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Software Engineering Job Market Dynamics
Comparison of industry demand vs. academic focus shift.
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How Do Software Engineering Students Use Generative AI in Real-World ...
(30.04.2026) Abstract. Real-world Capstone Projects (RWCPs) are a key component of software engineering education, enabling students to develop software for external clients under authentic conditions. Their high ecological validity, combined with substantial variation in domains, technologies, and stakeholders, typically requires flexible and minimally prescriptive teaching approaches. The rapid integration of generative AI (GenAI) into professional software development adds new challenges: students are expected to use AI tools that are common in practice, yet unguided use may affect learning, collaboration, and consistency in ways that are not yet well understood. To establish an empirical baseline for responsible GenAI integration, we conducted a large-scale study of self-determined GenAI use in an undergraduate RWCP course. The module involved 178 students working in 18 teams across 15 client projects over four months, with GenAI use explicitly permitted. We collected mixed-method survey data from 150 students on attitudes, usage prevalence, workflows, use cases, and perceived benefits and risks, and surveyed client stakeholders regarding expectations and concerns. Our findings provide (1) a characterization of GenAI practices across the software engineering lifecycle, including a distinction between emerging workflows; (2) student-recommended use cases and responsible-use directives emphasizing verification and maintaining independent understanding; (3) client perspectives highlighting strong support for GenAI use but clear expectations regarding understanding, quality, and data protection; and (4) implications for future course iterations, including the need for explicit responsible-use guidelines, targeted AI literacy resources, and team-level governance roles. This study offers a status quo baseline for evidence-based pedagogical interventions in the era of GenAI. Software engineering education, Capstone projects, Generative AI, AI-assisted software development, Empirical study, Student assessment ††copyright: acmlicensed††journalyear: 2026††doi: XXXXXXX.XXXXXXX††conference: The 30th International Conference on Evaluation and Assessment in Software Engineering; 9–12 June, 2026; Glasgow, Scotland, United Kingdom††isbn: 978-1-4503-XXXX-X/2018/06††ccs: General and reference Empirical studies††ccs: Human-centered computing Empirical studies in collaborative and social computing††ccs: Social and professional topics Student assessment††ccs: Computing ...
University of Washington CS professor explains what's changing for ...
By Brent D. Griffiths You're currently following this author! Want to unfollow? Unsubscribe via the link in your email. University of Washington computer science professor Dan Grossman said AI makes it so you have to worry less about "the pesky details" of code. Matt Hagen/University of Washington 2026-04-29T09:33:01.307Z Before AI, getting all the tiny details of code right mattered a lot more. University of Washington computer science professor Dan Grossman said it's just one of the things that's changing. Ultimately, Grossman is bullish on the future of CS and the need for computer engineers. University of Washington computer science professor Dan Grossman said it's time to evolve the push to "Learn to Code." "I think that part of what we were teaching a few years ago, when we had people learn to code, was a lot of focus on getting all the tiny details right," Grossman, who is also vice director of the Paul G. Allen School of Computer Science and Engineering, told Business Insider. "Where did you put a semicolon versus a comma? What exactly is the word for something? Things like that."Grossman said AI coding tools have changed the conversations."We're going to see and really already see AI take care of a lot of that for the non-professional software engineers and in many ways for the professional software engineers," he said.That doesn't mean that CS degrees aren't valuable, a point that some in AI, including OpenAI Chairman Bret Taylor, have emphasized. "The idea to precisely specify what you want an algorithm to be, what you want code to do, to have this sort of creative but precise design for an app or something that just makes you more productive or creative in your life," Grossman said. "A lot of the same skills are going to be needed."Grossman said the Allen School, named after the famed Microsoft cofounder who once snuck into the university's computer science lab as a high school student, is still tweaking how it teaches students in a world "where the pesky details of code" matter less.At the same time, Grossman said the conversation around CS has clearly changed."There was a time a few years ago where computer science was the popular major," Grossman said.AI-related fears dominate the headlines and overshadow the job market, though the extent of the cooldown is debated. According to a New York Fed analysis of 2024 graduates, as of February, computer science and computer engineering graduates have among the highest unemployment rates at ...
Demystifying AI for engineering | UW College of Engineering
AI tools are reshaping nearly every field — including engineering. To meet the growing demand for engineers who know how to integrate these tools into their practice, the College of Engineering has launched two new professional programs — a graduate certificate and a master's degree — in AI and machine learning (ML) for engineering.
Key ideas from 'The Risks and Realities of AI Chatbots' event co-hosted ...
During " The Risks and Realities of AI Chatbots," an April 7 event at the Seattle Central Library co-organized by the University of Washington's Center for an Informed Public, KUOW Public Radio AI and economy reporter Monica Nickelsburg spoke with two of the nation's foremost technology journalists writing about artificial intelligence, social media and other emerging technologies.
