The Evolving Role of a Software Engineer with Forrest Brazeal

Episode Summary

Forrest Brazeal, Head of Developer Media at Google Cloud, joins Corey on Screaming in the Cloud to discuss how AI, current job markets, and more are impacting software engineers. Forrest and Corey explore whether AI helps or hurts developers, and what impact it has on the role of a junior developer and the rest of the development team. Forrest also shares his viewpoints on how he feels AI affects people in creative roles. Corey and Forrest discuss the pitfalls of a long career as a software developer, and how people can break into a career in cloud as well as the necessary pivots you may need to make along the way. Forrest then describes why he feels workers are currently staying put where they work, and how he predicts a major shift will happen when the markets shift.

Episode Show Notes & Transcript

About Forrest

Forrest is a cloud educator, cartoonist, author, and Pwnie Award-winning songwriter. He currently leads the content marketing team at Google Cloud. You can buy his book, The Read Aloud Cloud, from Wiley Publishing or attend his talks at public and private events around the world.

Links Referenced:


Announcer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.

Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn and I am thrilled to have a returning guest on, who has been some would almost say suspiciously quiet over the past year or so. Forrest Brazeal is the Head of Developer Media over at Google Cloud, and everyone sort of sits there and cocks their head, like, “What does that mean?” And then he says, “Oh, I’m the cloud bard.” And everyone’s, “Oh, right. Get it: the song guy.” Forrest, welcome back.

Forrest: Thanks, Corey. As always, it’s great to be here.

Corey: So, what have you been up to over the past, oh let’s call it, I don’t know, a year, since I think, is probably the last time you’re on the show.

Forrest: Well, gosh, I mean, for one thing, it seems like I can’t call myself the cloud bard anymore because Google rolled out this thing called Bard and I’ve started to get some DMs from people asking for, you know, tech support on Bard. So, I need to make that a little bit clearer that I do not work on Bard. I am a lowercase bard, but I was here first, so if anything, you know, Google has deprecated me.

Corey: Honestly, this feels on some level like it’s more cloudy if we define cloudy as what, you know, Amazon does because they launched a quantum computing service about six months after they launched some unrelated nonsense that they called [QuantumDB 00:01:44], which you’d think if you’re launching quantum stuff, you’d reserve the word quantum for that. But no, they’re going to launch things that stomp all over other service names as well internally, so customers just wind up remarkably confused. So, if you find a good name, just we’re going to slap it on everything, seems to be the way of cloud.

Forrest: Yeah, naming things has proven to be harder than either quantum computing or generative AI at this point, I think.

Corey: And in fairness, I will point out that naming things is super hard; making fun of names is not. So, that is—everyone’s like, “Wow, you’re so good at making fun of names. Can you name something well?” [laugh]. Absolutely not.

Forrest: Yeah, well, one of the things you know, that I have been up to over the past year or so is just, you know, getting to learn more about what it’s like to have an impact in a very, very large organizational context, right? I mean, I’ve worked in large companies before, but Google is a different size and scale of things and it takes some time honestly, to, you know, figure out how you can do the best for the community in an environment like that. And sometimes that comes down to the level of, like, what are things called? How do we express things in a way that makes sense to everyone and takes into account people’s different communication styles and different preferences, different geographies, regions? And that’s something that I’m still learning.

But you know, hopefully, we’re getting to a point where you’re going to start hearing some things come out of Google Cloud that answer your questions and makes sense to you. That’s supposed to be part of my job, anyway.

Corey: So, I want to talk a bit about the idea of generative AI because there has been an awful lot of hype in the space, but you have never given me a bum steer. You have always been a level-headed, reasonable voice. You are not—to my understanding—a VC trying desperately to prop up an industry that you may or may not believe in, but you are financially invested into. What is your take on the last, let’s call it, year of generative AI enhancements?

Forrest: So, to be clear, while I do have a master’s degree in interactive intelligence, which is kind of AI adjacent, this is not something that I build with day-to-day professionally. But I have spent a lot of time over the last year working with the people who do that and trying to understand what is the value that gen AI can bring to the domains that I do care about and have a lot of interest in, which of course, are cloud developers and folks trying to build meaningful enterprise applications, take established workloads and make them better, and as well work with folks who are new to their careers and trying to figure out, you know, what’s the most appropriate technology for me to bet on? What’s going to help me versus what’s going to hurt me?

And I think one of the things that I have been telling people most frequently—because I talk to a lot of, like, new cloud learners, and they’re saying, “Should I just drop what I’m doing? Should I stop building the projects I’m working on and should I instead just go and get really good at generating code through something like a Bard or a ChatGPT or what have you?” And I went down a rabbit hole with this, Corey, for a long time and spent time building with these tools. And I see the value there. I don’t think there’s any question.

But what has come very, very clearly to the forefront is, the better you already are at writing code, the more help a generative AI coding assistant is going to give you, like a Bard or a ChatGPT, what have you. So, that means the way to get better at using these tools is to get better at not using these tools, right? The more time you spend learning to code without AI input, the better you’ll be at coding with AI input.

Corey: I’m not sure I entirely agree because for me, the wake-up call that I had was a singular moment using I want to say it was either Chat-Gippity—yes, that’s how it’s pronounced—or else it was Gif-Ub Copilot—yes, also how it’s pronounced—and the problem that I was having was, I wanted to query probably the worst API in the known universe—which is, of course, the AWS pricing API: it returns JSON, that kind of isn’t, it returns really weird structures where you have to correlate between a bunch of different random strings to get actual data out of it, and it was nightmarish and of course, it’s not consistent. So, I asked it to write me a Python script that would contrast the hourly cost of a Managed NAT gateway in all AWS regions and return a table sorted by the most to least expensive. And it worked.

Now, this is something that I could have done myself in probably half a day because my two programming languages of choice remain brute force and enthusiasm, but it wound up taking away so much of the iterative stuff that doesn’t work of oh, that’s not quite how you’d handle that data structure. Oh, you think it’s a dict, but no, it just looks like one. It’s a string first; now you have to convert it, or all kinds of other weird stuff like that. Like, this is not senior engineering work, but it really wound up as a massive accelerator to get the answer I was after. It was almost an interface to a bad API. Or rather, an interface to a program—to a small script that became an interface itself to a bad API.

Forrest: Well, that’s right. But think for a minute, Corey, about what’s implicit in that statement though. Think about all the things you had to know to get that value out of ChatGPT, right? You had to know, A, what you were looking for: how these prices worked, what the right price [style 00:06:52] was to look for, right, why NAT gateway is something you needed to be caring about in the first place. There’s a pretty deep stack of things—actually, it’s what we call a context window, right, that you needed to know to make this query take a half-day of work away from you.

And all that stuff that you’ve built up through years and years of being very hands-on with this technology, you put that same sentence-level task in the hands of someone who doesn’t have that background and they’re not going to have the same results. So, I think there’s still tremendous value in expanding your personal mental context window. The more of that you have, the better and faster results you’re going to get.

Corey: Oh, absolutely. I do want to steer away from this idea that there needs to be this massive level of subject matter expertise because I don’t disagree with it, but you’re right, the question I asked was highly contextual to the area of expertise that I have. But everyone tends to have something like that. If you’re a marketer for example, and you wind up with an enormous pile of entrants on a feedback form, great. Can you just dump it all in and say, can you give me a sentiment analysis on this?

I don’t know how to run a sentiment analysis myself, but I’m betting that a lot of these generative AI models do, or being able to direct me in the right area on this. The question I have is—it can even be distilled down into simple language of, “Here’s a bunch of comments. Do people love the thing or hate the thing?” There are ways to get there that apply, even if you don’t have familiarity with the computer science aspects of it, you definitely have aspect to the problem in which you are trying to solve.

Forrest: Oh, yeah, I don’t think we’re disagreeing at all. Domain expertise seems to produce great results when you apply it to something that’s tangential to your domain expertise. But you know, I was at an event a month or two ago, and I was talking to a bunch of IT executives about ChatGPT and these other services, and it was interesting. I heard two responses when we were talking about this. The first thing that was very common was I did not hear any one of these extremely, let’s say, a little bit skeptical—I don’t want to say jaded—technical leaders—like, they’ve been around a long time; they’ve seen a lot of technologies come and go—I didn’t hear a single person say, “This is something that’s not useful to me.”

Every single one of them immediately was grasping the value of having a service that can connect some of those dots, can in-between a little bit, if you will. But the second thing that all of them said was, “I can’t use this inside my company right now because I don’t have legal approval.” Right? And then that’s the second round of challenges is, what does it look like to actually take these services and make them safe and effective to use in a business context where they’re load-bearing?

Corey: Depending upon what is being done with them, I am either sympathetic or dismissive of that concern. For example, yesterday, I wound up having fun with it, and—because I saw a query, a prompt that someone had put in of, “Create a table of the US presidents ranked by years that they were in office.” And it’s like, “Okay, that’s great.” Like, I understand the value here. But if you have a magic robot voice from the future in a box that you can ask it any question and as basically a person, why not have more fun with it?

So, I put to it the question of, “Rank the US presidents by absorbency.” And it’s like, “Well, that’s not a valid way of rating presidential performance.” I said, “It is if I have a spill and I’m attempting to select the US president with which to mop up the spill.” Like, “Oh, in that case, here you go.” And it spat out a bunch of stuff.

That was fun and exciting. But one example he gave was it ranked Theodore Roosevelt very highly. Teddy Roosevelt was famous for having a mustache. That might be useful to mop up a spill. Now, I never would have come up in isolation with the idea of using a president’s mustache to mop something up explicitly, but that’s a perfect writer’s room style Yes, And approach that I could then springboard off of to continue iterating on if I’m using that as part of something larger. That is a far cry from copying and pasting whatever it is to say into an email, whacking send before realizing it makes no sense.

Forrest: Yeah, that’s right. And of course, you can play with what we call the temperatures on these models, right, to get those very creative, off-the-wall kind of answers, or to make them very, kind of, dry and factual on the other end. And Google Cloud has been doing some interesting things there with Generative AI Studio and some of the new features that have come to Vertex AI. But it’s just—it’s going to be a delicate dance, honestly, to figure out how you tune those things to work in the enterprise.

Corey: Oh, absolutely. I feel like the temperature dial should instead be instead relabeled as ‘corporate voice.’ Like, do you want a lot of it or a little of it? And of course, they have to invert it. But yeah, the idea is that, for some things, yeah, you definitely just want a just-the-facts style of approach.

Another demo that I saw, for example, that I thought showed a lack of imagination was, “Here’s a transcript of a meeting. Extract all the to-do items.” Okay. Yeah, I suppose that works, but what about, here’s a transcript of the meeting. Identify who the most unpleasant, passive-aggressive person in this meeting is to work with.

And to its credit—because of course this came from something corporate, none of the systems that I wound up running that particular query through could identify anyone because of course the transcript was very bland and dry and not actually how human beings talk, other than in imagined corporate training videos.

Forrest: Yes, well again, I think that gets us into the realm of just because you can doesn’t mean you should use it for this.

Corey: Oh, I honestly, most of what I use this stuff for—or use anything for—should be considered a cautionary tale as opposed to guidance for the future. You write parody songs a fair bit. So do I, and I’ve had an attempt to write versions of, like, write parody lyrics for some random song about this theme. And it’s not bad, but for a lot of that stuff, it’s not great, either. It is a starting point.

Forrest: Now, hang on, Corey. You know, as well as I do that I don’t write parody songs. We’ve had this conversation before. A parody is using existing music and adding new lyrics to it. I write my own music and my own lyrics and I’ll have you know, that’s an important distinction. But—

Corey: True.

Forrest: I think you’re right on that, you know, having these services give you creative output. What you’re getting is an average of a lot of other creative output, right, which is—could give you a perfectly average result, but it’s difficult to get a first pass that gives you something that really stands out. I do also find, as a creative, that starting with something that’s very average oftentimes locks me into a place where I don’t really want to be. In other words, I’m not going to potentially come up with something as interesting if I’m starting with a baseline like that. It’s almost a little bit polluting to the creative process.

I know there’s a lot of other creatives that feel that way as well, but you’ve also got people that have found ways to use generative AI to stimulate some really interesting creative things. And I think maybe the example you gave of the president’s rank by absorbency is a great way to do that. Now, in that case, the initial creativity, a lot of it resided in the prompt, Corey. I mean, you’re giving it a fantastically creative, unusual, off-the-wall place to start from. And just about any average of five presidents that come out of that is going to be pretty funny and weird because of just how funny and weird the idea was to begin with. That’s where I think AI can give you that great writer’s room feel.

Corey: It really does. It’s a Yes, And approach where there’s a significant way that it can build on top of stuff. I’ve been looking for a, I guess, a writer’s room style of approach for a while, but it’s hard to find the right people who don’t already have their own platform and voice to do this. And again, it’s not a matter of payment. I’m thrilled to basically pay any reasonable out of money to build a writer’s room here of people who get the cloud industry to work with me and workshops on some of the bigger jokes.

The challenge is that those people are very hard to find and/or are conflicted out. Having just a robot who, with infinite patience for tomfoolery—because the writing process can look kind of dull and crappy until you find the right thing—has been awesome. There’s also a sense of psychological safety in not poisoning people. Like, “I thought you were supposed to be funny, but this stuff is all terrible. What’s the deal here?” I’ve already poisoned that well with my business partner, for example.

Forrest: Yeah, there’s only so many chances you get to make that first impression, so why not go with AI that never remembers you or any of your past mistakes?

Corey: Exactly. Although the weird thing is that I found out that when they first launched Chat-Gippity, it already knew who I was. So, it is in fact familiar, so at least my early work of my entire—I guess my entire life. So that’s—

Forrest: Yes.

Corey: —kind of worrisome.

Forrest: Well, I know it credited to me books I hadn’t written and universities I hadn’t attended and all kinds of good stuff, so it made me look better than I was.

Corey: So, what have you been up to lately in the context of, well I said generative AI is a good way to start, but I guess we can also call it at Google Cloud. Because I have it on good authority that, marketing to the contrary, all of the cloud providers do other things in addition to AI and ML work. It’s just that’s what’s getting in the headline these days. But I have noticed a disturbing number of virtual machines living in a bunch of customer environments relative to the amount of AI workloads that are actually running. So, there might be one or two other things afoot.

Forrest: That’s right. And when you go and talk to folks that are actively building on cloud services right now, and you ask them, “Hey, what is the business telling you right now? What is the thing that you have to fix? What’s the thing that you have to improve?” AI isn’t always in the conversation.

Sometimes it is, but very often, those modernization conversations are about, “Hey, we’ve got to port some of these services to a language that the people that work here now actually know how to write code in. We’ve got to find a way to make this thing a little faster. Or maybe more specifically, we’ve got to figure out how to make it run at the same speed while using less or less expensive resources.” Which is a big conversation right now. And those are things that they are conversations as old as time. They’re not going away, and so it’s up to the cloud providers to continue to provide services and features that help make that possible.

And so, you’re seeing that, like, with Cloud Run, where they’ve just announced this CPU Boost feature, right, that gives you kind of an additional—it’s like a boost going downhill or a push on the swing as you’re getting started to help you get over that cold-start penalty. Where you’re seeing the session affinity features for Cloud Run now where you have the sticky session ability that might allow you to use something like, you know, a container-backed service like that, instead of a more traditional load balancer service that you’d be using in the past. So, you know, just, you take your eye off the ball for a minute, as you know, and 10 or 20, more of these feature releases come out, but they’re all kind of in service of making that experience better, broadening the surface area of applications and workloads that are able to be moved to cloud and able to be run more effectively on cloud than anywhere else.

Corey: There’s been a lot of talk lately about how the idea of generative AI might wind up causing problems for people, taking jobs away, et cetera, et cetera. You almost certainly have a borderline unique perspective on this because of your work with, honestly, one of the most laudable things I’ve ever seen come out of anywhere which is The Cloud Resume Challenge, which is a build a portfolio site, then go ahead and roll that out into how you interview. And it teaches people how to use cloud, step-by-step, you have multi-cloud versions, you have them for specific clouds. It’s nothing short of astonishing. So, you find yourself talking to an awful lot of very early career folks, folks who are transitioning into tech from other places, and you’re seeing an awful lot of these different perspectives and AI plays come to the forefront. How do you wind up, I guess, making sense of all this? What guidance are you giving people who are worried about that?

Forrest: Yeah, I mean, I, you know—look, for years now, when I get questions from these, let’s call them career changers, non-traditional learners who tend to be a large percentage, if not a plurality, of the people that are working on The Cloud Resume Challenge, for years now, the questions that they’ve come to me with are always, like, you know, “What is the one thing I need to know that will be the magic technology, the magic thing that will unlock the doors and give me the inside track to a junior position?” And what I’ve always told them—and it continues to be true—is, there is no magic thing to know other than magically going and getting two years of experience, right? The way we hire juniors in this industry is broken, it’s been broken for a long time, it’s broken not because of any one person’s choice, but because of this sort of tragedy of the commons situation where everybody’s competing over a dwindling pool of senior staff level talent and hopes that the next person will, you know, train the next generation for them so they don’t have to expend their energy and interview cycles and everything else on it. And as long as that remains true, it’s just going to be a challenge to stand out.

Now, you’ll hear a lot of people saying that, “Well, I mean, if I have generative AI, I’m not going to need to hire a junior developer.” But if you’re saying that as a hiring manager, as a team member, then I think you always had the wrong expectation for what a junior developer should be doing. A junior developer is not your mini me who sits there and takes the little challenges, you know, the little scripts and things like that are beneath you to write. And if that’s how you treat your junior engineers, then you’re not creating an environment for them to thrive, right? A junior engineer is someone who comes in who, in a perfect world, is someone who should be able to come in almost in more of an apprentice context, and somebody should be able to sit alongside you learning what you know, right, and having education integrated into their actual job experience so that at the end of that time, they’re able to step back and actually be a full-fledged member of your team rather than just someone that you kind of throw tasks over the wall to, and they don’t have any career advancement potential out of that.

So, if anything, I think the advancement of generative AI, in a just world, ought to give people a wake-up call that, hey, training the next generation of engineers is something that we’re actually going to have to actively create programs around, now. It’s not something that we can just, you know, give them the scraps that fall off of our desks. Unfortunately, I do think that in some cases, the gen AI narrative more than the reality is being used to help people put off the idea of trying to do that. And I don’t believe that that’s going to be true long-term. I think that if anything, generative AI is going to open up more need for developers.

I mean, it’s generating a lot of code, right, and as we know, Jevons paradox says that when you make it easier to use something and there’s elastic demand for that thing, the amount of creation of that thing goes up. And that’s going to be true for code just like it was for electricity and for code and for GPUs and who knows what all else. So, you’re going to have all this code that has a much lower barrier of entry to creating it, right, and you’re going to need people to harden that stuff and operate it in production, be on call for it at three in the morning, debug it. Someone’s going to have to do all that, you know? And what I tell these junior developers is, “It could be you, and probably the best thing for you to do right now is to, like I said before, get good at coding on your own. Build as much of that personal strength around development as you can so that when you do have the opportunity to use generative AI tools on the job, that you have the maximum amount of mental context to put around them to be successful.”

Corey: I want to further point out that there are a number of folks whose initial reaction to a lot of this is defensiveness. I showed that script that wound up spitting out the Managed NAT gateway ranked-by-region table to one of our contract engineers, who’s very senior. And the initial response I got from them was almost defensive, were, “Okay, yeah. That’ll wind up taking over, like, a $20 an hour Upwork coder, but it’s not going to replace a senior engineer.” And I felt like that was an interesting response psychologically because it felt defensive for one, and two, not for nothing, but senior developers don’t generally spring fully formed from the forehead of some ancient God. They start off as—dare I say it—junior developers who learn and improve as they go.

So, I wonder what this means. If we want to get into a point where generative AI takes care of all the quote-unquote, “Easy programming problems,” and getting the easy scripts out, what does that mean for the evolution and development of future developers?

Forrest: Well, keep in mind—

Corey: And that might be a far future question.

Forrest: Right. That’s an argument as old as time, right, or a concern is old as time and we hear it anew with each new level of automation. So, people were saying this a few years ago about the cloud or about virtual machines, right? Well, how are people going to, you know, learn how to do the things that sit on top of that if they haven’t taken the time to configure what’s below the surface? And I’m sympathetic to that argument to some extent, but at the same time, I think it’s more important to deal with the reality we have now than try to create an artificial version of realities’ past.

So, here’s the reality right now: a lot of these simple programming tasks can be done by AI. Okay, that’s not likely to change anytime soon. That’s the new reality. So now, what does it look like to bring on juniors in that context? And again, I think that comes down to don’t look at them as someone who’s there just to, you know, be a pair of hands on a keyboard, spitting out tiny bits of low-level code.

You need to look at them as someone who needs to be, you know, an effective user of general AI services, but also someone who is being trained and given access to the things they’ll need to do on top of that, so the architectural decisions, the operational decisions that they’ll need to make in order to be effective as a senior. And again, that takes buy-in from a team, right, to make that happen. That is not going to happen automatically. So, we’ll see. That’s one of those things that’s very hard to automate the interactions between people and the growth of people. It takes people that are willing to be mentors.

Corey: I’m also curious as to how you see the guidance shifting as computers get better. Because right now, one of my biggest problems that I see is that if I have an idea for a company I want to start or a product I want to build that involves software, step one is, learn to write a bunch of code. And I feel like there’s a massive opportunity for skipping aspects of that, whereas effectively have the robot build me the MVP that I describe. Think drag-and-drop to build a web app style of approach.

And the obvious response to that is, well, that’s not going to go to hyperscale. That’s going to break in a bunch of different ways. Well, sure, but I can get an MVP out the door to show someone without having to spend a year building it myself by learning the programming languages first, just to throw away as soon as I hire someone who can actually write code. It cuts down that cycle time massively, and I can’t shake the feeling that needs to happen.

Forrest: I think it does. And I think, you know, you were talking about your senior engineer that had this kind of default defensive reaction to the idea that something like that could meaningfully intrude on their responsibilities. And I think if you’re listening to this and you are that senior engineer, you’re five or more years into the industry and you’ve built your employability on the fact that you’re the only person who can rough out these stacks, I would take a very, very hard look at yourself and the value that you’re providing. And you say, you know—let’s say that I joined a startup and the POC was built out by this technical—or possibly the not-that-technical co-founder, right—they made it work and that thing went from, you know, not existing to having users in the span of a week, which we’re seeing more now and we’re going to see more and more of. Okay, what does my job look like in that world? What am I actually coming on to help with?

Am I—I’m coming on probably to figure out how to scale that thing and make it maintainable, right, operate it in a way that is not going to cause significant legal and financial problems for the company down the road. So, your role becomes less about being the person that comes in and does this totally greenfield thing from scratch and becomes more about being the person who comes in as the adult in the room, technically speaking. And I think that role is not going away. Like I said, there’s going to be more of those opportunities rather than less. But it might change your conception of yourself a little bit, how you think about yourself, the value that you provide, now’s the time to get ahead of that.

Corey: I think that it is myopic and dangerous to view what you do as an engineer purely through the lens of writing code because it is a near certainty that if you are learning to write code today and build systems involving technology today, that you will have multiple careers between now and retirement. And in fact, if you’re entering the workforce now, the job that you have today will not exist in anything remotely approaching the same way by the time you leave the field. And the job you have then looks borderline unrecognizable, if it even exists at all today. That is the overwhelming theme that I’ve got on this ar—the tech industry moves quickly and is not solidified like a number of other industries have. Like, accountants: they existed a generation ago and will exist in largely the same form a generation from now.

But software engineering in particular—and cloud, of course, as well, tied to that—have been iterating so rapidly, with such sweepingly vast changes, that that is something that I think we’re going to have a lot of challenge with, just wrestling with. If you want a job that doesn’t involve change, this is the wrong field.

Forrest: Is it the wrong field. And honestly, software engineering is, has been, and will continue to be a difficult business to make a 40-year career in. And this came home to me really strongly. I was talking to somebody a couple of months ago who, if I were to say the name—which I won’t—you and I would both know it, and a lot of people listening to this would know as well. This is someone who’s very senior, very well respected is, by name, identified in large part with the creation of a significant movement in technology. So, someone who you would never think of would be having a problem getting a job.

Corey: Is it me? And is it Route 53 as a database, as the movement?

Forrest: No, but good guess.

Corey: Excellent.

Forrest: This is someone I was talking to because I had just given a talk where I was pleading with IT leaders to take more responsibility for building on-ramps for non-traditional learners, career changers, people that are doing something a little different with their career. And I was mainly thinking of it as people that had come from a completely non-technical background or maybe people that were you know, like, I don’t know, IT service managers with skills 20 years out of date, something like that. But this is a person who you and I would think of as someone at the forefront, the cutting edge, an incredibly employable person. And this person was a little bit farther on in their career and they came up to me and said, “Thank you so much for giving that talk because this is the problem I have. Every interview that I go into, I get told, ‘Oh, we probably can’t afford you,’ or, ‘Oh well, you say you want to do AI stuff now, but we see that all your experience is doing this other thing, and we’re just not interested in taking a chance on someone like that at the salary you need to be at.’” and this person’s, like, “What am I going to do? I don’t see the roadmap in front of me anymore like I did 10, 15, or 20 years ago.”

And I was so sobered to hear that coming from, again, someone who you and I would consider to be a luminary, a leading light at the top of the, let’s just broadly say IT field. And I had to go back and sit with that. And all I could come up with was, if you’re looking ahead and you say I want to be in this industry for 30 years, you may reach a point where you have to take a tremendous amount of personal control over where you end up. You may reach a point where there is not going to be a job out there for you, right, that has the salary and the options that you need. You may need to look at building your own path at some point. It’s just it gets really rough out there unless you want to continue to stagnate and stay in the same place. And I don’t have a good piece of advice for that other than just you’re going to have to find a path that’s unique to you. There is not a blueprint once you get beyond that stage.

Corey: I get asked questions around this periodically. The problem that I have with it is that I can’t take my own advice anymore. I wish I could. But what I used to love doing was, every quarter or so, I’d make it a point to go on at least one job interview somewhere else. This wound up having a few great features.

One, interviewing is a skill that atrophies if you don’t use it. Two, it gives me a finger on the pulse of what the market is doing, what the industry cares about. I dismissed Docker the first time I heard about it, but after the fourth interview where people were asking about Docker, okay, this is clearly a thing. And it forced me to keep my resume current because I’ve known too many people who spend seven years at a company and then wind up forgetting what they did years three, four, and five, where okay, then what was the value of being there? It also forces you to keep an eye on how you’re evolving and growing or whether you’re getting stagnant.

I don’t ever want to find myself in the position of the person who’s been at a company for 20 years and gets laid off and discovers to their chagrin that they don’t have 20 years of experience; they have one year of experience repeated 20 times. Because that is a horrifying and scary position to be in.

Forrest: It is horrifying and scary. And I think people broadly understand that that’s not a position they want to be in, hence why we do see people that are seeking out this continuing education, they’re trying to find—you know, trying to reinvent themselves. I see a lot of great initiative from people that are doing that. But it tends to be more on the company side where, you know, they get pigeonholed into a position and the company that they’re at says, “Yeah, no. We’re not going to give you this opportunity to do something else.”

So, we say, “Okay. Well, I’m going to go and interview other places.” And then other companies say, “No, I’m not going to take a chance on someone that’s mid-career to learn something brand new. I’m going to go get someone that’s fresh out of school.” And so again, that comes back to, you know, where are we as an industry on making space for non-traditional learners and career changers to take the maturity that they have, right, even if it’s not specific familiarity with this technology right now, and let them do their thing, let them get untracked.

You know, there’s tremendous potential being untapped there and wasted, I would say. So, if you’re listening to this and you have the opportunity to hire people, I would just strongly encourage you to think outside the box and consider people that are farther on in their careers, even if their technical skill set doesn’t exactly line up with the five pieces of technology that are on your job req, look for people that have demonstrated success and ability to learn at whatever [laugh] the things are that they’ve done in the past, people that are tremendously highly motivated to succeed, and let them go win on your behalf. There’s—you have no idea the amount of talent that you’re leaving on the table if you don’t do that.

Corey: I’d also encourage people to remember that job descriptions are inherently aspirational. If you take a job where you know how to do every single item on the list because you’ve done it before, how is that not going to be boring? I love being given problems. And maybe I’m weird like this, but I love being given a problem where people say, “Okay, so how are you going to solve this?” And the answer is, “I have no idea yet, but I can’t wait to find out.” Because at some level, being able to figure out what the right answer is, pick up the skill sets I don’t need, the best way to learn something that I’ve ever found, at least for me.

Forrest: Oh, I hear that. And what I found, you know, working with a lot of new learners that I’ve given that advice to is, typically the ones that advice works best for, unfortunately, are the ones who have a little bit of baked-in privilege, people that tend to skate by more on the benefit of the doubt. That is a tough piece of advice to fulfill if you’re, you know, someone who’s historically underrepresented or doesn’t often get the chance to prove that you can do things that you don’t already have a testament to doing successfully. So again, takes it back to the hiring side. Be willing to bet on people, right, and not just to kind of look at their resume and go from there.

Corey: So, I’m curious to see what you’ve noticed in the community because I have a certain perspective on these things, and a year ago, everyone was constantly grousing about dissatisfaction with their employers in a bunch of ways. And that seems to have largely vanished. I know, there have been a bunch of layoffs and those are tragic on both sides, let’s be very clear. No one is happy when a layoff hits. But I’m also seeing a lot more of people keeping their concerns to either private channels or to themselves, and I’m seeing what seems to be less mobility between companies than I saw previously. Is that because people are just now grateful to have a job and don’t want to rock the boat, or is it still happening and I’m just not seeing it in the same way?

Forrest: No, I think the vibe has shifted, for sure. You’ve got, you know, less opportunities that are available, you know that if you do lose your job that you’re potentially going to have fewer places to go to. I liken it to like if you bought a house with a sub-3% mortgage and 2021, let’s say, and now you want to move. Even though the housing market may have gone down a little bit, those interest rates are so high that you’re going to be paying more, so you kind of are stuck where you are until the market stabilizes a little bit. And I think there’s a lot of people in that situation with their jobs, too.

They locked in salaries at ’21, ’22 prices and now here we are in 2023 and those [laugh] those opportunities are just not open. So, I think you’re seeing a lot of people staying put—rationally, I would say—and waiting for the market to shift. But I think that at the point that you do see that shift, then yes, you’re going to see an exodus; you’re going to see a wave and there will be a whole bunch of new think pieces about the great resignation or something, but all it is just that pent up demand as people that are unhappy in their roles finally feel like they have the mobility to shift.

Corey: I really want to thank you for taking the time to speak with me. If people want to learn more, where’s the best place for them to find you?

Forrest: You can always find me at I have a newsletter there, and I like to post cartoons and videos and other fun things there as well. If you want to hear my weekly take on Google Cloud, go to and sign up there. You will get my weekly newsletter The Overwhelmed Person’s Guide to Google Cloud where I try to share just the Google Cloud news and community links that are most interesting and relevant in a given week. So, I would love to connect with you there.

Corey: I have known you for years, Forrest, and both of those links are new to me. So, this is the problem with being active in a bunch of different places. It’s always difficult to—“Where should I find you?” “Here’s a list of 15 places,” and some slipped through the cracks. I’ll be signing up for both of those, so thank you.

Forrest: Yeah. I used to say just follow my Twitter, but now there’s, like, five Twitters, so I don’t even know what to tell you.

Corey: Yes. The balkanization of this is becoming very interesting. Thanks [laugh] again for taking the time to chat with me and I look forward to the next time.

Forrest: All right. As always, Corey, thanks.

Corey: Forrest Brazeal, Head of Developer Media at Google Cloud, and of course the Cloud Bard. I’m Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice, along with an insulting comment that you undoubtedly had a generative AI model write for you and then failed to proofread it.

Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit to get started.
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