The loss of creativity. 

Network engineers fear losing the creativity of designing and crafting networks manually. Developers fear losing the creativity of building software manually.

This common fear reveals something important about people.
We don’t prefer efficiency.
We want agency.
Expression.
Mastery.
Creation.
Identity.

The act of building things by hand matters psychologically.
There is joy in craftsmanship.
There is pride in “I am the expert of the thing.”
There is validation when you can look at a thing and say, “I did that.”

Every Generation Thinks Their Layer Was the “Real” Work

History repeats itself.

At one point:
Assembly programmers resisted higher-level programming languages.
Server admins resisted virtualization.
Virtualization engineers resisted cloud abstractions.
Network engineers resisted automation.
Developers resist AI-generated code.

Each generation believes the way they learned and did the job was the “real engineering.” As new tools arrive, each new abstraction increases the distance between the artisan and their craft. A sense of betrayal creeps in. If they are among the lucky ones, they pass through the stages of grief, find acceptance, mourn the loss, and evolve.

We Prefer Familiar Pain Over Unfamiliar Possibility

Cognitive science suggests something more confounding.
Humans are loss-averse. We feel the pain of losing something more intensely than the pleasure of gaining something new.

When new paradigms emerge, we don’t instinctively think “What new possibilities does this create for me?” We think, “What part of my identity does this take from me?”

That’s not ignorance.
That’s loss aversion, and it limits what’s possible.

The Irony of Technologists Resisting Technology Shifts

I spent years being challenged by automation engineers who believed I was resisting the future. Now, many of those same developers are resisting AI-assisted development for identical psychological reasons.

I’m not here to cast judgment.
I get it.
I lived it.
I still do.

I actively question my assumptions to ensure I never get stuck again. Our brains are wired to keep us safe, even if it means hindering our ability to perceive objective reality.

Cognitive biases create the illusion of simplicity in an infinitely complex universe. While they provide a sense of safety, they often cause harm. Most of us are blissfully unaware of the mental shortcuts our brains take, and prefer comfortable delusions over uncomfortable facts. Our ignorance of the fundamental nature of our minds is the source of our perceived bliss.

Where to From Here?

The only constant is change, yet we resist change.
That’s a bug, not a feature.

We don’t need blacksmiths anymore.
We replaced hand saws and screwdrivers with power tools.
The human elevator operator was replaced by automation.
Dynamic routing protocols automate path selection.
Jets mostly fly themselves.
We have driverless cars.

Manual toil has always been, and will always be, replaced by efficiencies driven by innovation.
Each time innovation appears, a modern skillset that people spent a lifetime perfecting becomes obsolete.

Don’t be the blacksmith yelling about the invention of automobiles.
You are wrong, and no one cares about your bruised ego.
Well, I care. But the labor market does not.

Our intrinsic resistance to change is our brain’s attempt to produce a sense of safety in an unsafe world, and it can limit our career opportunities if we’re not careful.

It’s not your fault, but you are responsible for your ability to earn a living.
If you waste your limited time and attention pushing back on progress, you will be left behind.

Don’t get left behind.

This was never about networking.
Or Ansible.
Or Python.
Or DevOps.
Or LLMs.

It was always about identity and agency.

Technology changes faster than human psychology does.
Always has.
Always will.

Here’s my ask of you, dear reader. When the next paradigm shift arrives, instead of taking sides, existing in the binary, and arguing about who is right and which path is better, let’s share a knowing glance and send each other a loving, “Here we go again.”