I'm a professional developer, and AI has significantly increased my output—I'd say by maybe 30 or 40 percent. GitHub Copilot has significantly changed the way I work with code.

However, I take pride in producing high-quality code quickly, which is why my rates are high. Using AI helps me increase my output while maintaining that level of quality.
My take on AI is that it is not going to replace humans anytime soon.

It is, however, putting significant pressure on the economy. Previously, setting up a functional, decent-quality project without much complexity took time—at least weeks. Now, such tasks are incredibly fast and easy; anyone can set them up in a few minutes using AI, even without any coding knowledge.

Success in most fields, however, is not just a measure of how fast you can build; it's also about how well you can execute. Current AI can offer advice, but it still cannot execute for you. Market success requires sensitivity, context, and adaptability. AI can help significantly if you know how to ask the right questions. But the economy is made of people, not AI (yet). To earn money, someone must give you money because they value what you offer. The arrival of LLMs hasn't changed this.

I feel the pressure. The corporation I work for is pushing for AI adoption, and the initial drawbacks and realizations are already becoming apparent.
First point: Customers, at best, don't care about your AI. They don't want it.

Second point: AI succeeds at making developers more productive but fails with higher complexity—though not for the reason people usually think. With the right prompt, GPT-5.4 can create fairly complex solutions, even more complex than many corporate business processes.
The real reason is that, at a certain level, complexity lies not in the total amount of information in the system, but in how the human aspect of the business translates when you try to formalize higher-level context. This is something most developers don't see (or care about). For example, guiding an AI to implement a feature in a repository is easy. However, asking an AI how 50 apps in your company should better communicate is a question it cannot answer well, simply because this specific question may have hidden dependencies linked to why your products are successful in the first place. Do you see what I mean? At a certain level, technological questions can no longer be purely technological; they become (and must be) political and business-oriented.
Every developer dreams of having a perfect description of what needs to be built, complete with precise analysis and exact information. But you never get that in a higher-level context, because business success isn't modeled by perfect ideas alone—it relies heavily on execution, which often involves acting on incomplete information.

This is why AI is not going to replace developers anytime soon.