I have been working in the IT field for about 22 years now, starting back in 2004. Back then, there was no YouTube, no Facebook, barely any high-speed internet, and blogs were still called web logs.
Around 2007 and onward, we saw rapid shifts with the iPhone, the app ecosystem, and the big migration from on-premise server rooms to the cloud.
Through every single one of those cycles, one truth held up: technology expands the economy, creates new opportunities, and reshapes the job market.
Between 2010 and 2016, automation was the big topic. Everyone wanted to automate workflows, and a lot of people were genuinely afraid of automating themselves out of a job.
So it is not surprising that so many people see AI as an immediate threat today.
The crowd feeling the most vulnerable right now seems to be software engineers and developers.
I don't consider myself a traditional software engineer. My background has always been core IT infrastructure, focusing on servers, networks, and enterprise systems, but I have always had a soft spot for coding.
Over the years, I learned JavaScript, HTML, CSS, PHP, and Python. When I started building SAFi, I had to get right down into the weeds with those tools, well before AI tools became common for writing code.
Once I started using AI to assist with coding, I saw the power right away. But I also saw the trap. Without a clear plan and a solid mental model of what you are building, AI can be detrimental.
In IT infrastructure, we learn early on that code is a liability, not an asset.
Every single line of code you deploy is a line someone has to maintain, debug, monitor, and secure. If an AI helps someone churn out ten times more code without any real architecture behind it, they haven't built ten times faster. They have just created ten times more technical debt and security risk.
Building software has never been just about knowing the syntax. It requires the right mindset, structural discipline, and architectural judgment.
That is the real value experienced engineers and IT architects bring.
The value is not the mechanical act of typing out boilerplate code, because AI can handle that in seconds. The value is the experience and oversight required to make sure that code is maintainable, secure, and actually serves a purpose.
Without that experience, handing AI to someone is like handing an expensive custom guitar to someone who doesn't know how to play. The instrument might be great, but it won't produce music on its own.
With AI, raw code has become a cheap commodity. But the human skill and judgment needed to structure it properly has become priceless.