The conversation about AI in the tech market is still too polarized. On one hand, there's the panic that everything will be automated. On the other, there are those who completely ignore the paradigm shift. The reality lies in between — and those who will come out on top are those who understand how to integrate language models into their workflow without giving up critical thinking.
The point that no one talks about: LLMs are incredibly good at generating plausible code. The problem is that "plausible" and "correct" are very different things. The differential of the engineer who dominates AI is knowing exactly where to question the model's output.
Code agents, copilots, and RAGs are already a reality in production in dozens of companies. The question is no longer "is this going to happen?" — it's "do you know how to evaluate, debug, and orchestrate this?"
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