The Real Problem with New Grad Software Engineering in 2026

If you are at all acquainted with the current state of new-grad tech employment, and even if you are not, you likely know that there is currently some major upheaval occurring within the industry. Not just for new grads either, mind you. This recent job market has been undoubtedly brutal, regardless of what the LinkedIn warriors have to say in their posts. Just take a look at employment statistics from the most recent U.S Census data; after anthropology at a rate of 7.9% unemployment, computer engineering is second at 7.8%, with computer science sitting up there at a staggering 7% (Nietzel, 1). There are numerous stories floating around online consist of students of all backgrounds (top universities or otherwise) being unable to find employment in the industry. Considering the absolute golden age of SWE that took place from just a half-decade prior to a few years ago, this is an unseasonably bad conversion rate. Now, I hear many reasons to blame for this market adjustment: H1B outsourcing, overseas outsourcing, generative AI… etc. These are the demons that are often touted as the killers of entry-level/new-grad SWE work, but people are finding work in industry. So what actually determines someone’s employability? Are the metrics for defining this at all reasonable for determining technical ability?

Now, I have experienced this mass market correction firsthand, and everything written here (and in subsequent posts) is all from my perspective and opinion as someone who wants to work towards solving meaningful problems in this field. I would say that my experience at the hands of the current state of employment is closer to course correction rather than some doomed fate. To be fully transparent, I did not receive a degree in CS, but have experience within development and it is my primary passion. Plus, I’m right there with all of them in dealing with the current market.

I think, for the most part, tech hiring has become mostly a non-deterministic thing, not that it ever was, but now more than ever has it truly hinged on circumstance. More importantly, I think this has been a field within the public eye as powered by some forefront of meritocracy, as well as valuing pedigree. This illusion has been prominently shattered. Beyond that, the system itself, the pipeline touted to young folk as “go to college(secured employment) -> get a job -> achieve stability and success” no longer promises the same operational fortune as it did decades prior.

The bar has also raised. Generative AI has forcibly induced a narrowing of the technical gap. Intelligence has become incredibly cheap (for now), and code has become exponentially easier & cheaper to produce. It has also made it very difficult to determine who is actually capable. I have met with numerous people in the industry, many friends and acquaintances. One of them recently told me he was only getting his masters degree in CS for the “piece of paper” and questioned if it was worth doing anything if AI could do it for him — unemployed. Another friend fed the entirety of his OS class to ChatGPT and understands none of it — return offer at a F500 fintech firm. Another buddy of mine confided that his firm recently hired some absolutely stellar juniors, and he believed there was not a chance he could pass an interview today — mid-level at a F200. Luck, circumstance, and timing are more prevalent than ever, but companies also want undeniable proof of work, irrespective of how much the hire actually understands.

There are undoubtedly still some meritocratic aspects to be found, as can be seen all over on Twitter whenever some ‘cracked’ young engineer ships something exceptional and posts about it. Now, whether or not these projects are vibe-coded LARP slop is on a case-by-case basis, but the operative takeaway is the posting. As a field, CS has somewhat concerned itself around proficiency and optimization rather than marketing, only to find out now that this has become the new fulcrum for success. Development is also, I think, a “prideful” field. The wizards of CS that we admire and respect may very well be unemployable as new-grads in this market. They indubitably possess deep understanding, but that is a little less important nowadays. Regardless of the quality of LLM-written code, or how much artistry is stripped from it; this is irrelevant to consumers, so the moat you now have to cross is signaling.

The industry has shifted more towards signaling and valuing agency + efficiency over hard technical skill & deep understanding. That is not to say deep understanding isn’t valuable; matter of fact, to me, it may very well be the most important thing of all. Yet, what we determine to be valuable does not have to align with what the industry finds valuable. There is no doubt a sea of new-grads that frankly don’t understand as much as they should, and an equally large cohort of the opposite. Deep understanding is important, building fundamentals is vital, but these should not come at the cost of your agency.

Development has an incredibly low barrier to entry for actually building things(for the most part), and this grants devs a sort of freedom; but this tenuous also means that aforementioned signalling is incredibly important, as well as choosing which problems to solve. SWE is all about solving problems, and while understanding things deeply will absolutely make you far better at solving them, the knowledge is useless with no problems to solve. If you do happen to solve problems, and nobody knows about it, then it is similarly useless. Shipping something interesting but rough around the edges will always beat polishing something in obscurity.

So the real problem is, then, a combination of the non-deterministic nature of hiring combined with lacking the traits of the ‘Agentic Era’ developer: agency, signaling, passion. Talent notwithstanding, the only actions you can really take is to ship with imperfections, accept inevitable humility, and understand technical subjects deeply, but not sacrificing your agency to do so: do not halt progress on building something impressive/useful to know the minutiae of your tools. Nobody cares about how you used some obscure algorithm during implementation. Not stranger, clients, users, and certainly not hiring managers. Most of all: solve cool problems. Someone out there will undoubtedly find them of interest.