AI Eliminates Juniors, Multiplies Seniors in Software Development

AI does not equalize: it eliminates juniors and multiplies seniors

In programming, generative artificial intelligence has done the opposite of what was promised: instead of bringing the mediocre programmer closer to the brilliant one, it has multiplied the distance between them. The senior produces ten times more; the one who only writes prompts without judgment generates technical debt at record estimulante ilegal. And the junior, the one who used to enter to learn, has been left out. Job offers from two years ago asking for two years of experience and eagerness now demand a profile that already knows how to direct the machine.

The talent pipeline is drying up: who will train the next senior?

The first visible impact of the 2025-2026 cycle is the closing of the junior hiring tap. Companies no longer train: the equation is simple, one AI subscription plus one senior supervising three interns produces more code than a newly graduated junior. For a listed company looking at quarterly EBITDA, the junior is a short-term expense and a talent leak after two years once trained. The result, according to several analyses, is that the industry’s talent pipeline is drying up: there are no juniors, and in five or ten years, there will be no seniors who went through that learning phase.

The curious thing is that the same analysis announcing the disappearance of the junior admits it will need architects and technical profiles who understand the entire system. To reach that level, there will no longer be intermediate steps. You either enter with very solid knowledge, or you stay out. The bottleneck is not new, but AI has strangled it completely.

Vibe coding: the recipe for technical debt

In contrast to the enthusiasm for “prompting,” there is a much more skeptical current warning of the risk of building software by asking the AI to “do things” without method. The so-called vibe coding, or simply: letting the model write code without specification or tests, is the perfect formula for a medium-term catastrophe. Not because the AI generates bad code, but because no one knows why it generated it, and when it fails, there is no way to grab hold of it.

Structured methodologies, such as TDD or SDD, seem to fit better with generative AI: first you define the interface, then the tests, and only after that do you let the machine fill in the modules. In that flow, AI multiplies productivity without sacrificing control. But it requires a senior who knows how to design the system. And here appears the gap that many do not want to see: brilliant developers remain as far from mediocre ones as before, if not more, because now they can shed coding and dedicate themselves to what truly matters: thinking.

Legacy is the wall: where AI does not reach

The other side of optimism is the reality of companies with old code. A 1980 database managing six million daily financial transactions, with two million accumulated patches, is not terrain for an AI to “do it alone.” There, the agent does not enter, and those who pretend to replace the programmer with a subscription crash against the business logic coupled over 40 years.

Some compare this to previous bubbles: WYSIWYG editors were supposed to end HTML, code generators whole applications. In the end, they allowed a kid to tinker, but the dirty work still needed human hands. The difference this time is the pace: in six months, quality has taken a leap that others took decades.

The token economy: paying for what seemed free

All this disruption has a price, and it is not the junior’s salary. Underlying it is a question few ask: who pays for the tokens? The new offers of “AI pods” in large consultancies like Globant, where a programmer supervises agents generating code, are based on a pay-per-use model. AI is not free; it is a variable operating cost that, if not controlled, can ruin the monthly bill.

For the entrepreneur, the practical conclusion is less epic than headlines suggest: AI has indeed changed programming, but above all, it has changed the labor market. Hiring a junior to learn with you is no longer an investment; it is a luxury. Now, what matters is knowing what you want, how you want it, and knowing how to ask the machine for it. The rest, hopefully, will be retrained as electricians.

And who will train those future seniors, when today no one wants to pay for a junior?