Tony Stoyanov is CTO and co-founder EliseAI
In the 2010s, technology companies were looking for staff-level specialists: backend engineers, data analysts, system architects. This model worked when technology developed slowly. Specialists knew their craft, were able to complete tasks quickly and built careers on predictable foundations, such as cloud infrastructure or the latest JS framework
Then artificial intelligence entered the mainstream.
The pace of change has exploded. Fresh technologies emerge and mature in less than a year. You can’t hire someone who has been creating AI agents for five years because the technology hasn’t been around that long. The people who thrive today are not those with the longest lives; they are the ones who learn quickly, adapt quickly and act without waiting for guidance. Nowhere is this transformation more evident than in software engineering, which has arguably experienced the most dramatic change of all, evolving faster than almost any other field of work.
How AI rewrites the rules
Artificial intelligence has lowered the barrier to performing intricate technical work and technical skills, and raised expectations for what counts as true expertise. McKinsey estimates that by 2030 up to 30% of working hours in the USA can be automated and 12 million workers may have to change roles completely. Technical depth still matters, but AI favors people who can understand everything on the fly.
I see this every day in my company. Engineers who have never touched front-end code are now building user interfaces, while front-end developers are moving on to work on the back-end. Technology is becoming easier to exploit, but the problems are more arduous as they span more disciplines.
In this environment, being great at one thing is not enough. What matters is the ability to connect engineering, product and operations to make good decisions quickly, even with imperfect information.
Despite all this enthusiasm, only 1% of companies consider themselves truly mature in their exploit of AI. Many people still rely on structures built for a slower era – layers of acceptance, fixed roles, and an over-reliance on specialists who can’t step out of their lane.
Features of a sturdy generalist
A sturdy generalist has breadth without losing depth. They delve into one or two domains but are fluent in many. As David Epstein put it Range“People walk around with all of humanity’s knowledge on their phones, but they have no idea how to integrate it. We don’t train people to think or reason. ” True knowledge comes from connecting the dots, not just collecting information.
The best generalists have the following characteristics:
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Property: Comprehensive responsibility for results, not just for tasks.
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First Principles Thinking: Question assumptions, focus on the goal, and rebuild as needed.
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Adaptability: Learn novel domains quickly and move between them seamlessly.
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Agency: Act without waiting for approval and adapt as novel information arrives.
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Gentle skills: Communicate clearly, align teams, and focus on customer needs.
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Range: Solve different types of problems and draw conclusions from different contexts.
I try to make accountability a priority for my teams. Everyone knows what they have, what success looks like and how it connects to the mission. Perfection is not a goal, but movement forward.
Embracing change
The focus on versatile creators changed everything. These are people who can and are curious about how to exploit AI tools to learn quickly and perform their tasks with confidence.
If you are a builder who lives in ambiguity, this is your time. The era of artificial intelligence rewards curiosity and initiative more than credentials. If you’re hiring, look to the future. The people who will move your company forward may not be the ones who have the perfect CV for the position. They are the ones who can grow into what the company will need as it grows.
The future belongs to generalists and the companies that trust them.
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