Why Not Hiring Junior Engineers Is a Mistake

Not hiring junior engineers won't solve the problem you think you have

Why Not Hiring Junior Engineers Is a Mistake

A CTO's decision to stop hiring junior engineers, driven by AI fears, is misguided. Junior engineers are essential for talent retention and adaptability. The real problem isn't AI or juniors, but a waterfall-like system that reduces engineering to coding tasks. In an AI-first world, engineers still deliver value, and juniors will handle simpler versions of those tasks. Companies that embrace all levels of engineers will outperform those that don't.

If the industry is changing that fast, experience is the depreciating asset, and the people arguing juniors can’t adapt have the most to unlearn.
  1. lbriner

    I'm not sure I understand the logic that we wouldn't hire Juniors because now we have AI.

    What jobs are Juniors doing that AI can now do? I don't get juniors to build me entire web sites or implement complicated agentic pieces of work. Most of the time, we hire Juniors to help fill the talent pool with the hope that they will be productive in a few months. If we think that we don't need to refill the pool now because of AI, then that is daft although I can understand a period where companies are deciding whether they still need 50 Developers instead of 20 + AI.

    For me, the worst change for Juniors is remote working. I don't want the experience of newly qualified engineer being sitting in their bedroom all day chatting to people on Teams and not knowing when they can interrupt and when they can't. We used to have an office so we could at least do 2 days per week together but we don't any more. The banter, the office, the observation, the overhearing things is a critical part of both learning engineering and learning how to be part of a workplace.

  2. mikeocool

    Pre-AI juniors were valuable because on many tasks, it was faster for me (senior eng) to write a quick spec have a conversation with a junior, and have them go off for a few hours or a few days and write the code, and then come back with it for review. I could do that with several junior engineers and pretty reasonably paralellize the work.

    Now a junior takes my spec, drops it into Claude, and submits a PR a few minutes later. So I'm back to being the bottleneck -- there's constant pressure to provide specs and review code, and ultimately that process is just me having an indirect conversation with Claude (em dash is mine).

    The junior is probably providing negative value, since it would be more efficient for me just to talk to Claude, and they're not learning anything, because it's really hard to learn anything by skimming code that's being pooped out by Claude.

    I'm not sure what the solution to this is, I still think we need to train junior engineers. I think my best advice to juniors right now is stop using Claude so much. Use it to plan and answer questions, but you should still be writing code even it's slower. Because that's the only way they're going to learn enough to effectively guide AI and review output and get past being a net negative.

  3. uberman

    I'm not sure what the article actually has to say about the topic it presents. It seems to want to be something about not hiring junior talent (something by the way not restricted to the tech industry) but instead it ends up more a critique about people wanting to use a waterfall pipeline.

  4. cnj

    The problem I have: The CEO (and the investors, or the whole industry) is obsessed with ARR per employee. That's the key metric (in their mind).

    It doesn't matter how much the employee costs. Let's assume you can hire two Juniors or one Senior for the same salary. If you have to optimize for ARR per employee - you can only hire one person. And if you have the choice between hiring a Junior or hiring a Senior... you're going to hire the Senior.

    Goodhart's law fully applies here.

  5. CoffeeOnWrite

    I would have liked the article to address more specifically what skills will be needed in the future and how engineers of all levels will learn them. Senior engineers in my circle feel their own brainrot, and at the same time feel like super wizards combining our deep software knowledge with the amazing AI dev tools. How will the AI native engineers learn the things, do they need to learn the things, what does anybody need to learn anyway? Let’s talk about it.

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