101–110 of 197 posts
New Harvard's study (62M workers, 285k firms) shows firms adopting generative AI cut junior hiring sharply while continuing to grow senior roles — eroding the bottom rungs of career ladders and reshaping how careers start.
In 10 years where do the senior dev's come from? Real question. Seems like with lower entry level jobs now, in 10 years there won't be seniors to hire.
In the future, there will be two kinds of companies: 1. Those that encourage people to use AI agents aggressively to increase productivity. 2. Those that encourage people to use AI agents aggressively to be more productive while still hiring young people. Which type of company will be more innovative, productive, and successful in the long run?
Earlier quoted context omitted.
In 10 years where do the senior dev's come from? Real question. Seems like with lower entry level jobs now, in 10 years there won't be seniors to hire.
Even if we grant this is going to be a problem, it makes no sense for any individual company to do anything about it. Why take on the cost of training a junior when they can bail in a few years? This is especially true if you're not a big tech company, which puts you at risk of having your junior-turned-senior employees poached by big tech.
Earlier quoted context omitted.
In 10 years where do the senior dev's come from? Real question. Seems like with lower entry level jobs now, in 10 years there won't be seniors to hire.
Junior devs eventually will have been brought up with agentic coding, etc. Hopefully whatever the "new way" becomes is how they'll be taught. Currently part of the problem is the taboo using AI coding in undergrad CS programs. And I don't know the answer. But someone will find the right way to teach new/better ways of working with and without generative AI. It may just become second nature to everyone.
Pretty sure it's a self-destructive move for a CS or software engineering student to pass foundational courses like discrete math, intro to programming, algorithm & data structure using LLM. You can't learn how to write if all you do is read. LLM will 1-shot the homework, and the student just passively reads the code.
On more difficult and open coursework, LLM seems to work pretty well at assisting students. For example, in the OS course I teach, I usually give students a semester-long project on writing from scratch x86 32-bit kernel with simple preemptive multitasking. LLM definitely makes difficult things much more approachable; students can ask LLM for "dumb basic questions" (what is pointer? interrupt? page fault?) without fear of judgement.
But due to the novelty & open-ended nature of the requirement ("toy" file system, no DMA, etc), playing a slot machine on LLM just won't cut it. Students need to actually understand what they're trying to achieve, and at that point they can just write the code themselves.
"Our primary data source is a detailed LinkedIn-based resume dataset provided by Revelio Labs ...
We complement the worker resume data with Revelio’s database of job postings, which tracks recruitment activity by the firms since 2021 ...
The final sample consists of 284,974 U.S. firms that were successfully matched to both employee position data and job postings and that were actively hiring between January 2021 and March 2025.3 For these firms, we observe 156,765,776 positions dating back to 2015 and 245,838,118 job postings since 2021, of which 198,773,384 successfully matched with their raw text description."
They identified 245 million job postings from 2021 forward in the United States? I mean the U.S. population is like 236 million for the 18-65 age group (based on wikipedia, 64.9% of 342 total population).
And they find a very small percentage of firms using generative AI:
"Our approach allows us to capture firms that have actively begun integrating generative AI into their operations. By this measure, 10,599 firms, about 3.7 percent of our sample, adopted generative AI during the study period."
Maybe I am wildly underestimating just how much LinkedIn is used worldwide for recruiting? As a tech person, I'm also very used to seeing the same job listing re-listed by what seems to be a large number of low-effort "recruiting" firms on LinkedIn.
I think for trying to figure out how generative AI is affecting entry-level jobs, I would have been much more interested in some case studies. Something like find three to five companies (larger than startups? 100+ employees? 500+?) that have decided to hire fewer entry-level employees by adding generative AI into their work as a matter of policy. Then maybe circling back from the case studies to this larger LinkedIn dataset and tied the case study information into the LinkedIn data somehow.
Interesting. However just because this is true right now doesn't mean it will be true going forward. Unique to the current moment is that there are simultaneously (1) high interest rates and a challenging economy (2) a narrative that AI adoption should enable cutting junior roles. This could lead to companies that would anyway be doing layoffs choosing to lay off or not hire juniors, and replace with AI adoption. To…
I'm not disputing your point, but I'm curious: given that the main headline measures that we tend to see about the US economy right now involve the labour market. How do you establish the counterfactual?
We had some marketing folks give us a company-wide demo of Chat GPT and some other Gen AI tools and showed us how cool it is and how quick they can make stylish and sophisticated pitch decks and marketing materials now. And the entire time I'm watching this I'm just thinking that they don't realize that they are only demonstrating the tools that are going to replace their own jobs. Kinda sad, really. Demand for soft…
LLMs are good at creating single use documents, like a pitch deck used for one prospective customer (never to be used again). But for long lived documents, on which future work builds atop, the bar is higher and the value of LLMs is more grey.
Generative AI may automate some entry-level tasks, but young professionals are not just “replaceable labor.” They bring growth potential, adaptation, and social learning. Without frameworks to manage AI’s role, we risk undermining the very training grounds that prepare the next generation of experts.
It's pretty clear this is happening. The question is... is this based on existing capability of LLMs to do these jobs? Or are companies doing this on the expectation that AI is advanced enough to pick up the slack? I have observed a disconnect in which management is typically far more optimistic about AI being capable of performing a specific task than are the workers who currently perform that task. And to what exte…
For the tech side, we've reduced behavioral questions and created an interview that allows people to use cursor, LLMs, etc. in the interview - that way, it's impossible to cheat.
We have folks build a feature on a fake code base. Unfortunately, more junior folks now seem to struggle a lot more with this problem
New Harvard's study (62M workers, 285k firms) shows firms adopting generative AI cut junior hiring sharply while continuing to grow senior roles — eroding the bottom rungs of career ladders and reshaping how careers start.
In 10 years where do the senior dev's come from? Real question. Seems like with lower entry level jobs now, in 10 years there won't be seniors to hire.