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The Most Ambitious Career Is No Longer Being the Best Expert

An investor argues ambitious young people are now aiming to build systems that help discover drugs.

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digitalnative.tech · The Post-Agentic Founder

Jared Newman, a writer for Daybreak, an investment firm that works with early-stage founders, was summing up months of internal debate. The thinking appeared in Daybreak's Q2 letter to its investors, which the firm later shared publicly to be more transparent with founders about what it looks for.

He wrote that for much of the previous hundred years, highly motivated young people got simple guidance: pick a vital subject and master it more fully than anyone else. A teenager hoping to defeat cancer would train as a cancer doctor. One hoping to slow global warming would train as a chemist who improves batteries.

That model, he argues, has started to shift. In his words, the question for the most driven is now less "How do I solve the world's largest problems?" than "How do I build AI agents capable of solving those problems?"

Agents is a general term for software that can pursue a goal with limited supervision, such as searching papers or drafting code. Newman illustrates the change with that young cancer doctor. Where once his firm might have urged her to design new treatments herself, it now urges her to create the tools that aid discovery.

Newman writes that the two paths call for "different forms of leverage." The first, in his phrase, "rewards years of immersion in a single discipline." The second depends on what he calls the scarce resource: "knowing how and when to apply capabilities toward important problems," along with organizing people around those tools and building organizations that get stronger as the models improve.

He presents this as a shift in direction for ambition, not as proof that expertise stopped counting. The point is that training as the top specialist and building systems that extend specialists require different strengths.

Questions people ask

What exactly is an AI agent?

An AI agent is software built on top of a large AI model that can take a goal and work through steps toward it, like searching papers, writing code, or running analyses, with limited supervision. Think of it as the difference between asking for an answer and hiring a junior assistant to do a project.

Does that mean oncologists and chemists are no longer needed?

No, in Newman's telling. His point is that the most ambitious path has shifted from being the expert to building systems that extend what experts can do. Medicine, chemistry, and other fields still supply the problems and the standards for what counts as a solution.

If a student wanted to pursue this path, what should they study?

There is no single degree, and founders come from many backgrounds. Useful preparation typically combines fluency with current AI tools, enough technical skill to prototype software, and close study of a real problem in clinics, labs, or companies where the agent would be used.