Agentic AI speeds up code, but not judgment. Without humans capable of saying no, abundance becomes debt: invisible bugs, uncontrolled costs and sacrificed juniors.
The AI writes the code. Judgment cannot be purchased via API.
Agentic AI shifts work from production to judgment. But judgment is not generated on demand: it is cultivated. And many companies are already destroying their capacity to produce them.
Speed fascinates, but it masks the real question
Everyone looks at the speed. Agents write code faster than any team, and the industry applauds. Nobody asks the real question: who decides whether this code deserves to exist, and who will still be able to say it in five years?
Value does not shift to the one who produces. It moves towards the one who judges. And the judgment, unlike the code, is not obtained by pressing “generate”.
The machine optimizes everything except what matters
An agent does not understand what it is doing: it is optimizing a target. Give him autonomy without safeguards, and he will push this target to the point of absurdity.
The bills speak for themselves. Uber capped its AI spending after exhausting its 2026 budget in April. According to the press, a company received a bill of 500 million dollars in a single month, because of agent loops gone crazy.
These are not technical incidents. These are decisions that no machine was able to make, made anyway, for lack of a human to decide. The real danger of agentic AI is not that it is wrong: it is that it does not know that it is wrong.
We only supervise what we know how to do ourselves
This is the trap that no one dares to name. As agents produce, humans validate. But we do not reread with the same acuity reasoning that we have not constructed.
The magazine then turns into a theater: a buffer placed on a volume that no brain can absorb. The subtle bug passes, not through negligence, but because the eye that should have caught it no longer has the context to see it.
The result? The more you delegate, the less able you are to supervise. Judgment is a muscle: it atrophies when we stop using it. And an organization that loses this capacity doesn’t realize it until it’s too late to rebuild it.
Cutting off juniors means drying up the source of seniors
This is where management makes the most costly mistake. Faced with agents who “do the work”, the temptation is clear: reduce the workforce, starting with junior profiles, and transfer the savings to the AI bill.
Except that a senior capable of saying no to the machine has never fallen from the sky. He was a junior who wrote code, made mistakes, reread that of others, and slowly formed this famous judgment. Remove the junior, and you remove the senior of tomorrow.
It’s not a saving: it’s a debt. Invisible today, required the day when someone will be needed to arbitrate what AI will never be able to arbitrate.
What if the real rare skill was knowing how to say no?
The companies that succeed won’t be the ones that generate the most code. They will be those who have protected and maintained their capacity for discernment as a strategic asset.
This requires reversing the reflex: treating human judgment not as a cost to be compressed, but as the resource that the abundance of code suddenly makes valuable. Version, proofread and challenge agents. Keep humans who still know why a line of code exists.
Technology doesn’t decide for you. It is content to make visible trade-offs that the slowness of development has hidden until now.
The AI will write your code, of course. There remains one point that nothing will automate: someone will always need to judge what it produces. The only question is whether you’re still training this person — or whether you’ve just fired them.
