A Look at the Computer Science Degree in 2026
In 2018, a student published an article in this paper titled “YC’s Computer Science Major is on the Rise.” His piece proved prescient for the next four years, as enrollment in Intro to Computer Science continued to increase, indicating a growing interest in the field. Enrollment in this introductory course in Yeshiva College reached an all-time high in the fall semester of 2022, with 73 students. On the women’s campus, 26 students enrolled in the parallel course that semester, a number relatively high compared to previous years.
This fall, there are 16 students enrolled in Intro to Computer Science on Wilf. On Beren, there are 4.
This downward enrollment trajectory is consistent with trends across the country. The number of computer science majors rose nationally until 2024, when the numbers began to drop. From 2025 to 2026 there was an estimated 12.5% decrease in computer science majors in the United States. Student interest is evidently decreasing, but is it an accurate indicator of a real shift in the job market?
If one were to assess the state of the job market based on media reports from the past few years, the situation may seem dire. One particularly ominous piece published in August 2025 argued that AI tools have practically obviated entry-level jobs: “Goodbye, $165,000 Tech Jobs. Student Coders Seek Work at Chipotle.” While current reports suggest that the unemployment predictions were largely overhyped, students may fear that entering the computer science industry is no longer a stable career path. Alternatively, students may be concerned that the computer science degree will no longer prepare them for a job whose skillset is changing.
I spoke to Professor Judah Diament and Professor Alan Broder, the chairs of YC’s and Stern’s computer science departments, to address these concerns.
Diament emphasized that the pattern of a new tool being created that increases coding productivity, followed by a global reaction that software engineers will no longer be needed, has been repeating for decades. With each added layer of abstraction, as coding came to resemble plain language more and more, people believed that software engineers could be replaced by people with no engineering knowledge. But, as Diament explained, “productivity has never made software engineers irrelevant.” He noted that, in fact, innovations invariably gave way to new opportunities and made software engineers more valuable to companies.
Diament shared that in a conversation with a technical leader at a big tech company, this engineer said that he instructed his team to develop all of their code by prompting AI: “Hands off the keyboard.” This was around December 2025, when AI models were already very good at generating code. Later, in May, this engineer reported that his team saw a large increase in production issues. The AI models were producing too much code too quickly, and it was impossible for human engineers to keep up and properly debug it.
It is clear to Diament that a human still needs to be the creative agent to build systems that last. This sentiment was shared by Broder, who said that “AI can indeed crank out tons of code, but an educated human must still understand the problem, imagine what should be built, ensure that it scales robustly, make sure that it will fit into larger systems and then judge whether the result is viable.” Of course, the number of engineers needed to do this type of work is likely much fewer than was once needed. Yet Diament emphasized that, consistent with trends seen with every coding innovation, many AI-related positions are now being created; companies continue to reach out to him to recruit for these newly-available jobs.
Regarding the job market, Broder shared with The Commentator that recent Stern graduates have successfully found jobs or graduate programs “at roughly the same rate as in prior years.” In YC, 23/25 of the recent graduates came out with a job offer or an acceptance to a graduate program; in Diament’s words, “Baruch Hashem, the guys are still doing well.” In response to the increased layoffs in many tech companies, Diament posited that these may not be a fair way of assessing the necessity of engineers. He pointed out that tech companies may be incentivized to increase layoffs as a false signal of increased productivity, masking the fact that their huge investments in AI data centers have not yet paid off.
To me, the question of how to prioritize computer science skill-building in a world where AI can be an easy crutch is of particular interest. From my assessment in talking to a handful of people in corporate jobs, new hires seem to be struggling to reach a level of competence that would have been formerly expected. What is theorized in a recent Wall Street Journal article is that AI’s elimination of “busy work” is “depriving [entry-level workers] of the way [they] have long gleaned the expertise to become valuable players later on — by getting in the reps.”
On both of YU’s campuses, exams in introductory computer science courses are paper-only; using AI as a crutch is not an option. Additionally, both Diament and Broder made changes in their curricula to replicate ways that AI has been implemented in the computer science industry. In YC’s Advanced Distributed Systems course, students now use AI to complete their final projects rather than leaving them in the draft stage, a requirement which would have previously been too ambitious for a one-semester course. In Stern’s Data Structures course, students learn to use AI to assist in building unit tests, small functions which test that specific qualities of code perform as expected.
Will this be enough to set students up for success, or is there a deeper gap between the CS degree and the reality of working in a tech company? Sarah Schafer (SCW ‘28), a current computer science major, voiced her concerns about a disconnect between the coding skills taught in class and the AI-assisted coding being implemented in the workforce.
“From what I gather, experienced engineers can use AI to greatly accelerate their pace and maximize productivity, but bad engineers just end up producing more bad code,” Schafer shared with The Commentator. “What worries me about the gap in my education is that I won’t be able to develop into a good engineer and create that foundation for which AI becomes a useful skill.”
Of course, whether or not students are best set up for success five to ten years down the line can only be speculated, and — as with success in any field — much will depend on the dedicated work of the student and not just the curriculum design. In the words of Akiva Nachum Rosenberg (YC ‘28), “only G-d knows what the future holds, but any computer skills should be valuable in some form.” Perhaps now more than ever students should choose a major that forces them to think in an expansive and productive way rather than trying to predict a rapidly changing industry.
For some students, computer science will continue to be a major they choose for the mode of thinking it develops, while those who found computer science desirable mainly for the job prospects it offers are likely to opt for other options. Yakov Halstuch (YC ‘28) speaks highly of the algorithmic-thinking skills he is gaining from his computer science education. “I never really considered changing my major,” Halstuch shared with The Commentator. “I think CS is the strongest department in YC.”
Photo Caption: A CS student hard at work
Photo Credit: Elza Koslowe
