Are junior and entry-level hires more or less valuable in the AI era?

Gustav Söderström · Dec 20, 2023

Big technology shifts are precisely when opportunity opens up for people early in their careers, because tenured employees keep using the old tools

New graduates lack experience but have the latest and greatest knowledge, while someone ten years into a company is using old tools

42:59 20VC Roundtable: Spotify, Adobe & Linkedin CPOs on How AI Changes The Future of Product, Why AI is Now the Product, How TikTok Changed Product, Why Cost is the Biggest Barrier to LLM Usage & Why Incumbents Can Adopt AI Faster Than Any Prior Innovation Cyc

Severin Hacker · May 19, 2025

The consensus move of freezing entry-level engineering hiring while hiring only seniors is a mistake

People who grow up using these tools early will become much better at using them, so Duolingo keeps hiring from universities

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David Cahn · Oct 27, 2025

Companies badly underestimate 23 and 24 year olds, and this is more true in AI than anywhere else

ChatGPT has only existed about five years so nobody has more than five years of AI experience; the playing field is level and in a dynamic market slope and ability to learn matter more than accumulated experience

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Clay Bavor · Jul 4, 2026

New graduates who come out of university as masters of AI tools are more valuable to employers than inexperienced young people have ever been.

University gives huge control over disposable hours to master these tools, and a thousand companies want that knowledge infused into how they work; some of Sierra's most effective employees are 22-23 and completely AI-pilled with facility more experienced staff lack.

Scope: requires the right mindset and real experience with the tools

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Harry Stebbings · Aug 8, 2026

It is much easier to train people than to retrain them, so 22-year-olds tinkering with AI tools will beat mid-career workers who are less mentally plastic

Recent graduates are mentally plastic to the tools even if not AI-maximalist, whereas a 45-year-old who has always done accounting one way is not

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Harry Stebbings · Jan 22, 2025 · hedged

Delegating analytical grunt work to AI removes the graduation pathway that trains junior professionals, leaving future senior decision makers without earned judgment

Today's GPs and managing partners learned what makes a great business by staying late analyzing companies themselves; if AI does that work, the next generation never goes through it

Scope: framed as a worry

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Richard Socher · Apr 18, 2025

The biggest worry about AI and engineering teams is that entry-level jobs are increasingly automatable, so companies need a long enough time horizon to keep training juniors even when AI could do the work

People need to reach seniority to be able to manage AI agents, because if you've never done something yourself it's much harder to manage someone or something else doing it

Scope: depends on AI not automating senior roles by the time juniors mature

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Harry Stebbings · Aug 25, 2025

The optimistic 'we'll just give you tools to do more' framing is naive — these are reductions in force, and the generation of 23-to-30-year-olds who lack deep craft expertise is about to be hit hard

That cohort has neither a passion for nor mastery of the craft, and companies like Shopify have already cut thousands of people (a good business decision) rather than augmenting them

Scope: concedes the cuts have been good for the businesses

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Aaron Levie · Apr 20, 2026

The erosion of junior legal roles is a real problem, but it is a mentorship and apprenticeship problem, not evidence that total demand for lawyers will fall

How to train the next generation when AI automates the traditional junior tasks is a genuine question facing every bank and law firm, but it's distinct from the downstream constraints that remain unautomated

Scope: concedes the apprenticeship issue is real

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Zach Lloyd · Oct 17, 2025

The importance of senior engineers is not going down

It has never been more competitive for Warp to hire someone good; the talent market is crazy competitive

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Tobias Lütke · May 4, 2026

He was wrong that engineers straight out of school with no priors would have the big advantage in AI-native programming — senior engineers with many reps steer AI models far more effectively and accomplish more in less time

Agentic programming is mostly continuous steering of the model, which is just programming at a very high level, and experience of having seen many systems makes that steering better

Scope: many young engineers are still exceptional and speed-running their careers; he isn't sure yet what it implies

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Matan Grinberg · Jun 13, 2026

Veteran engineers are more reluctant to adopt agent tools but are often better at using them, while early-career engineers adopt eagerly but manage agents poorly

Long-tenured engineers and managers know how to delegate and avoid sending a junior off for seven days on the wrong task; juniors lack standardized workflows so adopt faster but lack delegation skill

Scope: described as a balance, not absolute

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Micha Kaufman · Jun 9, 2025

Companies should maximize the capacity of the existing team before hiring more people, and any new hires must be AI-native regardless of function

This was true even five years ago; running lean but not too lean means you know who the first 50 cuts would be — and if you know that, you should already say goodbye

52:29 Junior marketers are being automated faster than junior developers

George Sivulka · Jan 22, 2025

AI tooling will make juniors better investors rather than hollowing out their development, because it lets them reason over every deal in a firm's history instead of relying on one senior partner's remembered sample

Senior judgment is really depth of pattern data — 'I've seen 20 companies like this' — and a junior with a matrix over the full deal history can quantify percentile performance across more deals than any partner has ever seen

31:33 Ai augments junior judgment by giving access to full firm history not hollowing out development

Andrew Ng · Nov 17, 2025

The white-collar pipeline problem is not that juniors are being replaced; it is that workers of any seniority who haven't learned AI are the ones in trouble

In software engineering he observes a ranking: experienced engineers on top of AI are most productive, then AI-fluent fresh grads, then ten-year veterans still coding like it's 2022, with non-AI fresh grads worst off; he no longer hires people who code the old way

16:12 Ai fluency not seniority decides who is at risk

Harry Stebbings · Jan 31, 2026 · hedged

Workers in their forties and above face poor prospects in an AI-driven labour market

Older workers tend to use AI merely as a better Google rather than as an operating system for how they work, which matches what he observes

50:15 Workers over forty lose out because they use ai as a better search