The bottom rung. The danger isn’t the lost jobs. It’s the layer that made the seniors.

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TL;DR

Entry-level jobs in the US have fallen significantly since early 2023, but the key issue is the erosion of the training layer that develops junior workers into seniors. Experts debate whether this change is temporary or structural, with potential long-term consequences.

Entry-level job postings in the US have decreased by approximately 35% since early 2023, with some sectors experiencing declines of up to 67%, according to recent data. This contraction is reshaping the traditional career ladder, raising questions about the long-term development of skilled professionals.

Data from sources such as Thorsten Meyer indicates that the decline in entry-level positions is not solely a cyclical response to economic conditions but also reflects a fundamental shift in how junior work is performed. Notably, hiring of recent graduates by major tech firms has dropped by 50% from pre-pandemic levels, and unemployment among college graduates aged 22 to 27 has risen above the national average to nearly 6%. These figures suggest a shrinking pipeline for developing expertise.

While some analysts attribute the decline to a temporary hiring freeze or economic cycles, others warn that automation—particularly AI—has directly replaced the routine tasks traditionally performed by juniors, such as coding, data cleaning, and document review. This automation eliminates the training ground for future senior roles, potentially leading to a long-term skills gap.

The Bottom Rung — Thorsten Meyer AI
RUNG
● DISPATCH / JUNE 2026
THORSTEN MEYER AI · POST-LABOR · NEWS-FLEX
POST-LABOR · FLEX
ENTRY-LEVEL / RUNG
Dispatch · Entry-Level-Compression Forensic · 2026-06-09

The bottom rung.
The danger isn’t the lost
jobs. It’s the layer that
made the seniors.

The first rung of the career ladder is narrowing fast. The deeper story isn’t a job-loss wave — it’s the apprenticeship layer disappearing.
The numbers are large and consistent: entry-level postings down ~35% since 2023, junior tech roles down 67%, big-tech graduate hiring down ~55% from pre-pandemic, recent-grad unemployment above the national rate. But the instinct to read this as a job-loss story misses the point. AI is automating exactly the “drunt work” that was simultaneously a junior’s job and a junior’s training — so the firm saves the salary now and loses the pipeline that produces its seniors. The structural argument: the genuine risk is deferred — a broken expertise pipeline whose cost appears not in this year’s unemployment rate but in a decade’s senior shortage — and whether that risk is real or whether the rung rebuilds in a new form turns on a cyclical-versus-structural confound the data cannot yet resolve.
−67%
Junior tech / data postings ·
since 2022 (the steepest decline)
−55%
Big-tech recent-grad hiring ·
vs pre-pandemic levels
~6%
Recent-grad unemployment ·
above the national rate (a reversal)
a decade
To rebuild a broken pipeline ·
the deferred, asymmetric cost
THE BOTTOM RUNG· THE DANGER ISN’T LOST JOBS · IT’S THE LAYER THAT MADE THE SENIORS· ENTRY-LEVEL POSTINGS DOWN ~35% SINCE 2023 · TECH UP TO 67%· BIG-TECH GRAD HIRING DOWN ~55% VS PRE-PANDEMIC· RECENT-GRAD UNEMPLOYMENT ABOVE THE NATIONAL RATE · A REVERSAL· AI AUTOMATES THE “DRUNT WORK” THAT WAS THE TRAINING· THE GRUNT WORK WAS THE CURRICULUM· STRANDED BETWEEN AI AGENTS AND SENIOR INCUMBENTS· SAVINGS NOW · SENIOR SHORTAGE LATER · THE DEFERRED COST· OR THE RUNG REBUILDS · WEF, MCKINSEY +12%, ROPES & GRAY 400 HRS· THE CONFOUND · AI OR THE 2020-22 RATE CYCLE REVERSING?· CHEAP TO PROTECT · EXPENSIVE TO LOSE · THE ASYMMETRY· PROTECT THE RUNG BEFORE PROOF· THE BOTTOM RUNG· THE DANGER ISN’T LOST JOBS · IT’S THE LAYER THAT MADE THE SENIORS· ENTRY-LEVEL POSTINGS DOWN ~35% SINCE 2023 · TECH UP TO 67%· BIG-TECH GRAD HIRING DOWN ~55% VS PRE-PANDEMIC· RECENT-GRAD UNEMPLOYMENT ABOVE THE NATIONAL RATE · A REVERSAL· AI AUTOMATES THE “DRUNT WORK” THAT WAS THE TRAINING· THE GRUNT WORK WAS THE CURRICULUM· STRANDED BETWEEN AI AGENTS AND SENIOR INCUMBENTS· SAVINGS NOW · SENIOR SHORTAGE LATER · THE DEFERRED COST· OR THE RUNG REBUILDS · WEF, MCKINSEY +12%, ROPES & GRAY 400 HRS· THE CONFOUND · AI OR THE 2020-22 RATE CYCLE REVERSING?· CHEAP TO PROTECT · EXPENSIVE TO LOSE · THE ASYMMETRY· PROTECT THE RUNG BEFORE PROOF·
FIG. 01 — THE COLLAPSE · LARGE AND CONSISTENT ACROSS SOURCES
The entry-level layer is unambiguously contracting — the phenomenon is not in dispute
The contraction is sharpest exactly where AI is most capable
Junior tech / data postingssince 2022
−67%
Big-tech recent-grad hiringvs pre-pandemic
−55%
All entry-level postingssince early 2023 (Revelio)
−35%
LinkedIn entry-level rateDec 2025 – Feb 2026
−6%
Recent-grad unemployment has climbed to ~5.6-6% — above the national rate, a near-unprecedented reversal (a degree usually buys a lower rate). Grads aged 22-27 are 5% of the workforce but contributed 12% of the unemployment rise since mid-2023. The concentration of the collapse exactly where AI is most capable — software, data, analysis — is the first reason to suspect this is more than a hiring cycle, even if a hiring cycle is part of it.
FIG. 02 — THE APPRENTICESHIP MECHANISM · WHAT THE RUNG ACTUALLY WAS
The bottom rung was never just a job — it was how professions reproduced themselves
AI is the first technology to automate the grunt work the training rode on
The rung’s dual function
Grunt work = curriculum
The junior did the rote tasks (basic coding, first-draft research, doc review) and learned the trade in the same motion. Inseparable.
AI
automates
the task
What AI severs
The task, and its training
When AI does the grunt work at near-zero cost, it removes the task and the training the task provided. The job that remains is verification — a senior skill.
As AI does the production, the human job shifts from creation to verification — but you cannot verify code you never learned to write. The work that remains is the senior work, and the rung that would have taught a junior to do it has been automated away — leaving early-career workers stranded between the AI agents below them and the senior incumbents above, with no rung to climb from.
FIG. 03 — THE DEFERRED COST · WHY THE DANGER IS INVISIBLE NOW
Cutting the rung saves money this year and pays the bill a decade out
Which is exactly why the bill gets run up
Now · concentrated, visible
The savings
Fewer salaries, more AI efficiency. Immediate, bankable, real — that’s what makes the trap work.
Later · diffuse, deferred
The shortage
No mid-career professionals, because the roles that produced them are gone. Appears years later, when seniors retire.
The standard error is to wait for an unemployment spike as the signal of structural change — but labor markets adjust earlier and quietly, through fewer hires and longer searches. By the time a senior shortage shows up in a metric, the rung will have been gone for a decade, and rebuilding a pipeline takes another. A rational firm optimizing for the quarter cuts the rung; an economy of rational firms dismantles the apprenticeship layer with no one deciding to.
FIG. 04 — THE RESHAPING COUNTER-CASE · THE RUNG MIGHT REBUILD
The strongest counter: entry-level work isn’t disappearing but transforming
Backed by serious institutions and firms acting against the trend
The thesis (WEF)
From doing to reviewing
Roles reshaped — task execution → judgment, drafting → reviewing, producing → triaging the machine’s output. The rung becomes a different, higher-order rung.
The firms acting on it
Rebuilding deliberately
McKinsey +12% hiring in 2026; Ropes & Gray gives first-years 400 of 1,900 hrs on AI; Accenture apprentices = 20% of NA entry-level; tech apprenticeships +29%.
PwC’s survey of 9,394 entry-level workers across 48 economies found them more curious (47%) and excited (38%) than worried (29%). The reshaping case isn’t wishful thinking — it’s backed by institutions acting on it, firms investing in it, and the affected workers’ own read. On this view AI makes the apprenticeship layer more valuable, and the firms cutting the rung are making an error the smart ones are correcting.
FIG. 05 — THE CONFOUND & THE ASYMMETRY · HOW MUCH IS AI AT ALL
The same data fits both stories — and they imply opposite responses
The collapse coincides almost exactly with the post-2022 rate cycle
If mostly cyclical
If mostly structural
The 2020-22 zero-rate overhiring reverses (Meta ~2x, Alphabet ~1.6x); entry-level cut first. The rung rebuilds when rates fall.
AI automates the training layer itself. The rung doesn’t come back; the pipeline breaks.
“Eerily close” to past rate-driven freezes (Stanford Review). A technological scapegoat.
A generation of missing mid-career expertise.
The asymmetry resolves what the data can’t: cheap to protect (some redundant junior hiring), expensive to lose (a decade to rebuild the pipeline). Protect the rung now — the same no-regrets logic the ownership case rests on, applied to the training layer.
The first thing AI changes about work may not be how many jobs exist, but whether there is still a way to learn to do them. The firms quietly cutting the rung for this quarter’s efficiency are running an experiment whose result they will not see until it is too late to undo.
Thorsten Meyer · The Bottom Rung · Post-Labor news-flex

Risks of Losing the Junior Training Layer

The contraction of entry-level roles threatens to dismantle the apprenticeship system that traditionally groomed workers into senior professionals. If this layer disappears permanently, it could result in a future shortage of skilled experts, impacting industries’ ability to innovate and grow. The debate centers on whether current changes are temporary or indicate a structural shift that could reshape workforce development for decades.
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Shifts in Entry-Level Hiring and Automation Trends

Historically, entry-level roles have served as the foundation for workforce development, with juniors performing rote tasks that build expertise. Recent years have seen a sharp decline in these roles, driven partly by a cyclical slowdown and partly by AI automation. Major firms like McKinsey and the WEF suggest that this shift might be a transformation rather than a collapse, as some companies are investing in new forms of junior work and AI-based apprenticeships. However, the long-term impact remains uncertain, with experts debating whether the current decline signals a temporary pause or a permanent change in the training pipeline.

“The most important consequence of the entry-level contraction is the potential dismantling of the apprenticeship layer, which risks breaking the pipeline that produces future senior expertise.”

— Thorsten Meyer

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Unresolved Questions About Workforce Development

It remains unclear whether the decline in entry-level jobs is primarily a cyclical phenomenon that will reverse when economic conditions improve or a structural change driven by AI automation that will permanently alter the training pipeline. The extent to which firms are investing in new apprenticeship models versus simply cutting roles is also still being evaluated.

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Monitoring Workforce Trends and Policy Responses

Future developments will depend on economic recovery, technological advancements, and corporate strategies. Analysts will watch hiring patterns, investments in AI-based training, and education policies to assess whether the traditional apprenticeship layer can be rebuilt or if new models will emerge to fill the gap. Long-term workforce planning will be critical to address potential skills shortages.

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Key Questions

Why is the decline in entry-level jobs a concern for the future workforce?

Because these roles traditionally serve as training grounds for developing expertise and leadership in various professions. Their decline may lead to a shortage of skilled workers in the future.

Is the current decline in entry-level hiring temporary or permanent?

It is currently uncertain. Some experts believe it is cyclical and will reverse with economic recovery, while others warn it could be a permanent structural shift due to AI automation.

How is AI affecting the training of junior workers?

AI automates many routine tasks that juniors used to perform, potentially eliminating the traditional learning opportunities that helped them develop into senior roles.

What can companies do to prevent a skills shortage?

Investing in new apprenticeship models, rethinking junior roles, and integrating AI with training programs could help sustain the pipeline of skilled professionals.

Source: ThorstenMeyerAI.com

This content is for general information only and is not financial, tax or legal advice. Consult a qualified professional for decisions about your money.
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