What It Takes to Be an Adaptable Engineer
IEEE Spectrum Gwendolyn Rak
AI tools are changing how engineers work and get hired. That’s why “be adaptable” is the new career advice, even if nobody agrees what it means.
Based on reporting by IEEE Spectrum, Gwendolyn Rak — read the original for the full story.
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The AI boom has done more than add new software to the stack. It has changed how engineers are expected to work, raised the bar for what teams are supposed to ship in a day, and made hiring tougher at the same time. That leaves students with an awkward problem: the old advice about which language to learn first feels a lot less useful than it used to.
Samantha Brunhaver, an associate professor of engineering at Arizona State University in Tempe, says adaptability is real but rarely taught in a useful way. Her definition is simple enough: notice when something has changed, then respond effectively. The catch is that employers don’t all mean the same thing when they use the word. In software, it can mean dealing with a turnover in tools. In aerospace or biomedical work, it can mean keeping up with shifting procedures and regulations.
The uncertainty is not just local to one company or one field. A June 2026 PwC report said technology, media, and telecom jobs are seeing the fastest pace of skill turnover. The World Economic Forum’s 2025 Future of Jobs Report said employers across sectors expect 39 percent of workers’ core skills to change by 2030. That is a lot of motion for a job market that already likes to ask for confidence, speed, and perfect résumés.
Brunhaver’s answer starts before people even enter the workforce. She points to internships, team projects, community service, and leadership roles as ways to practice adapting to different demands. Reflection matters too, because people adapt better when they believe they can do something about the problem instead of just absorbing it. Her three-step version is blunt: see the need to adapt, weigh the options, then act.
For people already working, the advice gets even more practical. Jenna Butler, a research scientist at Microsoft who studies developer well-being and productivity, says the current AI shift looks like other big transitions: a messy “chaos period” before a new normal settles in. She says software engineers are already seeing more code review, and that future work may lean more on prompting models and managing agents than typing code line by line. Andy Hunt, coauthor of The Pragmatic Programmer, makes a similar point from a different angle: the real job is problem solving and communication, not worshipping a particular tool.
The uncomfortable part is that employers often want adaptability and speed at the same time. Butler says companies need to make room for learning, even if that means an hour a week with no expectation of immediate output. Otherwise people just cling to what they know and burn out. The technology may be changing fast, but the bigger question is whether organizations are willing to let engineers change with it.
My take — AI-written commentary, not fact-checked reporting
This is where a lot of companies get very modern and very stupid: they ask for adaptability, then schedule every minute of it away. The bigger truth is that AI is not only testing engineers; it is testing managers who still think learning happens in the cracks between deliverables. If there is no time to learn, there is no adaptability, just theatre.
Read more about this at: IEEE Spectrum