LLM AI has already changed coding. The highest-leverage engineers are no longer just the fastest typists; they’re the ones who can frame problems clearly, steer AI well, and judge outputs with taste and rigor. Code generation is becoming abundant. Good judgment is not.

That means prior knowledge still matters — maybe even more than before. Architecture, systems thinking, organizational navigation, communication, and product sense are what separate people who can independently deliver from those who still need constant guidance. If anything, the gap may widen: if the effort required to guide a junior person becomes higher than the effort required to guide AI, then low-agency work starts to look increasingly fragile.

This shift probably changes lifestyle design too. The future may be less about choosing between corporate life and entrepreneurship, and more about combining them. A plausible path is a hybrid of high-skill corporate work and global nomad / solopreneur freedom. As code and content become cheap to produce, the edge moves closer to distribution, customer intimacy, and real-world trust. The people who win won’t just build faster. They’ll talk to customers, uncover pain points, clarify demand, and turn those insights into products, services, and audiences.

That also makes apprenticeship in distribution feel underrated and increasingly important. If building is getting commoditized, then knowing how markets are reached, how attention is earned, and how trust is converted may become one of the most valuable skills to learn next. In a world flooded with generated output, being close to reality may be the real moat.

The same pattern seems to apply to investing. The boundary between builder, seller, and investor is getting thinner because ideas can be tested faster, products can be launched faster, and market conditions can change faster. In that kind of environment, static expertise matters less than a continuous learning and adaptation loop: notice change early, build quickly, talk to users, refine distribution, and allocate capital toward the strongest signals.

My guess is that the future belongs less to people who stay in one lane, and more to those who can move fluidly across creation, distribution, and capital allocation — combining technical leverage with human judgment and market awareness. AI may make building cheaper, but it also raises the premium on taste, agency, and contact with reality.