This is what I want my kids to learn
Brian Jenney is the owner of Parsity, a program that helps engineers through hands-on training.
This article is crossposted from IEEE Spectrum’s careers newsletter. Sign up now to get insider tips, expert advice, and practical strategies, written in partnership with tech career development company Parsity and delivered to your inbox for free!
If you have kids, they’re probably back in school right now after the summer break. Mine are too.
My kids range from 9 to 20 years old, and lately I’ve been thinking a lot about what their future careers are going to look like.
Some schools are embracing AI in the classroom. Others are banning it completely. I’m not sure either side has figured out the right answer yet—I’m not sure any of us have.
What I do know is that AI is already changing how engineers, and nearly every other knowledge worker, does their job. So I’ve been thinking: What skills do I actually want my kids to develop for an AI-augmented workforce?
The more I use AI, the more convinced I am that it’s a multiplier, not a substitute.
Give a great researcher AI tools and they can accelerate their research. Give an experienced software engineer the same tools and they can build at an incredible rate. But put those tools in the hands of someone without foundational knowledge and you often get something else you’re used to seeing way too much of: slop.
We’ve all seen the vibe-coded applications that barely work. Our inboxes are filled with emails that sound suspiciously identical. Teachers are reading papers that sound like they were all written by the same person. That “person” has the last name GPT.
When everyone has access to the same tools, having an actual voice becomes a differentiator.
Ironically, strong writing skills might be MORE important because of AI, not less. Text is still the primary way we communicate with these models, so being able to clearly articulate what you want improves what you get back.
But more importantly, writing teaches you to develop ideas of your own.
AI can help you express your opinion. It shouldn’t manufacture one for you.
Like written communication, speaking skills are now at a premium—but for a different reason.
We live in a strange moment. We’re more digitally connected than ever, while often feeling increasingly isolated from one another. At the same time, we’re seeing renewed interest in conferences, meetups, communities, and in-person experiences.
When human interaction feels scarce, communication becomes more valuable.
So learn how to explain an idea in front of a room. Learn how to disagree without being disagreeable. Learn how to tell a story. Learn how to listen. Learn how to persuade someone.
There’s a timeless book, originally published 90 years ago, that teaches these interpersonal skills, and it’s probably more valuable for engineers than another white paper on how neural networks work: How to Win Friends and Influence People.
An AI can generate a presentation for you, but it can’t convincingly deliver it to a skeptical audience. That takes emotional intelligence.
This might be the hardest one.
We have engineered boredom almost completely out of our lives. There’s always a podcast to listen to, a notification to check, a video to watch, a feed to scroll, or now an AI to talk to.
Go for a walk without headphones. Eat without looking at a phone. Sit in the car without immediately reaching for something to fill the silence, and let your mind wander.
Because boredom isn’t wasted time. It’s a breeding ground for original ideas.
The danger I worry about isn’t that AI becomes too intelligent, but that we become too willing to outsource the uncomfortable parts of thinking.
The students going back to school today will enter a workforce filled with technology that I couldn’t have imagined when I was their age. I have no idea what the dominant AI model will be by then or even what interacting with a computer will look like.
That’s exactly why I don’t want to optimize their education around today’s tools. I want them to learn the skills that will outlive the tools.
Write clearly. Speak confidently. Think independently.
And every once in a while, embrace boredom.
Software engineers have entered a new era of code review. The strategies they’re now testing will determine whether AI can actually provide code that’s faster and more reliable when you factor in the review process. If it can, what does that mean for the entry-level engineers who are still learning to code on their own?
In response to a barrage of actions by the U.S. federal government to limit legal immigration, tech companies are adapting their search for top talent. IEEE Spectrum looked into the responses to proposed changes, like higher fees for H-1B visa applications.
As AI changes the job market and day-to-day work of engineers, young professionals are often told they need to be adaptable. But what does adaptability actually look like in practice? The skill has different definitions depending on who you ask, but with the right mindset and support from leadership, adaptability can help keep you afloat.
Brian Jenney is the owner of Parsity, an online education platform that helps people break into AI and modern software roles through project-based learning and one-on-one mentorship with senior developers. Parsity helps career changers transition into software by focusing on practical skills, real-world systems, and the kind of experience companies actually look for.
Outside Parsity, Brian works a senior software engineer in the SF Bay Area.
Brian is also a father of three, and when he’s not working with students or building programs, you might catch him running around Lake Merritt in Oakland, California.
Source: IEEE Spectrum
