In 2019, I helped hire two junior developers for a team I was working with. They were fresh out of school, nervous during their interviews, and their code was — let’s be generous — rough. One of them mixed up let and const like they were interchangeable seasoning. The other wrote a function so deeply nested it looked like a geological cross-section.

Within eighteen months, both of them were running features end-to-end. One became our go-to person for a legacy migration nobody else wanted to touch. The other started mentoring newer juniors.

That’s how it’s always worked. You bring people in at the bottom, hand them the boring stuff, and watch them grow. But right now, across the industry, companies are quietly bricking up that doorway. And the data is staggering.

The employment cliff

Entry-level tech job postings dropped 67% between 2023 and 2024. Employment among developers aged 22 to 25 declined by roughly 20%. According to ADP Research, overall “programmer” employment in the United States fell 27.5% since its peak.

Let those numbers land for a moment. We’re not talking about a minor dip. We’re talking about an entire generation hitting a locked door.

Decline in entry-level tech job postings from 2022 to 2025

A Harvard study covering 285,000 firms and 62 million workers found that within six quarters of adopting AI tools, junior employment dropped 9 to 10%. But here’s the twist: employment for workers aged 30 and older grew by 6 to 12% in the same period. Companies aren’t shrinking — they’re reshaping. They’re cutting the bottom rungs of the ladder while piling more weight on the top.

“Today’s juniors are tomorrow’s senior engineers. Cut off the pipeline and you create a leadership vacuum in five to ten years.”

The reasoning from management is seductively simple. AI can write boilerplate. AI can scaffold a CRUD app. AI can handle the kind of work that used to fill a junior’s first year. So why pay a human to do it?

I’ll tell you why.

The talent doom cycle

Chris Eldridge, CEO of recruitment firm Robert Walters, coined a term for what’s happening: the talent doom cycle. It works like this:

  1. Cut junior roles because AI can handle “simple” tasks.
  2. Starve the pipeline of developers gaining real-world experience.
  3. Scramble to hire experienced seniors externally when you need them.
  4. Pay inflated salaries because everyone else starved their pipeline too.
  5. Face cost pressure from those expensive senior hires.
  6. Cut more junior roles to compensate.
  7. Repeat.

It’s a feedback loop with a time-delayed detonation. The savings feel real today. The cost shows up in 2030 when there aren’t enough mid-level and senior engineers to go around — because nobody trained them.

Hiring manager attitudes have shifted in lockstep. According to Stack Overflow’s research, 70% of hiring managers believe AI can do intern-level work. 57% say they trust AI more than they trust interns. And 37% would rather “hire” an AI than a recent graduate.

Read that last one again. More than a third of hiring managers would prefer a language model to a human being who needs to learn.

Bainbridge saw this coming in 1983

This pattern has a name, and it isn’t new. In 1983, Lisanne Bainbridge published a paper called Ironies of Automation that should be required reading for every CTO making workforce decisions right now. Her core argument is deceptively simple:

The more advanced a control system becomes, the more crucial human expertise becomes for the cases where the system fails.

Bainbridge was writing about industrial automation — pilots, nuclear operators, manufacturing. But the parallel to software is almost eerie. When everything runs smoothly, you don’t need the human. When the automated system produces garbage, hallucinates, or fails silently, you desperately need someone who understands the underlying domain well enough to intervene.

Here’s the irony (and it really is ironic, in the structural sense): AI automates exactly the tasks that used to train juniors. Writing boilerplate. Building CRUD operations. Debugging simple issues. Tracing through code line by line. These weren’t make-work. They were learning-by-doing. They built the mental models that eventually made someone a capable senior engineer.

Remove those tasks from a junior’s trajectory and what do you have? A generation of developers who can prompt an AI but can’t reason about what it produces. Who can ship code but can’t debug it when it breaks in production at 2 a.m. (And it will break at 2 a.m. It always does.)

The three-phase crisis

Octopus Deploy’s AI Pulse Report maps out the timeline with uncomfortable specificity:

Phase 1 — Experimentation (2024-2025): Companies adopt AI coding tools. Productivity appears to rise. Junior developers start looking redundant on spreadsheets.

Phase 2 — The junior hiring freeze (2025-2027): Entry-level positions dry up. Internship programs shrink. Bootcamp graduates find a market that doesn’t want them. The pipeline narrows to a trickle.

Phase 3 — The senior talent crisis (2027-2030): The industry discovers, with dawning horror, that seniors don’t materialize from thin air. The mid-level developers who should have been moving into leadership roles don’t exist in sufficient numbers because they were never hired as juniors.

We’re currently deep in Phase 2. And most companies are behaving as though Phase 3 is someone else’s problem.

Wharton researchers have described this as the “vanishing ladder” problem — the traditional career progression from junior to mid to senior that has sustained the industry for decades is being dismantled from the bottom. Their analysis warns that the consequences will be felt industry-wide, not just at individual firms.

But wait — are developer jobs actually dying?

This is where the data gets nuanced, and where a lot of panic-driven headlines get it wrong.

The Bureau of Labor Statistics draws a distinction between “programmers” and “software developers.” Programmer roles — the category that historically covered people who mainly write and maintain code — declined 27.5%. But software developer roles declined only 0.3% and are projected to grow 17% through 2033.

What does that gap tell us? The job isn’t dying. It’s transforming. The pure “write code to spec” role is shrinking. The “design systems, make architectural decisions, understand the domain, communicate with stakeholders” role is growing. As IEEE Spectrum notes, AI is compressing the bottom of the skill ladder, not eliminating the profession.

Addy Osmani (engineering lead at Google) puts it well: AI won’t kill junior developers, but your hiring strategy might. The technology itself isn’t the threat. The organizational response to the technology is.

The distinction matters. AI changes what developers do, not whether developers are needed.

What this means if you’re starting out

If you’re a junior developer or a recent graduate reading this, I know the landscape looks bleak. The numbers don’t lie — it is harder to get that first role than it was five years ago. But the demand for capable, thoughtful developers hasn’t evaporated. It’s shifted.

Here’s my honest take: lean into the things AI can’t do well. Understand why systems are designed the way they are, not just how to build them. Get comfortable reading other people’s code — really reading it, not just skimming. Learn to debug without leaning on autocomplete. Build things that break and figure out how to fix them. (I know that sounds like your grandfather telling you to walk uphill both ways, but the developers I’ve watched grow fastest all share one trait: they’re comfortable being confused and keep digging anyway.)

The Stanford Digital Economy Lab calls junior developers “canaries in the coal mine” — the first group affected by a shift that will eventually reshape every experience level. If the canaries are dropping, it’s a signal to pay attention, not to seal the mine and pretend everything’s fine.

What this means if you’re a manager

Stop treating junior hiring as a cost center. It’s infrastructure investment. Every junior developer you don’t hire today is a senior engineer you won’t have in 2030.

Redesign junior roles instead of eliminating them. Yes, AI can write the boilerplate. So let juniors focus on code review, testing strategy, understanding the codebase holistically, and learning to evaluate what AI produces. The CIO article on this shift makes a compelling case that the junior developer role needs to evolve, not disappear.

And if your company’s AI strategy depends on never needing to grow new talent — if your entire plan assumes you can always buy senior engineers on the open market — I’d suggest stress-testing that assumption. Because every other company is making the same bet. And there aren’t enough chips on the table.

The real cost of short-term thinking

There’s a version of this story where the industry course-corrects. Where companies realize that the talent doom cycle is real and start investing in training again, just structured differently around AI-augmented workflows. Where junior roles evolve rather than vanish.

And there’s a version where we don’t. Where we spend the next three years congratulating ourselves on headcount savings and then spend the five years after that in a brutal, expensive war for senior talent that barely exists.

I’ve been in this industry long enough to know which version is more likely. We tend to optimize for this quarter’s numbers and deal with the consequences later. But if you’re in a position to influence hiring decisions, you have a genuine opportunity to be the exception.

The juniors you invest in today won’t thank you next quarter. They’ll thank you in 2030 — by being the senior engineers your company desperately needs.

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