The article essentially says that, for a junior to be hired, they should demonstrate the same experience as a senior: deploy real system that solve real problems, know how systems behave in production, etc. That is precisely the skillset that someone builds up in a professional environment, i.e. after being hired.
In my view and experience (20+ years in the field) the value of junior colleagues is not in what they already know how to do, but in the freshness of their ideas, and the ability to learn the skills required to bring those ideas to fruition.
So, I agree that the hiring pipeline is broken, but for a different reason: companies stopped looking at juniors as a long-term investment.
I can think of a few reasons for that. In any case, that mindset is to blame, not the "kids" and their education.
Additionally, getting into the best school possible is critical. The top 20 CS, CE, EE, ECE, and EECS undergrad programs in the US graduate around 15-20k students a years. That is a large enough pool to recruit from for NCGs. For diversity reasons, employers will often also recruit from Veteran programs and some respected regional colleges (eg. SJSU, CalPoly, or SCU in the Bay or UTD, UTA, or UTSA in Austin) and then call it a day, so where you go truly does matter.
Social capital matters more than just about anyone who has a degree can understand and tell you or mentor you about, because the majority of them have always had it, and they tend not even to interact with people without it.
It is a signal about your wealth (and your families ability to deploy it for you), from which follows your stability, your intelligence, your taste, your willingness to play the game, and your belonging in the club. These matter more than EVER in the business world - I've never seen a time when tech is less about engineering than right now.
Alarming doesn’t begin to describe it. This is an existential crises for our industry. The situation for entry level has been dire for some time. Those of us who have decades experience have nothing to worry about; the companies who replace juniors with AI are doomed. It takes years to gain proficiency with art of software engineering. Who will replace us? Or what am I missing?
I know plenty of programmers with degrees other than computer science. Geologists, biochemists, theoretical physicists, etc. Most hard sciences involve some degree of programming at this point (usually Python). And with AI, system thinking is becoming much more relevant than deep algorithmic knowledge or math skills. Nice if you can do that stuff manually but not that essential anymore.
also right now nothing is higher signal than a new grad who built a product with actual paying users
Why? You don’t narrow your scope at the beginning!
How could this possibly signal competence? I think it just signals capital and free time.
Idk though, really seems like the "AI layoffs" are just corps shedding headcount bloat accumulated in 2020-23.
I never understood why software engineers were so excited about open source and teaching everyone to code.
Why aren‘t we more like doctors or lawyers?
Hope you like being overworked!
That country never ceases to astonish me lol.
I am very curious how this changes for young technologists in an AI era, where maybe non-technical people in this layer no longer see a self made technologist as a value add to their cohort.
I purposely use technologist over software developer, since I feelnthe generalist self-made developer typically commands an intuitive breadth of skills not just programming.
I also didn't make out like Zuck, though I am happily working and making games on the side.
You only miss a bad job market entry and low salaries, you need every meagre advantage you can get.
100% agree on a degree being a strong signal, by the way.
Yes, this has unemployment computer engineering at #2 with 7.8% and computer science at #5 at 7.0%.
Philosophy is at 5.1% unemployment.
The next column is also important to look at - the underemployment rate. Is the graduate in a profession that requires the degree.
The underemployment rate is defined as the share of graduates working in jobs that typically do not require a college degree. A job is classified as a college job if 50 percent or more of the people working in that job indicate that at least a bachelor's degree is necessary; otherwise, the job is classified as a non-college job.
Underemployment for computer engineering is at 15.8% (3rd lowest) and computer science is at 19.1% (9th lowest).
If you want a unemployment rate for computer science that matches philosophy the answer is easy - hold your nose and take the front desk receptionist job.
Also... sort by "median wage early career." Computer engineering and computer science are #1 and #2 at $90k and $87k. There's something important there too - most college graduates are not getting $100k/year jobs. That expectation of Big Tech wages out of college and turning one's nose up at a job that offers the median claiming that "it isn't competitive" may be contributing to the unemployment rate.
There isn't an existential crisis there. Most college graduates are finding jobs in the profession and computer science and engineering (from that data) are the highest paying college majors.
Left unstated is what jobs philosophy and art history majors take.
There's more computer scientists working in computer science than there are philosophy or art history majors working in philosophy or art history.
Maybe, but the degree has to be paid for, with time and money.
I'm worried the slop can remain irrational longer than I can remain solvent
I draw the line at things that directly impact my net worth.
> Do you not care about global warming because you're probably not going to experience an unsurvivable wet bulb temperature where you happen to live in your lifetime?
Correct. I don’t care about global warming or climate change.
Blacksmithing as a profession isn't dead either, it is still possible with the right approach. Just don't expect knights to come knocking asking you to make them the next Excalibur.
I suppose that makes a change from it's not happening or it is happening but it isn't man made or it is man made but we can't do anything about it.
If I decide you're having a negative impact on my net worth, can I come to your home and shoot you in the head?
It seems we need a remedial class in morality here, where we work up to you understanding the golden rule. But perhaps you're not capable of understanding that. Is euthanizing you then the only option?
Currently the only method to stop students from cheating is to run strictly controlled paper-based exams, and with smart glasses with built in LLMs, this is becoming more and more problematic. Anything not run under strict conditions is entirely untrustworthy.
Management is slow to catch-up or react and the lecturers running these degree courses are under significant pressure to increase the results. I'm aware that many are doing class-wide weighted adjustments just to keep the numbers of passing students up. The quality of students graduating with CS degrees is declining rapidly.
[1] https://www.dailycal.org/news/campus/academics/failing-grade...
Would it be 80s technology everywhere but widely deployed? Or would things have advanced further - better compilers, more ergonomic languages, better platforms etc? I don't know. But I suspect we'd still have needed people studying computer science to advance the state of the art.
Now looking forward 30-40 years from now, will everything still run on 2020s technologies?
A degree simplifies the cognitive resources needed to gain trust. Normally, gaining trust requires a lot of time. As a freelancer, it took me two years of very low-income work and repeatedly taking small jobs before I got my first real contract, simply because I didn't have a good degree.
But if you have a degree, you can skip that starting line quickly. I've done over 400 small jobs—work for college students, professors, and business owners. 80% of those were won with the lowest bid. And because I took those low-bid jobs, I eventually landed fairly well-paying contracts (about 35 of them) where I even drafted the contracts myself.
Moreover, while they say you can learn without a degree, it's much harder.
Why? Because a degree provides guidance through a curriculum. When you're just starting out, you don't even know what you need to learn. You have to ask around and figure it out piece by piece. A degree, even if you don't study properly, at least gives you the keywords to search for. Without a degree, you don't even know what it is you're trying to do.
I don't have a computer science degree, nor did I attend a good university. That's why it took an enormous amount of time to generate income from computer-related work. And even then, the vast majority of jobs paid below minimum wage, if anything at all.
That is a really interesting admission upon which to evaluate your other comments here…
Isn't this just grading on a curve, which has been done probably as long as universities have existed? The key is the instructor making sure a high standard is met (which seems to be the crux of the issue).
Less competition for me, and "educators" are being punished HARD for their abrogation of their actual responsibilities, which was to teach and give exams.
All exams should be verbal. The fact that verbal exams are so rare is because teachers/professors are overworked and (outside of AI) underpaid. Too many students, not enough time.
The moment you pull up a powerpoint and start reading off of it, or start assigning homework, you've already failed to implement the traditional liberal arts education that the humanities seems to fawn over so much.
There's ACTUALLY no solution to blooms two sigma problem (https://en.wikipedia.org/wiki/Bloom%27s_2_sigma_problem) except for teachers to fundamentally change their responsibilities. More time needs to be spent being intention to every individual student. If that means we need fewer students in universities, so be it. AI will kill the impenitence for higher education anyway.
If anything it seems wide deployment of LLMs would go against this. When nobody writes code by hand anymore, who will care about the ergonomics of programming languages? And even if a few do care, how would you get adoption? I expect everyone will just use whatever is already used most.
I made it 15 years on mostly willpower earning millions of dollars, but never worked for a FAANG in any capacity, was unemployed (and even homeless) for different stints starting out, and to this day still get asked why I don't have a CS or engineering degree.
And a Haiku-powered Claude Code could now probably one-shot most of the stuff I have ever banged my head on as hard as I could to figure out.
I am just reflecting on the past though. What will make you "successful" then won't be what makes you that now.
Universities consist of a wide range of people with different incentives, the lecturers typically (in my experience) have very pure motives. It's the management parts that put pressure to pass students, meet metrics, etc.
> The moment you pull up a powerpoint and start reading off of it, or start assigning homework, you've already failed to implement the traditional liberal arts education that the humanities seems to fawn over so much.
Homework is essentially dead post-LLMs. The lecturer's responsibility is to provide guided learning, but also most importantly to assess each student's attempt to learn.
> There's ACTUALLY no solution to blooms two sigma problem (https://en.wikipedia.org/wiki/Bloom%27s_2_sigma_problem) except for teachers to fundamentally change their responsibilities. More time needs to be spent being intention to every individual student. If that means we need fewer students in universities, so be it. AI will kill the impenitence for higher education anyway.
You'd be surprised how much 1:1 with students there are. One example I'm aware of is CS students getting 4 hours 1:1 for one module per semester - that's a hell of a lot.
What you're ultimately up against is cost per student. The overheads in Universities are enormous. It's usually 40:60:+, so £40k pay, £60k overhead plus research and investment (conference paper, travel, journals, new tools, etc).
I lived in a 3 pyeong (about 100 sq ft) space for three years (I wasn't homeless, so I had it better than you). Still, I'm grateful that now I have a small 8 pyeong (about 260 sq ft) space. Thank you for sharing your experiences and emotions.
I want to succeed through willpower, just like you. As you know, most of my coding is done better by AI. Unless it's large scale programming, the work that comes to people like us is usually small scale, handled at the level of specific frameworks.
Nevertheless, I still believe there is a place for me somewhere (though that might be self hypnosis).
Thanks for the comment
It seems that now more than ever, testing is important. But LLMs love to cheat the tests and make them superficially pass. If you're never reading the code, how do you know changes are reasonable?
Do you see lots of posts about new compilers and languages and language features on HN in the last year? Maybe I just missed them. I'd love to read more posts like that and fewer about agent frameworks.
This article is crossposted from IEEE Spectrum_’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written i_n partnership with tech career development company Parsity and delivered to your inbox for free!__
There is no shortage of people telling recent engineering graduates that their degree was a mistake and that AI is coming for their jobs before they even land one. I respectfully disagree.
I have been a software engineer for 12 years, done well over 100 interviews on both sides of the table, and run Parsity, an AI engineering program. A few patterns emerge consistently in who actually breaks through in today’s job market. Here’s why I think the job market isn’t as dire as it looks, and what I would do if I were looking for my first tech job.
The Federal Reserve Bank of New York recently placed unemployment for recent CS graduates in the United States at 6.1 percent, with computer engineering graduates at 7.5 percent. Compared to philosophy majors at 3.2 percent and art history graduates at 3.0 percent, those figures look alarming. They require more context than most headlines provide.
When researchers factor in underemployment (graduates working jobs that don’t require a college degree), then engineers are doing relatively well, coming in below 20 percent, against a 42 percent average across all recent graduates. Many majors reporting lower unemployment are achieving that figure by accepting work entirely unrelated to their field. Scored across unemployment, underemployment, and early-career earnings together, CS and computer engineering still rank among the top fields for overall labor market outcomes.
The degree is not the problem. The hiring pipeline is. Job postings labeled “entry-level software engineer” grew roughly 47 percent between late 2023 and late 2024, while actual hiring into those roles dropped approximately 73 percent in the same window. So-called “ghost jobs,” used to create an illusion of company growth, are everywhere. This makes the front door harder to find, but it exists.
Do a broad search of your (real-life) network. Roughly 26 percent of job offers come through referrals. Look at your actual network—classmates, professors, past internship contacts, relatives—and identify people at companies that might be hiring. The goal is a warm introduction to someone who is or knows a decision maker. One introduction carries more weight than a hundred cold applications through a portal.
Find symmetric risk. A junior engineer is a risky hire by definition. A startup carries a matching risk profile, meaning potentially lower compensation, no certainty of longevity, and higher performance expectations. But that shared risk creates mutual interest. The learning curve is steep, the exposure is broad, and the track record transfers directly. For engineers whose longer-term goal is a large organization, a startup is not a detour. It can be how you build the experience those organizations eventually want to see. The first job is for validation and learning. It is not a life sentence.
Manufacture experience rather than waiting for it. Employers want experience but will not hire you to get it. The way through is to create it: a deployed project, an open-source contribution, building something real for a small business or family member. Recruiters are skeptical of toy projects. A deployed application solving a real problem, combined with the ability to talk clearly about the decisions you made and why, still moves the needle.
Gain practical AI engineering skills, not just AI tool fluency. Using Cursor or Copilot is now a baseline expectation. What differentiates candidates is going one level deeper. Most working engineers, including senior ones, have not built a RAG pipeline or designed a multi-agent system. Understanding how to chunk documents, generate embeddings, store and query them from a vector database, and wire it into a production application puts a candidate ahead of a significant portion of the market on a skill in rapidly growing demand. AI and data science roles grew 163 percent in job postings in 2025. The engineers who understand how these systems actually work, not just how to prompt them, are in the shortest supply.
Stop optimizing around conditions you cannot predict. Nobody anticipated the 2021 hiring boom. Nobody predicted this correction. Build durable skills. The demand for engineers who can reason clearly about systems is not going away. Where you start is not where you end.
—Brian
More major workforce reductions are on the horizon at Big Tech companies: Meta announced it will cut 10 percent of its workforce, or about 8,000 employees, and Microsoft plans to offer buyouts for 7 percent of its U.S. employees in a voluntary retirement program. The cuts are understood by many to be linked to AI. But is AI really to blame? For The Conversation, two academics at the University of Sydney give their two cents.
Tom Burick got his start as a roboticist. But when a financial downturn forced him to close his robotics business, he thought of the effect teachers had on his life and decided to pay it forward. Burick now works as a technology instructor at a school for students with autism, where he recently led a project building a full-scale replica of ENIAC, an historic computer celebrating its 80th anniversary this year.
Across several industries, the United States has been moving toward limiting the use of sensitive technology made in China. Now, legislation has been introduced to extend the trend to ground robots, including humanoids, dogs, and crawlers. This could benefit some U.S.-based robotics firms—but many of these companies still rely on Chinese-made components. “The U.S. robotics industry is in a pickle,” writes Spectrum tech policy editor Lucas Laursen.