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I was at a tech conference recently – one built by (and for) networking professionals – chatting with another attendee about the usual mix of news, tech challenges, and hobbies when the conversation took a sudden and sobering turn:
“I guess I have a lot more time for side quests these days. I got laid off a couple of months back and can’t seem to land even a solid conversation, let alone a job offer. I thought it would be easier than this.”
When the interview comes to the “Do you have any questions for me?” part, your best use of time is to try to uncover things that would cause you to absolutely say no (or yes) to the job.
“What gets you most excited about the company’s future?” is… nice, but no matter what answer they give, it’s not likely to change your mind about whether to accept the job or not.
As part of my involvement at LeadDev NYC, I had the opportunity a short video message that would be part of a montage played for folks between the live talks. I decided to speak about the way engineers are enabling the future of products (you can watch it here).
It seems to me that questions like “how can engineers affect the future of (whatever)” sometimes come from a place of anxiety. And these days, there’s no greater source of that anxiety than the advances — and the impacts we imagine coming from those advances — in large language models (LLM), more broadly billed as artificial intelligence (AI).
This post continues my exploration of concepts and techniques related to both the way so-called “Jewish times” (zmanim) are calculated; as well as the techniques needed to use the PHP Zmanim library – a library of functions that let you easily calculate Jewish times. Once again I owe a huge debt of gratitude to several folks – including Eliyahu Hershfeld, creator of the Kosher Java library, Zachary Weixelbaum (owner of the PHP Zmanim library, a port of Kosher Java), Elyahu Jacobi (who built RoyZmanim.com with those tools and patiently explained so many concepts to me), and Maor Neim, who offered explanations that turned theory into practice.
In my last post, I explored both the foundational concepts of Jewish time calculations (zmanim) and also the initial steps needed to install and use PHP Zmanim. We got as far as calculating sunrise with that library.
Recently someone asked me if one of the jobs I had shared (something I do every week) was open to remote folks. While I work hard to ensure my weekly list of jobs only includes remote-friendly opportunities, this particular role was listed as being in-office.
However, I offered the following advice based on my personal experience and what I’ve seen from other folks over the years: Even when a job is listed as being “in office,” it’s still possible to get the company to consider a remote employee.
In the course of talking about job hunting with friends, colleagues, and randos on Slack and elsewhere, I end up talking about resumes. A lot. There is, (in my (not so) humble) opinion, a sizeable misunderstanding about what resumes are, what they do, how they should look, the effort one should (or shouldn’t) put into creating them, and more.
Given the current period of churn in the tech industry and the resulting uptick in the frequency with which I’m having these types of conversations, I decided to commit to what’s become a standard part of my “so you’re looking for a new job?” shpiel to paper (or at least electrons).
In last week’s post, as I was talking about job descriptions, I asked a question I feel is key to a successful job search:
“Do you like the company because of it’s culture, creation, community, calling, or some other Aspect? Are you intrigued enough to want to find out more? “
As I worked through the homework challenge round at one of the companies I interviewed at (a company that was very WordPress centric), I found myself struggling with literally every step – trying to find shreds of information on how to do the most basic things. Things like building a simple local test environment.
I found information telling me I could use:
As regular readers know, I recently changed companies. After all the interviews, the next part of that process was the offer negotiation phase. To be incredibly transparent, I hate that part of the interview process like almost nothing else in my life. It’s gut-churning and mind-numbing and terror-inducing all at the same time. I always feel like I’m doing it wrong, and at the end of the process, I’m certain I’ve made horrible mistakes that will haunt me for the rest of my career.
In the 35+ years I’ve worked in tech, I’ve changed jobs several times, each time interviewing with several companies before making a career move. After some back-of-the-napkin math, I realized I’ve received dozens of offers over the course of my career.
(And sometimes it’s not)
My post about my 6-month job search generated some attention and conversation. The comments helped me clarify some of the more specific lessons I’ve learned recently or that I knew but were reinforced by the experience. After taking time to organize them into a somewhat coherent structure, I’m ready to share. Here are the first lessons on the list.
My post about my 6-month job search generated some attention and conversation. The comments helped me clarify some of the more specific lessons I’ve learned recently or that I knew but were reinforced by the experience. After taking time to organize them into a somewhat coherent structure, I’m ready to share. Here are the first lessons on the list.
As always, if you have opinions, corrections, or experiences you want to share, please do so in the comments below.
Now that I’m free to share the news that I’ve landed at Kentik — a visionary company filled by an amazing group of folks who believe that the value of their team goes far beyond what they might offer to the business — I wanted to take a minute to reflect on my job search, comment on the state of the job market, and share some lessons I’ve picked up along the way.
Let me be clear — I’m under no illusion that the world has breathlessly awaited the thoughts of a middle-aged white dude and will now, graced with my heretofore-undiscovered wisdom, be a truly better place. People with far more knowledge, experience, and expertise have written and spoken on this topic, with data and examples that are far more eloquent and compelling than anything I could hope to share.
At last comes their answer through cold and through frost,
That not all who wonder or wander are lost,
No matter the sorrow, no matter the cost,
That not all that wonder or wander are lost.
. – Poppy Proudfellow, “The Rings of Power”
We’ve arrived at the end of the series. If you have missed parts of the journey so far, you can find part one here; and here you’ll find part two; and then you’ll find part three waiting for you here. And now, let us see what final wisdom Amazon’s “The Rings of Power” has in store for us:
I’ve made no secret of the fact that, at 55 and after 35 years in I.T., I’m learning to code “for real." And some of this journey is far from comfortable. Some of it is downright frustrating and difficult in ways I didn’t expect and feel (albeit without justification) it shouldn’t be.
It took a drive in the car with my son to put it into perspective.
Of drink I have little and food I have less,
My strength tells me no but the path demands yes,
My legs are so short and the way is so long,
I’ve no rest nor comfort, no comfort but song.
– Poppy Proudfellow, “The Rings of Power”
Call to me, call to me, lands far away,
For I must now wander this wandering day.
Away I must wander this wandering day.
– Poppy Proudfellow, “The Rings of Power”
It’s no secret that I derive a special kind of joy from finding lessons for my life and work in tech within pop culture — and specifically “geeky” movies, tv series, books, and more. With Amazon’s “The Rings of Power” season one reaching its conclusion, there was zero chance I wasn’t going to dig into it with zeal to see what this Tolkien (or at least Tolkien-inspired) work might hold.
Over the last few weeks, there’s been a lot of chatter about ChatGPT, a writing tool built in OpenAI. So much noise, in fact, that everyone from CNN, the NYT, Forbes, the Atlantic, the Washington Post, the Guardian, BBC, TechCrunch, CNet, and approximately a half billion techbruhs on YouTube had to sound off on it. All in the last two weeks.
The opinions range from incredulous to breathless to skeptical — albeit carefully so. Nobody really knows what the next few weeks will bring, and therefore nobody is willing to declare ChatGPT entirely one thing or another.
While a lot of my inspiration for blog posts come from talking with New Relic users, it's hard to share them as examples because their so specific and often confidential. So I find myself struggling more to find a generic "for instance" that's easy to understand and accessible to all everyone.
Which should explain why I use my home environment as the sample use case so often. Even if you don't have exactly the same gear or setup I do, it's likely you have something analogous. On top of that, if you don't have the specific element I'm discussing, many times I believe it's something you ought to consider.