Hiring specialists made sense before AI — now generalists win

Source: VentureBeat

The Evolution of Hiring: From Specialists to Generalists

Tony Stoyanov is CTO and co‑founder of EliseAI.

In the 2010s, tech companies chased staff‑level specialists: backend engineers, data scientists, system architects. That model worked when technology evolved slowly. Specialists knew their craft, could deliver quickly, and built careers on predictable, narrowly scoped projects.

As AI accelerated the pace of change, the specialist‑first approach began to show cracks. The rapid emergence of new tools, frameworks, and workflows meant that deep expertise in a single niche could quickly become obsolete. Companies started to value engineers who could move fluidly across domains, learn new technologies on the fly, and connect disparate pieces of a product ecosystem.

Today, generalists—those who blend software engineering, data analysis, product sense, and a willingness to experiment—are in high demand. They can adapt to shifting priorities, bridge gaps between teams, and help organizations stay agile in an AI‑driven landscape.

The shift reflects a broader industry realization: while deep expertise remains valuable, the ability to learn continuously and apply knowledge across multiple areas has become the new competitive advantage.