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Before we get into this week’s article, I’d love to hear from you. If you have a question about your career or an upcoming decision that you want advice about, you can ask it here. I’ll be reading through your responses and picking questions to answer on a regular basis. Now back to our regularly scheduled program.
The Safest Career Move Is Often the Riskiest
Software engineers have some of the shortest tenures of any white-collar profession. The average software engineer stays at a company for roughly two years, about half as long as workers in most other knowledge professions. The layoffs of the past few years have certainly highlighted this instability, but it was already there.
This isn’t an essay about a broken job market though. Rather, it’s about how to turn that instability to your advantage, which is something I’ve spent the last decade doing on purpose.
Playing It Safe Was the Riskiest Option
I switched careers into software in my 30s. I had a stable job at a community college, complete with a union and a pension. It was about as secure as a career gets, and I learned to program on the side.
Then I did something nearly everyone in my life considered reckless: I quit, leaving the secure job to become a junior developer at 31. My own mother was skeptical. I took the riskier job anyway, for two reasons: It was the work I actually wanted, and I could see potential.
My first development job was at a grocery retailer. Good people and a company I liked. But I kept meeting engineers earning twice my salary for the same work. In the San Francisco Bay Area, surrounded by some of the best engineering talent in the world, I realized my skills were stagnating.
So I left for a small startup. I learned more in nine months than I had in the previous two years, and my salary doubled.
Over the years I’ve come to treat career risk as something to manage deliberately. It falls into two categories.
Take Risks With Your Job
The first type of risk involves the job itself: Bet on yourself by striving for better roles and opportunities.
Job-hopping for money alone isn’t wrong, especially early on. But the returns shrink after the first few hops, and the stress of chasing a slightly bigger paycheck every year will wear you down.
There’s another career risk with rewards that compound: Seeking positions to work alongside the strongest engineers.
You might struggle to keep up. You might even get laid off. But the skills you absorb working alongside people better than you are the ones that create durable stability. You build marketable expertise, you see how different organizations actually operate, and every project becomes another tool you carry to the next opportunity. Working next to stronger engineers is a proven way to increase your own expertise.
If that feels too big, try volunteering for a project you have no idea how to do. The risk is that you fail in front of people. The reward is a new skill and a resume line that opens the next door.
Compare that with the “safe” path.
You stay at one company, assuming loyalty will be rewarded. It usually isn’t. And when you finally leave, by choice or not, you may find the skills you built are worth little on the open market. You might be the in-house expert in an aging tech stack while employers are hiring for more cutting edge technologies. Suddenly you’re competing against people with half your experience.
You could be taking on a risk you didn’t notice.
Risk Your Time
The second form is risking your time, which means betting on trends.
Some trends are non-negotiable. If you’re a software engineer, then cloud services, ReactJS, and AI are mainstream enough that ignoring them actively damages your career. A backend engineer who refuses to learn cloud architecture is volunteering for obsolescence.
The real gamble is with the smaller trends: the niche tools you stumble onto and find quietly interesting, with no idea whether they’ll matter.
About two and a half years ago, I learned about retrieval-augmented generation (RAG). Almost no one in my circle was talking about vector databases, a central piece of RAG. Today RAG is close to mainstream, and for once, I had the early-adopter advantage.
Most of these bets don’t pay off. But when one turns into a major trend, you’re already on the ground floor. Right now I’m making the same bet on voice AI. It isn’t mainstream. It may never be. But if it becomes the next thing, I’m already there, building a foundation.
Short-Term Risk, Long-Term Stability
Counter-intuitively, job-hopping and betting on trends gave me the thing I was after the whole time: stability. I’ve rarely struggled to find work, because every risky move stacked skills the market actually wanted.
If you feel stable and comfortable right now, enjoy it. But ask yourself whether you’re still learning. Because if you’re not, the comfortable choice and the dangerous one may have converged.
The goal isn’t to avoid the open market forever. It’s to make sure that when you land on it, you’re not at its mercy.
By Brian Jenney
P.S. Don’t forget to submit questions about your career or an upcoming decision that you want advice about here!
—Brian
What It Means to Be a Mathematician When AI Does the Math
Until recently, human mathematicians have been central to creating new proofs, even when the work relies on massive computational resources. AI is now challenging that status quo. Writer Benjamin Skuse surveys the ongoing debate in the field about the role of AI, and the existential questions mathematicians have about their own careers. If AI mathematicians surpass human knowledge, could these researchers become “priests to oracles”?
Chip R&D Is Accelerating to Keep Pace with AI
A new partnership between UCLA and five major semiconductor companies is the latest program aiming to bridge the gap between industry and academia. The US $125 million university-industry hub is meant to strengthen collaboration and speed up the R&D process to help meet AI’s fast-paced hardware demands.
Why Mentorship Is the Most Underrated Leadership Skill
True mentorship is far more than friendly advice. This key leadership skill requires advocacy and honest feedback via lasting relationships, and it can strongly benefit both mentor and mentee. Parul Jain, a product management leader at Deloitte, shares what she learned from serving as a mentor—something she didn’t have for much of her own early career.
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.

Facts Only

* Average software engineer tenure is roughly two years.
* The author switched careers into software in their 30s after having a stable job at a community college.
* The author left a secure job to become a junior developer at age 31.
* The author moved from a grocery retailer to a small startup, doubling salary over nine months.
* One risk category is taking risks with the job, such as seeking roles alongside stronger engineers.
* Another category is risking time by betting on trends like cloud services, ReactJS, and AI.
* Retrieval-augmented generation (RAG) was a niche interest before becoming mainstream.
* The author is currently making a bet on voice AI.
* Job-hopping for money alone shrinks returns after initial hops.
* A partnership between UCLA and five semiconductor companies aims to accelerate R&D for AI hardware demands.

Executive Summary

Software engineers often have shorter tenures in white-collar professions, with the average tenure being about two years compared to other knowledge professions. The author discusses managing career risk through two categories: taking risks with a job and risking time by betting on trends. Taking risks with a job involves pursuing better roles or working alongside stronger engineers, which builds expertise but carries the risk of insecurity. Risking time involves betting on non-negotiable trends like cloud services and AI, as well as smaller, emerging trends such as RAG and voice AI. The author posits that these risky moves can lead to greater stability by building marketable skills, suggesting that the goal is to ensure stability when entering the open market by stacking sought-after skills rather than relying on job loyalty.

Full Take

The narrative presents a tension between conventional career security and dynamic market adaptation. The argument suggests that stability is not found in monolithic loyalty but in the deliberate accumulation of transferable, market-relevant expertise achieved through calculated risk-taking. This challenges the traditional assumption that remaining in a single entity guarantees future value, reframing job mobility as an active strategy for self-optimization rather than mere escape. Furthermore, the analysis on trends suggests a pattern where early adoption of nascent technologies yields significant advantage, even if those bets do not pay off immediately. The underlying implication is that cognitive sovereignty requires viewing career progression not as a linear climb toward safety, but as a portfolio management exercise balancing immediate security against future adaptability. The focus shifts from avoiding the market to ensuring one controls their position within it by continuously updating the assets they bring to the table.

Sentinel — Human

Confidence

The text reads as an opinion/advice piece built around personal career strategy, featuring a distinct, reflective human narrative interspersed with analysis, making it highly likely to be human-authored journalism or commentary.

When Career Risks Are Worth Taking — Arc Codex