We keep seeing posts on LinkedIn and elsewhere with catchy lines like: 🧠 "AI won't replace you. Someone using AI will." ⚙️ "You must adapt or be left behind."

But what does "adapt" actually mean in real life?

Suppose someone has spent 10+ years as a front-end engineer. They're great at building UIs, collaborating with designers, and shipping products — but they haven't trained deep learning models or fine-tuned LLMs. Are they now expected to pivot into AI engineering overnight? Is that even realistic or necessary?

And more broadly:

Can everyone become an AI engineer? Should they?

What does meaningful growth with AI look like for those not directly in the AI/ML field?

How do we distinguish between real adaptation and empty "reskilling" hype?

For many people, the future might not mean becoming an AI builder — but learning how to think with AI, delegate better using AI tools, or even reimagine what their value is outside traditional tech tracks.

Let's be honest: not everyone will fit neatly into the "AI engineer" mold. So what other paths of growth should we be talking about?

Would love to hear how others are thinking through this.