I don't take immediate issue with the points made here, but I think the conclusion is not entirely correct. Security isn't full, it's just harder and more competitive than people think.
I'll explain: because of the hype described here, many, many people decided that security would be a great way to make a living. They were told that there was a severe need for security professionals, and that there would be high-paying jobs just waiting for them to apply.
So these people studied security in school, maybe took the Security+ or CEH certs, and applied for jobs. Those that got jobs got laid off (again, mentioned in the article) when times got tough, or never got a job in the first place. Why?
Security is a field of people who love what they do. Go to DEF CON -- or even better, small, regional infosec conferences -- and you'll find people who are extremely talented... some of whom don't even work in the industry. For people like this, there is a talent shortage.
I've been consistently hiring security people for the last 15 years. There is absolutely a talent shortage at high levels of the industry -- but it's really hard to get to that level. Learning the OWASP Top 10 and a few nmap flags isn't going to cut it.
My experience may not be universal, but this is what I've seen over the course of a lifetime in infosec.
For those of you who, thankfully, don't have personal experience, it generally goes like this: reasonable-ish individual starts using AI and, in turn, their AI either develops or is prompt-instructed to have certain personality traits. LLMs are pretty good at this.
Once the "personality" develops, the model reinforces ideas that the user puts forth. These can range from emotional (such as the subreddit /r/MyBoyfriendIsAI) to scientific conspiracies ("yes, you've made a groundbreaking discovery!").
It's easy to shrug these instances off as unimportant or rare, but I've personally witnessed a handful of people diving off the deep-end, so to speak. Safety is important, and it's something many companies are failing to adequately address.
It'll be interesting to see where this leads over the next year or so, as the technology -- or at least quality of models -- continues to improve.