I understand and empathize with his sentiment, but I think he is missing the point. Using AI effectively as an engineer requires a paradigm shift in terms of how you work. You cannot approach your work as you did in the past, and use AI and expect it to be a big improvement. In fact, if you do that you will likely be disappointed, and worse off. Shifting your paradigm is one of the hardest things you can do, even more so if you have been in the field for a while, but it is also the most rewarding, and opens up many new possibilities. It's not about being left behind, as much as it is about limiting yourself unnecessarily, by staying in your comfort zone.
This article oversimplifies things...and then comes to some bold conclusions. It helps to look at different perspectives, rather than looking at everything through an ideological lens. I guess thats the age we live in, unfortunately.
You have the fear of being judged; the antidote is realizing that most people barely notice you, it just feels like they do because you’re self-conscious around new people.
I used to feel the same way about AI, but my perspective has completely changed.
The key is to treat AI as a tool, not as a magic wand that will do everything for you.
Even if AI could handle every task, leaning on it that way would mean surrendering control of your own life—and that’s never healthy.
What works for me is keeping responsibility for the big picture—what I want to achieve and how all the pieces fit together—while using AI for well-defined tasks. That way I stay fully in control, and it’s a lot more fun this way too.
Hiring poor developers is not the cause of what went wrong with Digg, but a symptom of what really went wrong.
The problem with Digg is they stumbled onto a formula that drove them to success overnight, but the company never had a true vision that they believed in and followed as a company.