AI Engineering: Do developers' opinions even matter?

The AI Engineer World's Fair in San Francisco is a genuine celebration of optimism. The atmosphere is electric, everyone's talking about the future and how AI will change everything. But beneath all this euphoria, a question lingers: who are these “AI Engineers” and what exactly do they do? It seems the title is more an aspiration than a clear definition.

The problem is that the AI Engineer role is still a bit nebulous, a sort of gold rush for a profession nobody has quite pinned down yet. The author of an article on dev.to, present at the event, noted this discrepancy. While everyone celebrates, few actually ask what's needed on the ground, day by day. It's like building a house without asking the bricklayers what they need to work effectively.

This is precisely why it's crucial to involve those who get their hands dirty with code: the actual developers. Instead of top-down definitions, it makes far more sense to ask the community what “AI Engineering” truly means. What should an AI engineer study? What tools do they use? What problems do they concretely solve? The author is actively collecting this very type of feedback.

This bottom-up approach helps give concrete shape to a field that risks remaining just a collection of buzzwords. Defining AI Engineering with the help of the dev.to community means creating a curriculum, standards, and expectations that have practical meaning. It's not just about a title; it's about building a solid, useful profession based on real experiences, not just optimistic predictions. It helps understand the true challenges and genuinely useful skills.