A lot of what we called talent was just scarce execution

Anyone who has used the latest frontier models seriously comes away feeling two things at once: amazed, and completely, hopelessly lost.

And honestly, for good reason.

For decades, we built our identities around intelligence, hard work, deep knowledge, reliability, getting hard things done, and delivering under pressure. We celebrated people who could out-think, out-work, and out-execute everyone around them. That was the game. And for a long time, it worked.

But that game is breaking.

Frontier models are mindblowing. They are already better informed than I am across a growing range of domains. They can sustain a level of speed, attention, and throughput I never could. In many coding workflows, Claude Code is already a stronger writer, debugger, and QA partner than most engineers, including me, on my best days.

These systems are not flawless. Neither are humans. Net-net, on more and more real work, they outperform us. And they will only get better.

If you are a software engineer, analyst, consultant, researcher, designer, or really anyone in knowledge work, you can already see the writing on the wall.

A lot of what we thought made us valuable was just scarce execution.

That’s the uncomfortable truth.

The hard stuff. The grind. The ability to push through complexity. Years of building domain expertise and pattern recognition. All of that felt like a moat because it was hard to access, hard to replicate, and hard to compress.

Frontier models are changing that. They make the quality of execution that used to be scarce much more available. And once that happens, the bottleneck shifts.

What changes is not the nature of work. It is the qualities that make someone exceptional at it.

Vision, or what people call taste these days, is becoming critical. Patience, the ability to not rush into implementation, and to think through second- and third-order effects, is becoming vital. The ability to keep the outcome aligned with the objective, and earn trust, is now at a premium.

It reminds me of a line from Siddhartha by Hermann Hesse: “I can think, I can wait, I can fast.”

For a long time, these qualities were undervalued because they were mostly invisible. We optimized for throughput. We rewarded execution because volume looked like value.

But LLMs can produce on demand. They can move instantly. They can give you ten plausible answers before you have properly understood the question.

That is exactly why wisdom matters more now, not less.

LLMs are powerful, fast, and often impressively capable. But they are not wise.

Wisdom is earned in lived context. It comes from making decisions, bearing consequences, and understanding the weight of responsibility. It comes from knowing that the cost of being wrong is not evenly distributed. It comes from having to live with outcomes.

That is where Hesse’s line hits different.

To think is to exercise judgment. To wait is to resist the pressure to act before understanding. To fast is to refuse the easy answer, the lazy answer, the good-enough answer.

That is the muscle.

And that is the moat.

AI does not remove the need for skill. If anything, it raises the bar on what skill has to become. Execution still matters. But it is less and less the bottleneck. What matters is whether it is being directed well - whether the person using the machine knows what they are doing, what tradeoffs they are making, what risks they are accepting, and what standards they are willing to hold.

Wisdom scales execution.

Without it, speed just creates more mistakes. More output. More confusion. More plausible-looking garbage.

With it, the same tools become real leverage.

So the shift is not away from work. It is not toward abstraction. And it is not some vague claim that “humanity” will win in the end.

It is much simpler than that.

The people who do well will be the people who can still tell what matters. The people who can use these systems without surrendering themselves to them. The people who can move fast without becoming sloppy, and hold standards when everything around them is optimized for convenience.

That is the new divide.

Not between people who use AI and people who don’t.

Between people who have wisdom, and people who only have output.

In the future of work, wisdom is not optional. It is the only thing that scales.