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Welcome back, esteemed listener, to another episode of data
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driven. In today's episode, we have the pleasure of delving into the mind
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of Nicholas Means, the vice president of software development at
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SIM. With a keen intellect and a propensity for
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weaving together multifaceted concepts, Nick touches upon the
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enthralling topic of shame and its relevance in our ever evolving software
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industry. Prepare yourself for we shall ponder the
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intricate connection between shame, vulnerability, and the
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cultural shifts within the software engineering landscape.
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As we explore the depths of these subjects, Nick leaves us curious and
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yearning for more recommending a podcast episode that unravels the
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intricacies of this enthralling topic. Now on with
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the show.
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Hello, and welcome to Data Driven, the podcast where we or the emerging fields of
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data science, artificial intelligence, data
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engineering, and occasionally, ever so occasionally,
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IT operations and engineering. Today we welcome
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Nicholas Means to the show. Nick is the VP of engineering at
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STEM, Spelled s y m, not like the video game
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kids, and it's an adaptive process tool built for
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developers. He's been an engineering leader for more than a decade, focused
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on helping teens build velocity through trust and autonomy.
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He's also regular speakers at conferences around the world, teaching more
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effective software development practices through stories of real world engineering
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triumphs And failures. Welcome to the show, Nick.
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Thanks so much for having me on, Frank. Excited to be here. Yeah. Awesome.
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You know, and And we were kinda talking in the virtual green room is that
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you're not really in the data space, but you are, I would say, dare I
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say, distinguished software engineer, and There's a bunch of
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us in the data space now that kinda started in this world, and and I
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think one of the things that that, when your name came across my desk,
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I was like, reading some papers lately about,
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you know, technical debt in data systems.
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Right? Mhmm. And I think that's kind of the big dirty secret,
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and I think that there's a lot that we can learn from software engineering
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practices, in this space as well.
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Yeah. For sure. So what when you say autonomy,
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you know, as an AI geek now, when I think autonomy, I think Something
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completely different. Well, I'm I'm assuming you mean people
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being autonomous from kinda that Dilbert type corner, you know, pointy haired boss
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guy. Right? Yeah. Absolutely. So
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you had a a pretty distinguishing
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distinguished career. You probably have had worked for people like that, and probably
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inspired you to kind of go in the other direction. Is that is that true?
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That's part of it for sure. Yeah. I mean, I, You know, I I
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think my my journey into engineering leadership kind of involved being
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in, like, some locker room kind of cultures where the loudest voice won.
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And and a lot of my motivation from shifting from writing code
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to being on the other side of the business, being being a manager, Was
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wondering if I could do better, wondering if I could could build teams that
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functioned more humanely and actually empowered each other and and supported each
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other in getting their work done. And the the last 10 years of my career
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has kind of been a journey in that direction. So what was
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that moment where you were like, I could do better?
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Interestingly, it was an episode of the Ruby Rogues
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podcast several several years ago, that that featured Alex Harms,
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talking some about the work of Brene Brown, and shame
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and vulnerability in the way that those concepts can inform the way that agile
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teams communicate. And that was, like, when my eyes really kinda opened
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to the idea that maybe the the thing that I was living through wasn't the
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only way to do this and that that it didn't have to be this hard.
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Interesting.
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What does that mean shame in terms of, I mean, you you mentioned kind of
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the the loudest voice in the room wins, the locker room mentality, kind of like,
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you know, you know, it's like we're we're chimps back
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in the savannah, Back mill 1000000 of years ago. Right? Like, we
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like like, is that is that obviously,
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obviously, at some point in history of The human species that might have worked,
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but I don't think in software where 90% of it involves kind of the
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prefrontal cortex, I think e I don't think that's gonna
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work, and What what was
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it about the Bray Brene Brown kinda concept of shame and vulnerability
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that kinda, like, made you Connect the dots because Brene Brown exists in
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kind of a different world than than your average, you know,
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software. I'd like to know more about that podcast episode. We'll have to link the
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to that episode That sounds interesting. Yeah. I mean, so for me, it
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so so part of it is that loudest voice always wins, but one of the
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effects that That almost always happens when you have one of those really loud
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voices in the room is that it tends to silence other voices.
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It tends to make People afraid to raise their hands, say I don't know, ask
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things that feel like obvious questions to them. And all that's kinda
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rooted in in shame And not wanting to be vulnerable and and not knowing
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something or or feeling shame that you don't know something that you think should be
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obvious to you. In reality, it's not. In reality, one of
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the things that that distinguishes the best senior individual
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contributors is willingness to say, I don't know, willingness to ask Questions when
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something comes up in in a discussion that they don't know about, but it takes
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a long time in your career to kinda build yourself up to that
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point of confidence. We're saying I don't know is an easy thing for you to
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do, unless you're in an environment that's that has high psychological
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safety and where those questions are invited And and where the the
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environment is very much set up to be oriented around growth and around making sure
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that everybody is able to ask Those questions able to push back on
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each other when they don't necessarily agree with the the direction something's taking.
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Not in a allowed chest thumping kind of way, but more in a,
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Let's talk about this. I I don't know that that's the best way to proceed,
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but maybe there's something about your position that I'm missing and just that that sort
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of curiosity. Interesting. How does
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the how does shame relate to imposter syndrome?
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Interestingly enough, my very first conference that I ever did was on
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impostor syndrome, and that this was kinda this line of thinking is kinda what sent
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me down that road and made me realize that was a thing that I was
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dealing with. It's it it very much relates to it. Very
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much the idea that it it's hard as a software engineer to
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kinda get perspective on how Good or bad, you are as a software engineer. You're
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really dependent on other people's feedback to do that. And that's
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one of the key components of impostor syndrome is anytime you're in a
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career Where something is subjectively judged, which code
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quality subjectively judged. There's there's rules. There's best practices.
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We don't agree on the rules and best practices, So that puts us squarely in
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in the subjective side of the house. So it's really no different than than being
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a professional musician or a ballerina or something like that.
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You're being judged by the the quality of your work output, but it's a subjective
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set of standards. And people in fields that are judged by subjective
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standards are especially prone to impostor syndrome. Really? I
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did not know that because, I I mean, it may make sense as you explain
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it that way, because if you're a civil engineer. Right? The bridge is
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either gonna stand up or it's not. Right? It's gonna shake too much
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or it's not. Right? The wind, like, the Tacoma Narrows Bridge, right, the
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wind's gonna hit the wrong way, Something's bad is gonna happen, or it doesn't. It's
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it's it's a very real world thing. I I I've often kind of
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wondered as software engineers, or even this applies to data
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people too. Right? What we deal with is so abstract. Mhmm.
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You know, that it is hard to kind of gauge that, and and I
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I can't be the only one that thinks that Because it's subjective,
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organizational politics plays a huge role
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in how someone's judged. I'll share a story. I used to work at this
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consulting firm. Actually, it's back when I met Andy, who's not here
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today. But, This guy wrote
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the most awful code. I don't wanna say his name for, you know,
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lawsuit reasons, but his last name and the word code became a
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synonym for garbage code. Right. But he was such a
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politician. He would walk around, and, like, everyone loved this guy. No one wanted to
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call him out on it even though he Wrote the most god
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awful bits of code. Yeah. And and that was when you
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know, I I wouldn't say it was an moment, but I was like I
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was like, oh, he should be selling used cars. He should be kept away from
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a keyboard. You know what I mean? Yeah. Yeah. Yeah. I mean, that gets into,
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like, the Dunning Kruger effect, right, where Where the people the people that
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often feel the worst at their job feel that way because they know what bits
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of knowledge they're missing, and the people that feel the best at their job feel
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that way because they have no idea what knowledge they're missing. They they just feel
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very confident in the things that they do know, and they're not worried about the
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rest of it. So it's sort of this idea that the more intelligent you
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are the more you're gonna struggle with this stuff. Interesting. It's almost like,
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the self reflection kind of Guess in the same recursive into
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infinite loop and you kind of lose sight of it. Yeah. And
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if you and if you do, if you are completely oblivious,
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You're unaware. It's it's kind of like a a a cruel trick the mind plays.
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Yeah. Absolutely. Interesting. So
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How did you we were talking about physical
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engine, engineering and things like that, like, what
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obviously, you know,
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a bridge falling down that happens. Right? What what can we learn
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because it's subjective, it probably I don't I never say never
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as a policy, usually. See I even qualify
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that. What can we learn from
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real I hate this this was always a thing because there's always,
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like, there's real engineers. Right? Like, the people who build stuff and but I mean,
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like, what can we learn from physical, engineering disciplines? Right?
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Because this this has come up before, I I can imagine,
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and What what can we learn from them? So the
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fascinating thing about that is the the lessons that there are to learn in
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physical engineering disasters are all still based in the human side of it
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Because even though steel is steel is steel, and it behaves according to a set
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of physical rules that we know, the people that work with steel still
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make mistakes in how that steel is gonna behave. I've
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done, you know, I've done a series of talks kind of on on connecting real
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world engineering disasters to the software world. One of them
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that the the steel metaphor brings to mind is the one I did on City
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Corp Center in New York, which is the building that's sort of
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built on stilts. It's It's built up on 4 legs. The legs are actually on
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the the sides of the building, not in the corners, and that created some wind
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loads that weren't accounted for in the original design. And then when it was actually
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being erected, they changed the way that they fastened the
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structural members together, thinking that the the original
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designer structure had overprovisioned them, and that they didn't need that amount of string. They
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could just do rivets and stuff, or they could do bolts instead of rivets. And
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it turned out that it would've it was vulnerable to a 100 year storm, and
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a 100 year storm could have actually blown that building over. And so it's
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the the story kinda gets into Fill the Measure, the the engineer
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that designed it, Basically raising his hand and going, hey, I
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figured this thing out. Thanks to a comment from an engineering
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student. We have to fix this building and, like like, sort of the
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process of talking about what happened
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himself, talking about the mistakes he had made in the design,
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bringing it to the attention of people that could then do something about it. In
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this case, the people that own the building, Citicorp, who financed
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the work, who worked with insurance companies. The whole thing
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is a story of, When you make a mistake, it's better to
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raise your hand early than try to sweep it under the rug and try to
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cover it up, because you'll end up making a bigger mess in in the process,
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and the consequences usually aren't what you've built them up to be in your head.
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So that's that's sort of an example that that kinda gets into the human side.
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No. That's awesome. Like, there are there are things in my life that I if
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I had learned that lesson sooner, would have been a lot easier. I I think
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that's true for all of us, and that's one of the reasons that I I
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find I mean, I'm I honestly, I kinda came into this line of of
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conference speaking because I like to read about disasters a
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lot. I I watch way too much Seconds from Disaster as a kid, and I've
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always been infatuated with this stuff. And it's it's sort of a way for me
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to Justify taking a really deep dive and learning a lot about
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one of these things and getting something productive out at the other end of it
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versus it just being a long Wikipedia Safari for its own sake.
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But I but I you know, there's I think there's a lot that we can
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learn from people that have been doing engineering longer than us because the the
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human factors The the communication between people working
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is still a a thing that existed in the physical engineering world, and that's been
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going on far longer than we've been building software for computers. So there's absolutely things
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that we can learn from those disciplines. Interesting. And in
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regards to the Citibank building thing, I remember seeing something in the History Channel about
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those. Apparently, like, overnight, like, they had
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crews working in the middle of the night. And then is it true? I don't
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remember all the details, but is it true they largely kept a hush-hush? Mhmm.
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Yeah. They did. They would go in, and and they would build these welding shacks
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around the the places where they needed to weld inside the building because all of
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the all the cross members were exposed inside the building, and it just been drywalled
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around them. So they would go in and build a little plywood shack, and knock
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the drywall off, and and weld it. And there's pictures of the building where you
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can see it lit up in the night with somebody welding on one of these
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structural members. Wow. They didn't tell people what was what was
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going on. It came very close to needing to order an evacuation because of a
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tropical storm that was headed towards New York, and the storm ended up turning away
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at Last minute. Wow. Wow. I do
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remember the part about that 100 year storm was, basically,
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almost happened. Yeah. Alright. Here's Andy.
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And in all of our years of podcasting, it's the first time he has,
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shown up late, so, kudos for him.
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I will I will I will either leave this edit raw,
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or, Or, kind of
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include it, with the, the thing. So I'll
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I'll I'll clue Andy in. Nick Means is the VP of software develop
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this I will edit out. VP of software development at a place called
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SIM, and he has connected,
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he's done a lot of personal research out of his interest
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in, disasters, and how those
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lessons can be learned, in software engineering, where
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software engineering, he can I can I can tell if I'm
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paying attention, is that, you know, it's largely been this, you know, who
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who can Pump their chest, the loudest type thing? And
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it's not really been the there's a certain pecking order
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that May have worked in ancient times, but works
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terrible in software engineering. Is that about right? Yep.
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Cool. Oh, wow. Okay. I'm gonna have to listen to the first part of this.
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This reminds me of Spaceballs. This, like, Spaceballs. Let's go
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to the instant machine own video. When will
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then be now? Now. Just now. What is this?
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This is now.
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Well, what happened? Classic.
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Never play that part again.
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Alright. So now that we were on I'm sorry. What? I was gonna say it's
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nice to meet you, Nick. And, You as well. Yeah. Yeah. Sorry Sorry,
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I was late. I've it's a great problem as a consultant to
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have being double booked and stuff, and usually, we're able to work this out,
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but, I am experiencing too much
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business. Again, great problem to have. Still a problem. Yeah. Great
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problem. Especially right now, it's a great problem. Right? Yeah. Yeah.
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So I'm very, very thankful and grateful for that. But, I know
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Frank Frank did a wonderful job, and I'll just, I'll hush now,
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and, we can get on with the show. Alright.
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So we were talking, so so that's interesting. So
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With software engineering, with with buildings and physical
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things. Right? You know, the nuclear reactor can melt down. Right? The, The,
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bridge can collapse, the Citibank building could almost tip over.
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With software engineering, you got a lot of other problems too. Right? I mean,
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Security breaches Mhmm. Come to mind. And and
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in your in your, kinda, your your sheet, like, You mentioned something
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called a blameless mindset. What what is a blameless mindset?
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So, I mean, it's really the the orientation that anytime something happens, your
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primary goal should be to learn from that thing, not to figure out whose fault
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it is. It kinda gets into, if if you if you've done any
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research into, like, safety 2 or or human factors. It gets into the work
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of Sydney Decker and and what he calls forward accountability.
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Kind kind of the idea is that nobody comes to work intending to do a
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bad job. And if if they make a mistake that causes an outage
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or causes a security breach, They probably already feel
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pretty bad about it and don't really need you piling on most of the time
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to learn their lesson. What they do need is a chance to tell their
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story, so that they can kind of put the facts together
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in their own mind. They can help other people learn from from what they just
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did. And that that kinda gets into when
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when something happens. It's often very tempting,
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especially for for us pointy head pointy head boss types To point
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the finger and and to find somebody on whose head the the blame for
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this thing lays. But when you do that, when you focus on
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establishing blame as as a primary Goal in one of these situations,
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you prevent people from learning, and you prevent people from raising their hand when it
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00:17:46
happens. You encourage people to sweep it under the rug. Kinda what we're talking about.
Speaker:
00:17:50
It's it's the thing if Phil Meacher had done this with Citicorp Center. Citicorp Center
Speaker:
00:17:53
probably would have fallen over at some point. And so having a
Speaker:
00:17:56
blameless mindset when something goes wrong encourages people to raise their
Speaker:
00:18:00
hand sooner, bring other people in on the solution, Let the whole organization
Speaker:
00:18:04
learn from the the mistake that they just made. And and, you know, it's kinda
Speaker:
00:18:08
rooted in a systems thinking mindset as well. You know, how can we Change the
Speaker:
00:18:11
system so that a a mistake that's shaped like this is more difficult to
Speaker:
00:18:15
make in the future. So here's a random question.
Speaker:
00:18:20
I noticed that GitHub has something called the blame tool. I think it's part of
Speaker:
00:18:23
Git. Mhmm. Is that is that a tongue in cheek
Speaker:
00:18:27
reference, or is that actually, Like, actually a
Speaker:
00:18:30
blame. Like, what are your thought? Well, I don't know the history of that,
Speaker:
00:18:34
so maybe maybe you could tell me. And then Yeah. I mean, it it is
Speaker:
00:18:38
from Git Self not from GitHub. It's something that just showed up in the in
Speaker:
00:18:41
the GitHub UI from from Git. I actually, on my own system, alias
Speaker:
00:18:45
it to get credit, so I don't have to type git blame. Oh, I like
Speaker:
00:18:48
that. Oh, that's awesome. And that's
Speaker:
00:18:52
I I it's definitely not my original idea. I know a lot of people that
Speaker:
00:18:55
do that as well, just because Get blame puts you in
Speaker:
00:18:59
sort of a certain frame of mind when you're reading code, and it's often not
Speaker:
00:19:02
a helpful or charitable frame of mind. Whereas get credit is more like,
Speaker:
00:19:06
okay. Who can I ask to hear this story of of why this line code
Speaker:
00:19:09
came to be? Yeah. That was because that
Speaker:
00:19:13
yeah. When you mentioned blameless mindset, and I was like but, I mean, I guess
Speaker:
00:19:17
that speaks to kinda, like, you know, like, you know, the origin story
Speaker:
00:19:20
of Git, I guess, Blame the blame tool or I don't I
Speaker:
00:19:24
don't know. Like, it just to me, it just seemed like there's gotta be more
Speaker:
00:19:27
to that story. Yeah. And when I first heard the tool, The guy I was
Speaker:
00:19:30
working with, he thought it was funny. Oh, they have a blame tool, so you
Speaker:
00:19:33
can always know who's to blame. And I was like I was like, that's kinda
Speaker:
00:19:37
mean, actually, you know. A little bit. A little bit. I mean and again, you
Speaker:
00:19:41
know, it gets into, like, the the prime directive of retrospectives if you've done spent
Speaker:
00:19:44
any time in the Agile world. This idea that everybody was doing the best that
Speaker:
00:19:47
they could at the time that they did it and made the best decision they
Speaker:
00:19:50
could with the information they had. Right.
Speaker:
00:19:53
What's interesting in as you see those That
Speaker:
00:19:58
agile processes kind of happen, right? There's there's
Speaker:
00:20:02
the theory, and then there's the practice. Mhmm. And
Speaker:
00:20:05
Its organizational culture tends to take all the
Speaker:
00:20:09
oxygen out of that room. Yeah. You know and and you're not
Speaker:
00:20:13
surprised so I guess that's that's a thing You know? I
Speaker:
00:20:16
I I like to and I forget who coined this distinction. It may
Speaker:
00:20:20
have been kept back, the idea of big a agile versus little a agile.
Speaker:
00:20:24
Yes. Big Agile, the idea that there's all all these off the
Speaker:
00:20:28
shelf methodologies that you can just pick up off the shelf and adopt in your
Speaker:
00:20:31
organization, and and suddenly the the heavens will part and will sound and you will
Speaker:
00:20:35
be more agile. You look at something like SAFe, the
Speaker:
00:20:38
scaled agile framework, and you can pretty clearly see that that's not the case. It's
Speaker:
00:20:42
just Waterfall in disguise at the organizational level.
Speaker:
00:20:46
Whereas more more little a agile is the actual principles, the
Speaker:
00:20:49
spirit of Of sort of the agile software movement where it is more
Speaker:
00:20:53
autonomous. It is more short planning cycles, getting feedback early,
Speaker:
00:20:57
shipping in small increments, that sort of thing. And it's really easy to pick up
Speaker:
00:21:00
an off the shelf agile methodology and not do any of that stuff.
Speaker:
00:21:04
Right. I I remember hearing an interview once, a podcast,
Speaker:
00:21:08
probably a decade ago where, someone referred
Speaker:
00:21:11
to their, their software development life cycle
Speaker:
00:21:15
as Scrum Bud. Mhmm. And so when we're doing
Speaker:
00:21:19
scrum, but and then, you know, something followed that wasn't
Speaker:
00:21:22
scrum. And it sounds a lot like what you're describing. Yep.
Speaker:
00:21:26
Absolutely. Yeah. One of the reasons I I tend to be more with my teams,
Speaker:
00:21:30
more Kanban inspired than Scrum inspired. And and the reason for that
Speaker:
00:21:33
is Because I've seen too many teams try to win the
Speaker:
00:21:37
sprint, and and it sort of creates this perverse incentive to just
Speaker:
00:21:41
get code across the line no matter what it takes. Yeah. I I like
Speaker:
00:21:45
the community aspect of Kanban, the swarming, and Mhmm. You know, I've
Speaker:
00:21:48
seen that work. I I actually learned that on a real live plant
Speaker:
00:21:52
floor. So, you know, I've got I I used to joke with
Speaker:
00:21:56
Frank that I've got about 8 more years of books I can write,
Speaker:
00:21:59
process engineering because I know where they're going. Yeah. And, you know,
Speaker:
00:22:03
and and what's interesting is we've reached that phase where I was in
Speaker:
00:22:06
manufacturing in the late, nineties, And we reached that
Speaker:
00:22:10
phase where we learned where it wouldn't work. Mhmm. For
Speaker:
00:22:13
instance, it didn't work in engineering.
Speaker:
00:22:17
So it's interesting that we're kinda getting to that maturity. I guess that
Speaker:
00:22:21
maturity would be a good description of it, where we're seeing in the context,
Speaker:
00:22:25
Especially if software engineering that is falling over some.
Speaker:
00:22:29
Mhmm. It works really, really well on the plant floor Mhmm. When you're
Speaker:
00:22:32
in a manufacturing environment, that quality goes through the roof.
Speaker:
00:22:36
Deming's methodologies are phenomenal. The,
Speaker:
00:22:41
And maybe you've already covered this, but the culture wherein a lot
Speaker:
00:22:44
of that, you know, from the manufacturing perspective was developed,
Speaker:
00:22:48
is a vastly different culture than we have today in the United States.
Speaker:
00:22:52
It wasn't even I mean, it was Japan. Right. You know? Coming
Speaker:
00:22:56
out of post World War 2, and That's that is a
Speaker:
00:23:00
different place. Mhmm. It's probably different than Japan today. I'm
Speaker:
00:23:03
sure it is. Yeah. You know? So That that has a lot to do with
Speaker:
00:23:07
it, and you did, I heard I heard the screed behind the
Speaker:
00:23:11
words about corporate culture. That's that's a huge driver.
Speaker:
00:23:15
Mhmm. It it just is. Alright. I'll show up. It's and it's, you know,
Speaker:
00:23:19
it's it's not it's really not any different than than what we're talking about about
Speaker:
00:23:22
off shelf agile methodologies. Right? Like, all of these things are tool are toolboxes.
Speaker:
00:23:26
There's useful things in all of them, and there's things that don't apply and don't
Speaker:
00:23:29
work On an organization by organization, team by team basis.
Speaker:
00:23:33
Absolutely. And the trick is you have to be able to have all of these
Speaker:
00:23:35
tools in your toolbox and then go up to a team and go, oh,
Speaker:
00:23:40
I know this shape problem, and I these are the things that we can try
Speaker:
00:23:43
that that will help make this better. Right. Right.
Speaker:
00:23:47
What's your, sorry, Anya cut your head. Go ahead. Go
Speaker:
00:23:51
ahead. How do how does, how
Speaker:
00:23:54
does a software engineering team
Speaker:
00:23:58
Change or leadership within software engineering change the the
Speaker:
00:24:02
the organizational culture, Because I think that's a
Speaker:
00:24:05
big problem. I think that software is eating the
Speaker:
00:24:09
world. I think that was a Mark Zuckerberg quote, and I think that, yeah,
Speaker:
00:24:13
Definitely since ChatGPT, I would say AI is
Speaker:
00:24:17
eating the world. Right? But but ultimately, I'm old enough to
Speaker:
00:24:21
remember when software people were those weird people that they they stuffed us in the
Speaker:
00:24:24
basement Mhmm. And did not wanna hear anything from us
Speaker:
00:24:29
Other than everything's working fine, everything's fine, they certainly
Speaker:
00:24:32
did not wanna hear, management philosophy of,
Speaker:
00:24:37
stump speeches from us. I imagine that's changed
Speaker:
00:24:41
a little, but how does how does
Speaker:
00:24:45
someone who's listening to this Wants to affect chains, wants to
Speaker:
00:24:48
kinda bring that blameless mindset into their organization. How do they
Speaker:
00:24:52
start? I know that's probably, like, a 3 hour talk,
Speaker:
00:24:56
but Where would they how
Speaker:
00:25:00
would they what's the first step? Yeah. I mean, what what a great
Speaker:
00:25:03
question. You know, I think step
Speaker:
00:25:07
1 is just learning and and kind of figuring out where this information
Speaker:
00:25:10
exists. So, like, reading some of the blog posts from John Alsbaugh when
Speaker:
00:25:14
he was When he was CTO at Etsy, reading some of the work
Speaker:
00:25:18
of Sydney Decker, that he's done on safety 2. I mean,
Speaker:
00:25:22
John John Osborn is still out on the speaking circuit doing talks a regular basis.
Speaker:
00:25:25
So there's there's plenty of material to learn from out there. I think it's
Speaker:
00:25:29
it's probably most at home in the SRE community right now.
Speaker:
00:25:33
That's that's where I see a lot of safety cultures and human factors research coming
Speaker:
00:25:37
out as in NSRE at the moment. It was it's still in the dev ops
Speaker:
00:25:40
movement as well. That's kinda where I got acquainted with it. So step
Speaker:
00:25:44
1's kind of learning and then just teaching, giving people the
Speaker:
00:25:47
opportunity to realize that There is a different way that some of the stuff can
Speaker:
00:25:51
be done. You know, as far as an engineering leader being able
Speaker:
00:25:55
to affect larger change in an in an organization, The
Speaker:
00:25:58
one advantage that an engineering leader has is that software
Speaker:
00:26:02
engineering salaries are usually one of an organization's biggest cost centers.
Speaker:
00:26:06
And so it's pretty easy to make a case that optimizations there will
Speaker:
00:26:10
pay off if you can make a A persuasive
Speaker:
00:26:14
case for the optimizations that you wanna make. And that's where some of the things
Speaker:
00:26:17
like getting into manufacturing theory and queuing theory and
Speaker:
00:26:21
systems thinking and being able to put together a very data driven
Speaker:
00:26:25
kind of case around some of the improvements that you're trying to affect and the
Speaker:
00:26:28
ways that you're trying to affect them. It it's funny. One
Speaker:
00:26:31
of one of the most common interventions that I found myself making over and over
Speaker:
00:26:35
again with engineering teams is putting WIP limits in place. Just
Speaker:
00:26:39
because when an engineering team is trying to work on too many things at the
Speaker:
00:26:42
same time, they end up spending so much of their time on context
Speaker:
00:26:46
shifting And and trying to load up new contexts and pick up a
Speaker:
00:26:49
project that's completely different than the one that they're currently working on so they can
Speaker:
00:26:52
provide effective code review, that sort of thing. And it's pretty
Speaker:
00:26:56
easy to kinda talk through the data of if we work on less,
Speaker:
00:27:00
we can get more done, but it's really counterintuitive on the
Speaker:
00:27:03
surface when you first hear that statement. Well, the whole drive
Speaker:
00:27:07
towards parallelism. Mhmm. You know, from a machine level right
Speaker:
00:27:11
through you know, it bleeds through. They're all leaky abstractions to throw out some
Speaker:
00:27:15
other Yep. Terms. But, you know, that that whole idea that if you
Speaker:
00:27:18
do things in parallel, you're gonna be able to accomplish more. And I've
Speaker:
00:27:22
seen, I'm gonna I can't remember the book. I was reading
Speaker:
00:27:26
reading a book by someone. It was maybe 2, 3, 4 years old,
Speaker:
00:27:30
and He was talking about just the exact opposite, and he had use
Speaker:
00:27:33
cases and it just you know, serialize it, and
Speaker:
00:27:37
you'll get more done. And it it it's exactly that context
Speaker:
00:27:41
You eliminate that. Human brains stink at constant
Speaker:
00:27:45
context switching. Awful at it. Yeah. Yeah. So
Speaker:
00:27:49
Great. Great point. Interesting.
Speaker:
00:27:52
So another thing that you you kinda
Speaker:
00:27:56
Mention is talking about compliance. Mhmm. And before everyone
Speaker:
00:28:00
kind of tunes off, turns off the the thing and stops,
Speaker:
00:28:06
stops listening. Bear with me. There's a point here, and I think it's
Speaker:
00:28:09
important. No one gets excited about compliance. I I know I know
Speaker:
00:28:13
that. My wife works in IT security compliance. No
Speaker:
00:28:17
one's happy to see her. I'm I'm happy to see her, but no one at
Speaker:
00:28:20
her job is happy to see her. Dear Roberta, you'll never
Speaker:
00:28:25
Alexa, order some flowers. The,
Speaker:
00:28:30
but With the rise of software
Speaker:
00:28:33
being more and more important, more critical to our, I was talking to somebody
Speaker:
00:28:37
else. It might have been in a preview, The another guest on
Speaker:
00:28:40
another completely random topic. I think
Speaker:
00:28:44
regulation is coming to the software industry whether we like
Speaker:
00:28:48
it or not, Because of its core kind
Speaker:
00:28:52
of nature to our, just economy and infrastructure. Mhmm. And I think that
Speaker:
00:28:56
compliance is gonna be one of those things where, You know, learn
Speaker:
00:29:00
it or, you know, learn it, love it, or, you know, leave the
Speaker:
00:29:03
industry. Yeah. Yeah. And and, Yeah. I'm
Speaker:
00:29:07
sorry. So so, like, how do you how does that it seems like
Speaker:
00:29:11
that would kinda dovetail into this. Right? The the the Learning from
Speaker:
00:29:14
mistakes and and meeting these compliance. I mean, certainly, we see it
Speaker:
00:29:18
in data and various data compliance schemes, but but how does he think this is
Speaker:
00:29:23
How does this gonna affect kind of software? Yeah. I mean, the the first thing
Speaker:
00:29:26
I was gonna say is you can you can already see some of this in
Speaker:
00:29:29
things like GDPR and the California privacy regulations, The the stuff the White
Speaker:
00:29:32
House has been doing lately on software bill of materials, we're starting to see it
Speaker:
00:29:36
kind of creep in in in the in the periphery of the things that we
Speaker:
00:29:39
work on. You know, it's
Speaker:
00:29:42
it's tempting to just look at it and go, this is dumb. This will never
Speaker:
00:29:46
work. It's not gonna make any difference. But there's a there's a There's a more
Speaker:
00:29:50
terrible way to look at it in that it's pointing at a thing that
Speaker:
00:29:53
actually is really important. You know, to to your point, s soft
Speaker:
00:29:57
reads the world as organizations hold on to more and more and more and more
Speaker:
00:30:00
data. That data's a liability, and
Speaker:
00:30:05
If if we're not taking steps to make sure that, a, we're only
Speaker:
00:30:09
holding the data we actually need to hold, and, b, we're doing it as
Speaker:
00:30:13
carefully as we can. We're putting as many walls around it as we can, and
Speaker:
00:30:16
still be able to do our job on on an ongoing basis.
Speaker:
00:30:21
You sort of have to put that responsibility hat on and and think about
Speaker:
00:30:25
it in terms of how can I be a good steward of the data
Speaker:
00:30:28
that people have entrusted to me in in this organization that our customers have given
Speaker:
00:30:32
us? Yeah. And and in that that perspective, when you're looking at it
Speaker:
00:30:36
from the Spirit of law versus the letter of the law. It makes some of
Speaker:
00:30:39
the controls that you need to put in place for some of these compliance regimes
Speaker:
00:30:42
a little bit easier to swallow, And it also gets you into sort
Speaker:
00:30:46
of a an outcome mindset because, you know,
Speaker:
00:30:49
it's really easy to go through and and comply with some of these regulations with
Speaker:
00:30:52
checkboxes. Just do the things they say and and not really
Speaker:
00:30:56
actually make any difference in the overall security of your organization.
Speaker:
00:31:00
But if you look at it from a perspective, this is actually a And and
Speaker:
00:31:03
we should actually be doing this, then you can go about it and put
Speaker:
00:31:06
meaningful controls in place that that don't make it harder to get work done.
Speaker:
00:31:10
They just make it safer to get work And that's ultimately that's ultimately the goal.
Speaker:
00:31:14
That's I mean, that's what we're working on at Sym. It's sort of the whole
Speaker:
00:31:16
point of the product. Yeah. It's a good segue. So
Speaker:
00:31:20
what is Sym? SYM. Not the
Speaker:
00:31:23
Sims. I'm sure that's not I know that's not the first
Speaker:
00:31:27
time you heard the joke today, but, You know? So It's it
Speaker:
00:31:31
is not the 1st time I've heard that joke for sure. What what is what
Speaker:
00:31:35
is Sym do? Like, what What
Speaker:
00:31:38
is the the product? It it's essentially at its core workflow
Speaker:
00:31:42
engine. It allows you to build simple workflows to
Speaker:
00:31:45
request and Orchestrate access to to
Speaker:
00:31:49
production systems. It's probably easiest to explain by just telling you
Speaker:
00:31:52
how we use the product at SEM. We have all of our production infrastructure behind
Speaker:
00:31:56
our own product. So when one of our engineers needs access to
Speaker:
00:32:00
a production system, they just they create a request in Slack, and
Speaker:
00:32:03
then anybody else on the engineering team can approve that request. So kind of a
Speaker:
00:32:07
a 2 keys to launch the rocket approach. And then in the back end,
Speaker:
00:32:11
there's some code that runs in AWS. We assume a role An
Speaker:
00:32:14
AWS that lets us escalate somebody into that
Speaker:
00:32:18
administrator access role or whatever permission set that they've requested
Speaker:
00:32:22
so they can go in and do their job. And then an hour later or
Speaker:
00:32:25
or 4 hours later, whatever time interval they've requested, that access expires.
Speaker:
00:32:29
So you don't end up over time accumulating that janitor's key ring of System access
Speaker:
00:32:33
that you don't actually need on a daily basis. Right.
Speaker:
00:32:37
That's cool. That is interesting.
Speaker:
00:32:41
Now and it it you said something, a a a little bit ago that
Speaker:
00:32:44
I thought was might have sound blasphemous to some of our listeners. Right?
Speaker:
00:32:48
The data is a liability. Yeah. But the more, like, you kinda unpack it,
Speaker:
00:32:52
oh, yeah, I mean, you're right. Like, you know, we're so conditioned to think of
Speaker:
00:32:56
data as an asset, and and asset only. Right?
Speaker:
00:32:59
That I think we will lose sight of reality. Right? Or the
Speaker:
00:33:03
risks of holding data. Right? And I was just thinking, like, you know, if I
Speaker:
00:33:06
had a company, and I had, let's just say, some kind of PII. Mhmm.
Speaker:
00:33:10
Right? And I, after so many
Speaker:
00:33:13
months, or once I'm done doing what I'm doing, I purge it. Right?
Speaker:
00:33:18
I probably would sleep better at night if if I heard,
Speaker:
00:33:22
about, like, there's a there's a breach or anything like that. Right? Like, it's kind
Speaker:
00:33:26
of like, I think I think that there's a, for lack of better term, data
Speaker:
00:33:29
hoarding happening in a lot of organizations. Yeah. And I understand it,
Speaker:
00:33:33
right, because there's this If we've been so conditioned to think data
Speaker:
00:33:37
is only an asset, right? Oh, well, why
Speaker:
00:33:40
not just store it? Store it is cheap, you know? Right? But if
Speaker:
00:33:44
you also think that it can also be a liability,
Speaker:
00:33:48
and obviously not all data types are created equal. Right. Yeah. Of course. And not
Speaker:
00:33:51
all liabilities are created equal. Mhmm. Then that becomes a pretty cold
Speaker:
00:33:55
calculation of, well, yeah, maybe we'll figure
Speaker:
00:33:58
out, you know, if they have an even or odd social security
Speaker:
00:34:01
number. If that means that they're more likely to buy our
Speaker:
00:34:05
product. Yeah. But I don't wanna even hold that stuff anymore. Right? Or
Speaker:
00:34:09
I'll collapse it into, you know, Flag 1, flag 2 based on
Speaker:
00:34:13
that. Right? So, you you know, I I I like that. I hadn't
Speaker:
00:34:16
really thought about that. Yeah. I mean, one of the interesting use cases, you know,
Speaker:
00:34:20
if you think of health care data, there's some of that that you have to
Speaker:
00:34:22
hold. Right. But HIPAA is pretty strict about who can access it and when they
Speaker:
00:34:26
can access it. So one of the workflows that we've seen set up is
Speaker:
00:34:29
is requesting approval to access a particular patient's
Speaker:
00:34:33
data with a reason for needing that access So that it's all audit logged.
Speaker:
00:34:36
It's all recorded, who requested it, who approved it, that there was an actual business
Speaker:
00:34:40
need to access that data, that it wasn't done willy nilly, or
Speaker:
00:34:44
that that you had the patient's permission to access that data.
Speaker:
00:34:47
You know, just creating that that simple little bit of
Speaker:
00:34:51
diligence to say, yeah, this data access happened for a reason.
Speaker:
00:34:55
Right. And that it's automatically documented, so then you don't have Some
Speaker:
00:34:59
tedious manual process where you have to fill out a form and and fax it
Speaker:
00:35:02
to headquarters and wait on them to contact somebody and, you know, the the typical
Speaker:
00:35:05
Byzantine Data access processes in health care.
Speaker:
00:35:10
Very cool. I I tweeted that. I didn't overheard.
Speaker:
00:35:14
Oh, I heard that more and more lately here, because during the pod
Speaker:
00:35:18
you know, the podcast recordings because, definitely trying
Speaker:
00:35:22
to tease season 7. And, yeah. It's
Speaker:
00:35:25
that's a that is a great a great line. It's it's got controversy
Speaker:
00:35:29
written all over it, Nicholas. Thank you. Absolutely. God, I can have
Speaker:
00:35:33
one. I totally agree with you, on on that. And
Speaker:
00:35:36
it's you know, I and I understand the drive to say data is
Speaker:
00:35:40
an asset Because for so long, people just looked at at data
Speaker:
00:35:44
as being something kinda neutral. You know? It was hanging around. Maybe they were,
Speaker:
00:35:48
Yeah. I was taking up space, filling up the sand Or byproduct. Or
Speaker:
00:35:52
byproduct. Right? Right. You know, I I always think of the story about I I
Speaker:
00:35:55
don't know exactly the chemical Or whatever, but apparently,
Speaker:
00:36:00
I guess steel mills used to produce, like, this kind of ash, and
Speaker:
00:36:03
it was useless until somebody figured out that it's Good for,
Speaker:
00:36:07
getting traction in snow or for car for for parking
Speaker:
00:36:11
lots or something like that. I I It's it's a bit late in the day.
Speaker:
00:36:15
It's been a long day, so I I don't forget exactly what it's about, but
Speaker:
00:36:18
I remember. So, you know, so the story goes is that, you know, whoever
Speaker:
00:36:21
figured that out, I mean, they the the
Speaker:
00:36:25
steel companies just, like, here, if you're willing to take our trash, go ahead. As
Speaker:
00:36:28
soon as they found out that this guy was making money off that, Suddenly, it
Speaker:
00:36:32
was no longer free. They charged, like, you know,
Speaker:
00:36:35
$5 a ton or something like that. It was just interesting how How,
Speaker:
00:36:39
you know, as the thing goes, 1 man's trash is another man's treasure, but as
Speaker:
00:36:42
soon as it becomes a treasure, then other people are gonna see
Speaker:
00:36:46
that. Yeah. I mean, at point in time example, Reddit's in the
Speaker:
00:36:50
process of making their API paid right now so that you have to pay to
Speaker:
00:36:53
train, like, large language models on it. Interesting.
Speaker:
00:36:58
I would shudder to think what a a large language model training that would
Speaker:
00:37:01
be. Little scary. You know, I don't wanna go to go down that
Speaker:
00:37:05
That's something I've been watching a lot lately, for
Speaker:
00:37:09
some for some playtime work I've been doing. And,
Speaker:
00:37:13
it dramatically dropped, The, the cost to
Speaker:
00:37:16
train because the large language models aren't as large any
Speaker:
00:37:20
Mhmm. At least the sets of tokens and such. Yeah. So it's gone
Speaker:
00:37:24
down to, like, less than $100. That that's on certainly less
Speaker:
00:37:28
than 1,000, but in some cases, like, you know, 30, $40 to train him
Speaker:
00:37:31
on. Yes. Which is a far cry from the 7 to 12,000,000 that
Speaker:
00:37:35
Right. Yeah. That some of the more popular ones have been on. So it's,
Speaker:
00:37:39
you know, and and and it it amuses me that, you know, you have countries
Speaker:
00:37:43
that are trying to ban chat gpt. Right? The the the
Speaker:
00:37:46
cat's out of the bag, genie's out, whatever, Genius on the bottle, like, you can't
Speaker:
00:37:50
stop the signal, you know, like, it's already out. And Great
Speaker:
00:37:54
reference, Frank. Yeah.
Speaker:
00:37:57
I was talking to somebody yesterday on a completely on nontechnology
Speaker:
00:38:01
related thing, and I said, you can't stop the signal. And he got the reference,
Speaker:
00:38:05
so which I thought was pretty funny.
Speaker:
00:38:09
But I'm sorry I cut you off, Nick. No. Oh, thought
Speaker:
00:38:12
I did. No. This is
Speaker:
00:38:16
a fascinating conversation. I think we can go on for hours, but we wanna be
Speaker:
00:38:20
respectful of your time and switch to our pre canned questions.
Speaker:
00:38:24
I will kick off number 1 because we have to change it slightly. How did
Speaker:
00:38:27
you find your way into technology? Did tech find you, or did that
Speaker:
00:38:31
Techlife, Where you found that Tech Life?
Speaker:
00:38:34
So I had an uncle that when I was,
Speaker:
00:38:38
gosh, 9 or 10, Had an old Amiga
Speaker:
00:38:42
computer, and that was the 1st computer I spent any significant time
Speaker:
00:38:46
with, and just sort of Really kinda fell in
Speaker:
00:38:49
love with it as a toy first. And then, you know, not long after
Speaker:
00:38:53
that, IBM PC's PC DOS came out.
Speaker:
00:38:57
Basic was everywhere. Went to a summer camp and learned how to program
Speaker:
00:39:01
in basic. And, the the first productive thing I ever did on a
Speaker:
00:39:04
computer was I wrote a 20 question quiz in Apple
Speaker:
00:39:08
2 Basic over Egyptian history for a
Speaker:
00:39:11
6th grade project. And I Nice. We didn't have a computer at home at the
Speaker:
00:39:15
time, so I stayed after school working on that Apple 2 to write that code.
Speaker:
00:39:19
And just I I obviously got a good grade on the assignment and just have
Speaker:
00:39:22
I've been infatuated with being able to make the the
Speaker:
00:39:26
magic blinking box kinda do what I want it to do ever since.
Speaker:
00:39:30
I like that description. Very cool. Our
Speaker:
00:39:34
second question is, what's your favorite part of your current gig?
Speaker:
00:39:39
My favorite part of my current gig is kinda it gets into what we were
Speaker:
00:39:41
talking about at The the top of the call, sort of
Speaker:
00:39:45
being able to really shape and and build a culture where the the people
Speaker:
00:39:49
on the engineering team are really able to thrive, and really able to support each
Speaker:
00:39:52
other. It's a really fun group of people
Speaker:
00:39:56
to get to work with, and and the way that they're able to support each
Speaker:
00:39:59
other in projects and in in growth and, learning new things is
Speaker:
00:40:03
really, really fulfilling for me from from a leadership perspective.
Speaker:
00:40:10
Interesting. So we have 3 complete the
Speaker:
00:40:13
sentence, questions. When I'm not working, I
Speaker:
00:40:17
enjoy blank. Trying to come up with 1 answer,
Speaker:
00:40:20
but this is really hard. I'm a huge soccer fan, so I'll say that. I
Speaker:
00:40:24
we have season tickets to Austin FC, watch a lot of EPL with my son.
Speaker:
00:40:28
My son plays. So Oh, cool. A a lot of a lot of 90
Speaker:
00:40:32
minute increments of my life are spent watching soccer matches.
Speaker:
00:40:37
Awesome. Our second is, I think the coolest thing in
Speaker:
00:40:41
technology today is Blank. That it's
Speaker:
00:40:45
becoming more humane. Like, the the conversation that we had at the
Speaker:
00:40:48
top of the call is one that is Far more common
Speaker:
00:40:52
today than it was 20 years ago when I started my career. And I think
Speaker:
00:40:55
it's only gonna get more that way, because As systems get
Speaker:
00:40:59
more complicated, we're gonna have more sophisticated and complicated discussions
Speaker:
00:41:03
about humans' roles and interacting with those systems. AI is a great
Speaker:
00:41:06
example. What part of jobs does this supplant? What part of jobs does
Speaker:
00:41:10
it augment? How do we do it in a safe way? How do we keep
Speaker:
00:41:12
it aligned with people? And at at at the root, Those are all questions about
Speaker:
00:41:16
how do humans interact with technology and with each other when technology's
Speaker:
00:41:20
in the room, and I think that's a really interesting bit of history to get
Speaker:
00:41:23
to live through. Interesting.
Speaker:
00:41:27
Our 3rd and final complete the sentence. I look forward to the day when I
Speaker:
00:41:31
can use technology to blank.
Speaker:
00:41:35
I just did my taxes, so autonomously do my taxes. That would
Speaker:
00:41:39
be nice.
Speaker:
00:41:43
Here's a moonshot goal. Have, some kind of large language model that can explain
Speaker:
00:41:47
the tax code in the United States. K. Good good luck with that one. It
Speaker:
00:41:50
would just Yeah. Yeah. Answers.
Speaker:
00:41:55
Oh, I thought of, like, 3 things to say, and I'm not gonna
Speaker:
00:41:59
say either of those things Because
Speaker:
00:42:03
We wanna keep our Itunes clean rating. I'm not gonna I'm not gonna
Speaker:
00:42:07
finish that segment. Yeah. Good segue to that. Share something different about
Speaker:
00:42:11
yourself. And do remember that we're a family show,
Speaker:
00:42:15
and we wanna keep that clean rating. Something different about
Speaker:
00:42:18
myself. I am really, really obsessively into To pour
Speaker:
00:42:22
over coffee. I spend an awful lot of time and
Speaker:
00:42:25
energy trying to dial in my daily cup because it's it's that just
Speaker:
00:42:29
Even the ritual of making coffee in the morning is sort of the thing that
Speaker:
00:42:32
mentally transitions me into work as someone who works from home. Uh-huh.
Speaker:
00:42:35
And, it it's one of those things that The more time I
Speaker:
00:42:39
spend on it, the more I learn about it, the more it rewards me with
Speaker:
00:42:42
a better cup of coffee. So you're doing the filter In
Speaker:
00:42:46
the kind of the ring, and you put the grounds in Mhmm. And then pour
Speaker:
00:42:49
the coffee through them. Yep. That's interesting.
Speaker:
00:42:54
So, yeah, I've I do a French press, but I've been doing that for I
Speaker:
00:42:57
don't know. It's way too long. But the, the I've
Speaker:
00:43:01
heard AeroPress. I've never I've had a lot of people recommend AeroPress. I've never
Speaker:
00:43:04
really tried it. It's great. So is it? It's a it's a really easy
Speaker:
00:43:08
way to get a really good cup of coffee. So what do you think the
Speaker:
00:43:11
big difference is then between AeroPress and pour over?
Speaker:
00:43:17
With AeroPress, Pressure is a component of how you're brewing. I mean, it's not
Speaker:
00:43:20
anything close to espresso. Yeah. But but you're generally going
Speaker:
00:43:24
to brew you're gonna grind a little bit Feiner for AeroPress, you're gonna
Speaker:
00:43:28
extract a little bit different notes out of the coffee with a little bit of
Speaker:
00:43:30
pressure that you add. So you kinda have to dial in the rest of things
Speaker:
00:43:34
to make sure you're extracting the part of the coffee that you wanna
Speaker:
00:43:37
drink. You said notes. Mhmm. So is that how you think about
Speaker:
00:43:41
it musically? Flavor notes. Flavor notes. So light. I
Speaker:
00:43:45
didn't understand. Yeah. I mean, you know, if you get into, like, the the one
Speaker:
00:43:48
of the easiest ones to taste in in lighter roast coffees is the difference between
Speaker:
00:43:52
a natural process and a washed processed coffee. So if
Speaker:
00:43:55
you get a single origin washed processed coffee, you're gonna get all kinds of citrus
Speaker:
00:43:59
notes from it. You're gonna get orange and lemon. If you get a natural
Speaker:
00:44:02
process, it's probably gonna be weighted more towards the berry side of the flavor
Speaker:
00:44:06
spectrum. So Interesting. A really good Ethiopian natural process
Speaker:
00:44:10
coffee Prepared well is gonna taste like blueberry pie in a way that you just
Speaker:
00:44:13
cannot miss. Wow. I've had really
Speaker:
00:44:17
I've had good coffee. I and I'm sitting here, like
Speaker:
00:44:21
Like, when I when I wake up in the morning, like, I am the only
Speaker:
00:44:24
thing I can functionally do is let the dogs outside
Speaker:
00:44:27
and Lift the Keurig machine, drop the kappa in, hit the button,
Speaker:
00:44:31
which I know is probably blasphemy, to
Speaker:
00:44:35
to to to To the purest out there, but I'm just incapable of doing.
Speaker:
00:44:38
However, if I am somewhere, and I can enjoy a good cup of coffee after
Speaker:
00:44:42
I've had my first couple of, cops to get conscious?
Speaker:
00:44:47
I do I do I have had that that type of Ethiopian single
Speaker:
00:44:51
source, and It's it's just very it's very strange.
Speaker:
00:44:55
Like, almost has, like, blueberry ish pie thing
Speaker:
00:44:59
going on. Like Like, what is in it? You know, like but and
Speaker:
00:45:03
then I think it was at some airport somewhere. It might have been Seattle where
Speaker:
00:45:06
they had, like they take coffee extremely seriously. And Mhmm. I was like, no.
Speaker:
00:45:10
No. No. That's just part of the thing. I was like, oh, that's interesting. So,
Speaker:
00:45:13
yeah, you had me at Blueberry. Now I got you at Blueberry. Yeah. I'm
Speaker:
00:45:17
a I'm a Blueberry fanatic. Nice. Awesome.
Speaker:
00:45:23
Alright. So Audible is a sponsor of Data Driven.
Speaker:
00:45:27
Do you do audiobooks and and do you recommend okay. Cool.
Speaker:
00:45:31
So, any particular lessons you would recommend to our,
Speaker:
00:45:34
listeners? I will give you 2. Right now, I'm listening to
Speaker:
00:45:38
John Scalzi's agent to the stars, narrated by Wil Wheaton, who is my
Speaker:
00:45:42
absolute favorite audiobook narrator. I actually pick audiobooks based on the
Speaker:
00:45:45
fact that he's the one that narrates them because he's just the the character
Speaker:
00:45:49
he brings to the book, the way he brings out the story, I just I
Speaker:
00:45:52
really enjoy. So that's a fun it's a really fun listen. And
Speaker:
00:45:55
then on the nonfiction side, my favorite management book of
Speaker:
00:45:59
all time is Turn the Ship Around by, admiral David Marche. It's about
Speaker:
00:46:03
a captain of a a nuclear submarine that sort of uses the same kind of
Speaker:
00:46:07
things we've been talking about to to turn around the performance of The
Speaker:
00:46:10
previously worst performing boat in the fleet. So kinda bucking
Speaker:
00:46:13
military hierarchical management traditions for for something that
Speaker:
00:46:17
gives the people on the boat more autonomy and ownership over over the thing that
Speaker:
00:46:21
they're in charge of on on the boat into some pretty spectacular results.
Speaker:
00:46:24
Nice. And it's it's very narrative, so it doesn't read like a business book. It's
Speaker:
00:46:28
a great audiobook listen. Yeah. Cool. Interesting.
Speaker:
00:46:32
So, if you go to the data driven book.com, you will get 1 free audiobook
Speaker:
00:46:36
on us, and then we get, Maybe enough to
Speaker:
00:46:39
get a a nice cup of blueberry pie. One of those blueberry pack office. I
Speaker:
00:46:43
was thinking the same thing if you sign up. If you sign up,
Speaker:
00:46:47
health support to show helps us, kinda grow, and we're already
Speaker:
00:46:50
in season 7, but we're recording us before season 7 launch. So hello,
Speaker:
00:46:54
future people. And then
Speaker:
00:46:58
finally, the final question is, where can
Speaker:
00:47:02
people learn more about you, Nick, and Sim?
Speaker:
00:47:06
So for me, all I've got a lot of blog posts and all of my
Speaker:
00:47:09
talks up at my personal website, nmeans.dev. And
Speaker:
00:47:12
then for Sim, you can visit our website sym0ps.com.
Speaker:
00:47:17
Sign up for a free tile trial, kick the tires. We'd love to get
Speaker:
00:47:21
feedback on it. So if any of your listeners try it, have questions about it,
Speaker:
00:47:25
feel free to to reach out to me or anybody at Sym. We'd love to
Speaker:
00:47:27
help you kinda get started on the platform. Excellent. Well, thank
Speaker:
00:47:31
you very much. Any parting words, Andy? No. I'm just really sorry
Speaker:
00:47:35
now after listening to the 2 answers that referred To the beginning of the
Speaker:
00:47:39
show. I'm really sorry I missed that. I'm gonna have to wait. Well, we can
Speaker:
00:47:41
use that that that machine from Spaceballs. You can go
Speaker:
00:47:45
back And then redo it so future Andy
Speaker:
00:47:49
will know how it all turned out.
Speaker:
00:47:52
Perfect. Perfect. I think Nick knows that we we, you know,
Speaker:
00:47:56
we we do a lot we do at lee there always ends up being at
Speaker:
00:47:59
least 1 movie reference, so we got that. Nice. Yeah.
Speaker:
00:48:03
Alright. Thank you, Nick. Any last thoughts? No. Thanks so much for having me on.
Speaker:
00:48:06
This has been a really fun conversation. Awesome. Thank you. We'll we'll let
Speaker:
00:48:10
Bailey finish the show. And that wraps up another
Speaker:
00:48:14
intriguing episode of data driven. We hope you
Speaker:
00:48:18
enjoyed our conversation with Nick Means, the VP of software
Speaker:
00:48:21
development at Sym. From exploring the concepts of
Speaker:
00:48:25
shame and vulnerability in the software industry Dri to diving into the
Speaker:
00:48:28
fascinating world of engineering disasters. This episode has been a
Speaker:
00:48:32
thought provoking journey. We delved into the importance of
Speaker:
00:48:36
being good stewards of data and the significance of compliance with
Speaker:
00:48:39
regulations, all while finding ways to balance security and
Speaker:
00:48:43
efficiency. As we wrap up, we encourage you to
Speaker:
00:48:46
reflect on the valuable insights and takeaways shared in this episode.
Speaker:
00:48:51
The path towards a blameless mindset, fostering stronger
Speaker:
00:48:54
organizational culture, and embracing the principles of little agile
Speaker:
00:48:58
are just some of the actionable steps we discussed.
Speaker:
00:49:02
Remember, mistakes happen, but it's how we learn from them and share
Speaker:
00:49:05
our experiences that truly makes a difference.
Speaker:
00:49:09
So let's continue to grow, adapt, and shape the software
Speaker:
00:49:13
industry into a more resilient space.
00:00:00
Welcome back, esteemed listener, to another episode of data
Speaker:
00:00:03
driven. In today's episode, we have the pleasure of delving into the mind
Speaker:
00:00:07
of Nicholas Means, the vice president of software development at
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00:00:11
SIM. With a keen intellect and a propensity for
Speaker:
00:00:14
weaving together multifaceted concepts, Nick touches upon the
Speaker:
00:00:18
enthralling topic of shame and its relevance in our ever evolving software
Speaker:
00:00:22
industry. Prepare yourself for we shall ponder the
Speaker:
00:00:26
intricate connection between shame, vulnerability, and the
Speaker:
00:00:29
cultural shifts within the software engineering landscape.
Speaker:
00:00:33
As we explore the depths of these subjects, Nick leaves us curious and
Speaker:
00:00:37
yearning for more recommending a podcast episode that unravels the
Speaker:
00:00:41
intricacies of this enthralling topic. Now on with
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00:00:44
the show.
Speaker:
00:00:50
Hello, and welcome to Data Driven, the podcast where we or the emerging fields of
Speaker:
00:00:53
data science, artificial intelligence, data
Speaker:
00:00:57
engineering, and occasionally, ever so occasionally,
Speaker:
00:01:01
IT operations and engineering. Today we welcome
Speaker:
00:01:05
Nicholas Means to the show. Nick is the VP of engineering at
Speaker:
00:01:09
STEM, Spelled s y m, not like the video game
Speaker:
00:01:12
kids, and it's an adaptive process tool built for
Speaker:
00:01:16
developers. He's been an engineering leader for more than a decade, focused
Speaker:
00:01:19
on helping teens build velocity through trust and autonomy.
Speaker:
00:01:24
He's also regular speakers at conferences around the world, teaching more
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00:01:27
effective software development practices through stories of real world engineering
Speaker:
00:01:32
triumphs And failures. Welcome to the show, Nick.
Speaker:
00:01:35
Thanks so much for having me on, Frank. Excited to be here. Yeah. Awesome.
Speaker:
00:01:39
You know, and And we were kinda talking in the virtual green room is that
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00:01:42
you're not really in the data space, but you are, I would say, dare I
Speaker:
00:01:46
say, distinguished software engineer, and There's a bunch of
Speaker:
00:01:49
us in the data space now that kinda started in this world, and and I
Speaker:
00:01:53
think one of the things that that, when your name came across my desk,
Speaker:
00:01:57
I was like, reading some papers lately about,
Speaker:
00:02:00
you know, technical debt in data systems.
Speaker:
00:02:04
Right? Mhmm. And I think that's kind of the big dirty secret,
Speaker:
00:02:08
and I think that there's a lot that we can learn from software engineering
Speaker:
00:02:12
practices, in this space as well.
Speaker:
00:02:16
Yeah. For sure. So what when you say autonomy,
Speaker:
00:02:20
you know, as an AI geek now, when I think autonomy, I think Something
Speaker:
00:02:24
completely different. Well, I'm I'm assuming you mean people
Speaker:
00:02:28
being autonomous from kinda that Dilbert type corner, you know, pointy haired boss
Speaker:
00:02:32
guy. Right? Yeah. Absolutely. So
Speaker:
00:02:35
you had a a pretty distinguishing
Speaker:
00:02:39
distinguished career. You probably have had worked for people like that, and probably
Speaker:
00:02:43
inspired you to kind of go in the other direction. Is that is that true?
Speaker:
00:02:47
That's part of it for sure. Yeah. I mean, I, You know, I I
Speaker:
00:02:51
think my my journey into engineering leadership kind of involved being
Speaker:
00:02:54
in, like, some locker room kind of cultures where the loudest voice won.
Speaker:
00:02:59
And and a lot of my motivation from shifting from writing code
Speaker:
00:03:02
to being on the other side of the business, being being a manager, Was
Speaker:
00:03:06
wondering if I could do better, wondering if I could could build teams that
Speaker:
00:03:10
functioned more humanely and actually empowered each other and and supported each
Speaker:
00:03:13
other in getting their work done. And the the last 10 years of my career
Speaker:
00:03:17
has kind of been a journey in that direction. So what was
Speaker:
00:03:20
that moment where you were like, I could do better?
Speaker:
00:03:25
Interestingly, it was an episode of the Ruby Rogues
Speaker:
00:03:28
podcast several several years ago, that that featured Alex Harms,
Speaker:
00:03:32
talking some about the work of Brene Brown, and shame
Speaker:
00:03:36
and vulnerability in the way that those concepts can inform the way that agile
Speaker:
00:03:40
teams communicate. And that was, like, when my eyes really kinda opened
Speaker:
00:03:44
to the idea that maybe the the thing that I was living through wasn't the
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00:03:47
only way to do this and that that it didn't have to be this hard.
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Interesting.
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00:03:56
What does that mean shame in terms of, I mean, you you mentioned kind of
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the the loudest voice in the room wins, the locker room mentality, kind of like,
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you know, you know, it's like we're we're chimps back
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00:04:07
in the savannah, Back mill 1000000 of years ago. Right? Like, we
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00:04:11
like like, is that is that obviously,
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00:04:15
obviously, at some point in history of The human species that might have worked,
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00:04:18
but I don't think in software where 90% of it involves kind of the
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00:04:22
prefrontal cortex, I think e I don't think that's gonna
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00:04:26
work, and What what was
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00:04:30
it about the Bray Brene Brown kinda concept of shame and vulnerability
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00:04:33
that kinda, like, made you Connect the dots because Brene Brown exists in
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00:04:37
kind of a different world than than your average, you know,
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00:04:41
software. I'd like to know more about that podcast episode. We'll have to link the
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00:04:44
to that episode That sounds interesting. Yeah. I mean, so for me, it
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00:04:48
so so part of it is that loudest voice always wins, but one of the
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effects that That almost always happens when you have one of those really loud
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voices in the room is that it tends to silence other voices.
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It tends to make People afraid to raise their hands, say I don't know, ask
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00:05:02
things that feel like obvious questions to them. And all that's kinda
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00:05:06
rooted in in shame And not wanting to be vulnerable and and not knowing
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00:05:10
something or or feeling shame that you don't know something that you think should be
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00:05:13
obvious to you. In reality, it's not. In reality, one of
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00:05:17
the things that that distinguishes the best senior individual
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00:05:21
contributors is willingness to say, I don't know, willingness to ask Questions when
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00:05:24
something comes up in in a discussion that they don't know about, but it takes
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00:05:28
a long time in your career to kinda build yourself up to that
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00:05:31
point of confidence. We're saying I don't know is an easy thing for you to
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00:05:34
do, unless you're in an environment that's that has high psychological
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00:05:38
safety and where those questions are invited And and where the the
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00:05:41
environment is very much set up to be oriented around growth and around making sure
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00:05:45
that everybody is able to ask Those questions able to push back on
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00:05:49
each other when they don't necessarily agree with the the direction something's taking.
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Not in a allowed chest thumping kind of way, but more in a,
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Let's talk about this. I I don't know that that's the best way to proceed,
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00:05:59
but maybe there's something about your position that I'm missing and just that that sort
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00:06:02
of curiosity. Interesting. How does
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00:06:06
the how does shame relate to imposter syndrome?
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00:06:10
Interestingly enough, my very first conference that I ever did was on
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00:06:14
impostor syndrome, and that this was kinda this line of thinking is kinda what sent
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00:06:17
me down that road and made me realize that was a thing that I was
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00:06:20
dealing with. It's it it very much relates to it. Very
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00:06:23
much the idea that it it's hard as a software engineer to
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00:06:27
kinda get perspective on how Good or bad, you are as a software engineer. You're
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00:06:30
really dependent on other people's feedback to do that. And that's
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00:06:34
one of the key components of impostor syndrome is anytime you're in a
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00:06:38
career Where something is subjectively judged, which code
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00:06:42
quality subjectively judged. There's there's rules. There's best practices.
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We don't agree on the rules and best practices, So that puts us squarely in
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00:06:49
in the subjective side of the house. So it's really no different than than being
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a professional musician or a ballerina or something like that.
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00:06:56
You're being judged by the the quality of your work output, but it's a subjective
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set of standards. And people in fields that are judged by subjective
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00:07:03
standards are especially prone to impostor syndrome. Really? I
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00:07:07
did not know that because, I I mean, it may make sense as you explain
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00:07:11
it that way, because if you're a civil engineer. Right? The bridge is
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00:07:15
either gonna stand up or it's not. Right? It's gonna shake too much
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00:07:18
or it's not. Right? The wind, like, the Tacoma Narrows Bridge, right, the
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00:07:22
wind's gonna hit the wrong way, Something's bad is gonna happen, or it doesn't. It's
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00:07:25
it's it's a very real world thing. I I I've often kind of
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00:07:29
wondered as software engineers, or even this applies to data
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00:07:33
people too. Right? What we deal with is so abstract. Mhmm.
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You know, that it is hard to kind of gauge that, and and I
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00:07:41
I can't be the only one that thinks that Because it's subjective,
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00:07:45
organizational politics plays a huge role
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00:07:49
in how someone's judged. I'll share a story. I used to work at this
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00:07:52
consulting firm. Actually, it's back when I met Andy, who's not here
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00:07:56
today. But, This guy wrote
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00:08:00
the most awful code. I don't wanna say his name for, you know,
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00:08:03
lawsuit reasons, but his last name and the word code became a
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00:08:07
synonym for garbage code. Right. But he was such a
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00:08:10
politician. He would walk around, and, like, everyone loved this guy. No one wanted to
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00:08:14
call him out on it even though he Wrote the most god
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00:08:18
awful bits of code. Yeah. And and that was when you
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00:08:22
know, I I wouldn't say it was an moment, but I was like I
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00:08:25
was like, oh, he should be selling used cars. He should be kept away from
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00:08:29
a keyboard. You know what I mean? Yeah. Yeah. Yeah. I mean, that gets into,
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00:08:32
like, the Dunning Kruger effect, right, where Where the people the people that
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00:08:36
often feel the worst at their job feel that way because they know what bits
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00:08:40
of knowledge they're missing, and the people that feel the best at their job feel
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00:08:43
that way because they have no idea what knowledge they're missing. They they just feel
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00:08:47
very confident in the things that they do know, and they're not worried about the
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00:08:49
rest of it. So it's sort of this idea that the more intelligent you
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00:08:53
are the more you're gonna struggle with this stuff. Interesting. It's almost like,
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00:08:57
the self reflection kind of Guess in the same recursive into
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00:09:01
infinite loop and you kind of lose sight of it. Yeah. And
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00:09:04
if you and if you do, if you are completely oblivious,
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00:09:09
You're unaware. It's it's kind of like a a a cruel trick the mind plays.
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00:09:13
Yeah. Absolutely. Interesting. So
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00:09:18
How did you we were talking about physical
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00:09:22
engine, engineering and things like that, like, what
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00:09:25
obviously, you know,
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00:09:29
a bridge falling down that happens. Right? What what can we learn
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00:09:33
because it's subjective, it probably I don't I never say never
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00:09:37
as a policy, usually. See I even qualify
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00:09:40
that. What can we learn from
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00:09:44
real I hate this this was always a thing because there's always,
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00:09:48
like, there's real engineers. Right? Like, the people who build stuff and but I mean,
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00:09:51
like, what can we learn from physical, engineering disciplines? Right?
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00:09:55
Because this this has come up before, I I can imagine,
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00:09:58
and What what can we learn from them? So the
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00:10:02
fascinating thing about that is the the lessons that there are to learn in
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00:10:06
physical engineering disasters are all still based in the human side of it
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00:10:09
Because even though steel is steel is steel, and it behaves according to a set
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00:10:12
of physical rules that we know, the people that work with steel still
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00:10:16
make mistakes in how that steel is gonna behave. I've
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00:10:20
done, you know, I've done a series of talks kind of on on connecting real
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00:10:24
world engineering disasters to the software world. One of them
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00:10:27
that the the steel metaphor brings to mind is the one I did on City
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00:10:30
Corp Center in New York, which is the building that's sort of
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00:10:34
built on stilts. It's It's built up on 4 legs. The legs are actually on
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00:10:37
the the sides of the building, not in the corners, and that created some wind
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00:10:40
loads that weren't accounted for in the original design. And then when it was actually
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00:10:44
being erected, they changed the way that they fastened the
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00:10:48
structural members together, thinking that the the original
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00:10:51
designer structure had overprovisioned them, and that they didn't need that amount of string. They
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00:10:55
could just do rivets and stuff, or they could do bolts instead of rivets. And
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00:10:58
it turned out that it would've it was vulnerable to a 100 year storm, and
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00:11:01
a 100 year storm could have actually blown that building over. And so it's
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00:11:05
the the story kinda gets into Fill the Measure, the the engineer
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00:11:09
that designed it, Basically raising his hand and going, hey, I
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00:11:12
figured this thing out. Thanks to a comment from an engineering
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00:11:16
student. We have to fix this building and, like like, sort of the
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00:11:20
process of talking about what happened
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00:11:23
himself, talking about the mistakes he had made in the design,
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00:11:27
bringing it to the attention of people that could then do something about it. In
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00:11:30
this case, the people that own the building, Citicorp, who financed
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00:11:34
the work, who worked with insurance companies. The whole thing
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00:11:38
is a story of, When you make a mistake, it's better to
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00:11:42
raise your hand early than try to sweep it under the rug and try to
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00:11:44
cover it up, because you'll end up making a bigger mess in in the process,
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00:11:47
and the consequences usually aren't what you've built them up to be in your head.
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00:11:50
So that's that's sort of an example that that kinda gets into the human side.
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00:11:55
No. That's awesome. Like, there are there are things in my life that I if
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00:11:58
I had learned that lesson sooner, would have been a lot easier. I I think
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00:12:02
that's true for all of us, and that's one of the reasons that I I
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00:12:05
find I mean, I'm I honestly, I kinda came into this line of of
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00:12:08
conference speaking because I like to read about disasters a
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00:12:12
lot. I I watch way too much Seconds from Disaster as a kid, and I've
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00:12:14
always been infatuated with this stuff. And it's it's sort of a way for me
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00:12:18
to Justify taking a really deep dive and learning a lot about
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00:12:22
one of these things and getting something productive out at the other end of it
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00:12:25
versus it just being a long Wikipedia Safari for its own sake.
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00:12:29
But I but I you know, there's I think there's a lot that we can
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00:12:33
learn from people that have been doing engineering longer than us because the the
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00:12:37
human factors The the communication between people working
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00:12:41
is still a a thing that existed in the physical engineering world, and that's been
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00:12:45
going on far longer than we've been building software for computers. So there's absolutely things
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00:12:48
that we can learn from those disciplines. Interesting. And in
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00:12:52
regards to the Citibank building thing, I remember seeing something in the History Channel about
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00:12:55
those. Apparently, like, overnight, like, they had
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00:12:59
crews working in the middle of the night. And then is it true? I don't
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00:13:02
remember all the details, but is it true they largely kept a hush-hush? Mhmm.
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00:13:06
Yeah. They did. They would go in, and and they would build these welding shacks
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00:13:09
around the the places where they needed to weld inside the building because all of
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00:13:12
the all the cross members were exposed inside the building, and it just been drywalled
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00:13:16
around them. So they would go in and build a little plywood shack, and knock
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00:13:19
the drywall off, and and weld it. And there's pictures of the building where you
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00:13:22
can see it lit up in the night with somebody welding on one of these
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00:13:25
structural members. Wow. They didn't tell people what was what was
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00:13:28
going on. It came very close to needing to order an evacuation because of a
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00:13:32
tropical storm that was headed towards New York, and the storm ended up turning away
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00:13:35
at Last minute. Wow. Wow. I do
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00:13:39
remember the part about that 100 year storm was, basically,
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00:13:46
almost happened. Yeah. Alright. Here's Andy.
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00:13:50
And in all of our years of podcasting, it's the first time he has,
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00:13:54
shown up late, so, kudos for him.
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00:13:58
I will I will I will either leave this edit raw,
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00:14:02
or, Or, kind of
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00:14:05
include it, with the, the thing. So I'll
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00:14:09
I'll I'll clue Andy in. Nick Means is the VP of software develop
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00:14:13
this I will edit out. VP of software development at a place called
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00:14:16
SIM, and he has connected,
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00:14:22
he's done a lot of personal research out of his interest
Speaker:
00:14:25
in, disasters, and how those
Speaker:
00:14:29
lessons can be learned, in software engineering, where
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00:14:32
software engineering, he can I can I can tell if I'm
Speaker:
00:14:36
paying attention, is that, you know, it's largely been this, you know, who
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00:14:40
who can Pump their chest, the loudest type thing? And
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00:14:43
it's not really been the there's a certain pecking order
Speaker:
00:14:47
that May have worked in ancient times, but works
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00:14:50
terrible in software engineering. Is that about right? Yep.
Speaker:
00:14:54
Cool. Oh, wow. Okay. I'm gonna have to listen to the first part of this.
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00:14:59
This reminds me of Spaceballs. This, like, Spaceballs. Let's go
Speaker:
00:15:03
to the instant machine own video. When will
Speaker:
00:15:07
then be now? Now. Just now. What is this?
Speaker:
00:15:11
This is now.
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00:15:15
Well, what happened? Classic.
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00:15:20
Never play that part again.
Speaker:
00:15:25
Alright. So now that we were on I'm sorry. What? I was gonna say it's
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00:15:28
nice to meet you, Nick. And, You as well. Yeah. Yeah. Sorry Sorry,
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00:15:32
I was late. I've it's a great problem as a consultant to
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00:15:36
have being double booked and stuff, and usually, we're able to work this out,
Speaker:
00:15:40
but, I am experiencing too much
Speaker:
00:15:43
business. Again, great problem to have. Still a problem. Yeah. Great
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00:15:47
problem. Especially right now, it's a great problem. Right? Yeah. Yeah.
Speaker:
00:15:50
So I'm very, very thankful and grateful for that. But, I know
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00:15:54
Frank Frank did a wonderful job, and I'll just, I'll hush now,
Speaker:
00:15:58
and, we can get on with the show. Alright.
Speaker:
00:16:02
So we were talking, so so that's interesting. So
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00:16:06
With software engineering, with with buildings and physical
Speaker:
00:16:10
things. Right? You know, the nuclear reactor can melt down. Right? The, The,
Speaker:
00:16:14
bridge can collapse, the Citibank building could almost tip over.
Speaker:
00:16:19
With software engineering, you got a lot of other problems too. Right? I mean,
Speaker:
00:16:23
Security breaches Mhmm. Come to mind. And and
Speaker:
00:16:29
in your in your, kinda, your your sheet, like, You mentioned something
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00:16:32
called a blameless mindset. What what is a blameless mindset?
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00:16:37
So, I mean, it's really the the orientation that anytime something happens, your
Speaker:
00:16:41
primary goal should be to learn from that thing, not to figure out whose fault
Speaker:
00:16:44
it is. It kinda gets into, if if you if you've done any
Speaker:
00:16:47
research into, like, safety 2 or or human factors. It gets into the work
Speaker:
00:16:51
of Sydney Decker and and what he calls forward accountability.
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00:16:55
Kind kind of the idea is that nobody comes to work intending to do a
Speaker:
00:16:59
bad job. And if if they make a mistake that causes an outage
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00:17:03
or causes a security breach, They probably already feel
Speaker:
00:17:06
pretty bad about it and don't really need you piling on most of the time
Speaker:
00:17:10
to learn their lesson. What they do need is a chance to tell their
Speaker:
00:17:13
story, so that they can kind of put the facts together
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00:17:17
in their own mind. They can help other people learn from from what they just
Speaker:
00:17:20
did. And that that kinda gets into when
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00:17:24
when something happens. It's often very tempting,
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00:17:27
especially for for us pointy head pointy head boss types To point
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00:17:31
the finger and and to find somebody on whose head the the blame for
Speaker:
00:17:35
this thing lays. But when you do that, when you focus on
Speaker:
00:17:38
establishing blame as as a primary Goal in one of these situations,
Speaker:
00:17:43
you prevent people from learning, and you prevent people from raising their hand when it
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00:17:46
happens. You encourage people to sweep it under the rug. Kinda what we're talking about.
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00:17:50
It's it's the thing if Phil Meacher had done this with Citicorp Center. Citicorp Center
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00:17:53
probably would have fallen over at some point. And so having a
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00:17:56
blameless mindset when something goes wrong encourages people to raise their
Speaker:
00:18:00
hand sooner, bring other people in on the solution, Let the whole organization
Speaker:
00:18:04
learn from the the mistake that they just made. And and, you know, it's kinda
Speaker:
00:18:08
rooted in a systems thinking mindset as well. You know, how can we Change the
Speaker:
00:18:11
system so that a a mistake that's shaped like this is more difficult to
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00:18:15
make in the future. So here's a random question.
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00:18:20
I noticed that GitHub has something called the blame tool. I think it's part of
Speaker:
00:18:23
Git. Mhmm. Is that is that a tongue in cheek
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00:18:27
reference, or is that actually, Like, actually a
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00:18:30
blame. Like, what are your thought? Well, I don't know the history of that,
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00:18:34
so maybe maybe you could tell me. And then Yeah. I mean, it it is
Speaker:
00:18:38
from Git Self not from GitHub. It's something that just showed up in the in
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00:18:41
the GitHub UI from from Git. I actually, on my own system, alias
Speaker:
00:18:45
it to get credit, so I don't have to type git blame. Oh, I like
Speaker:
00:18:48
that. Oh, that's awesome. And that's
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00:18:52
I I it's definitely not my original idea. I know a lot of people that
Speaker:
00:18:55
do that as well, just because Get blame puts you in
Speaker:
00:18:59
sort of a certain frame of mind when you're reading code, and it's often not
Speaker:
00:19:02
a helpful or charitable frame of mind. Whereas get credit is more like,
Speaker:
00:19:06
okay. Who can I ask to hear this story of of why this line code
Speaker:
00:19:09
came to be? Yeah. That was because that
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00:19:13
yeah. When you mentioned blameless mindset, and I was like but, I mean, I guess
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00:19:17
that speaks to kinda, like, you know, like, you know, the origin story
Speaker:
00:19:20
of Git, I guess, Blame the blame tool or I don't I
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00:19:24
don't know. Like, it just to me, it just seemed like there's gotta be more
Speaker:
00:19:27
to that story. Yeah. And when I first heard the tool, The guy I was
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00:19:30
working with, he thought it was funny. Oh, they have a blame tool, so you
Speaker:
00:19:33
can always know who's to blame. And I was like I was like, that's kinda
Speaker:
00:19:37
mean, actually, you know. A little bit. A little bit. I mean and again, you
Speaker:
00:19:41
know, it gets into, like, the the prime directive of retrospectives if you've done spent
Speaker:
00:19:44
any time in the Agile world. This idea that everybody was doing the best that
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00:19:47
they could at the time that they did it and made the best decision they
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00:19:50
could with the information they had. Right.
Speaker:
00:19:53
What's interesting in as you see those That
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00:19:58
agile processes kind of happen, right? There's there's
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00:20:02
the theory, and then there's the practice. Mhmm. And
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00:20:05
Its organizational culture tends to take all the
Speaker:
00:20:09
oxygen out of that room. Yeah. You know and and you're not
Speaker:
00:20:13
surprised so I guess that's that's a thing You know? I
Speaker:
00:20:16
I I like to and I forget who coined this distinction. It may
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00:20:20
have been kept back, the idea of big a agile versus little a agile.
Speaker:
00:20:24
Yes. Big Agile, the idea that there's all all these off the
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00:20:28
shelf methodologies that you can just pick up off the shelf and adopt in your
Speaker:
00:20:31
organization, and and suddenly the the heavens will part and will sound and you will
Speaker:
00:20:35
be more agile. You look at something like SAFe, the
Speaker:
00:20:38
scaled agile framework, and you can pretty clearly see that that's not the case. It's
Speaker:
00:20:42
just Waterfall in disguise at the organizational level.
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00:20:46
Whereas more more little a agile is the actual principles, the
Speaker:
00:20:49
spirit of Of sort of the agile software movement where it is more
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00:20:53
autonomous. It is more short planning cycles, getting feedback early,
Speaker:
00:20:57
shipping in small increments, that sort of thing. And it's really easy to pick up
Speaker:
00:21:00
an off the shelf agile methodology and not do any of that stuff.
Speaker:
00:21:04
Right. I I remember hearing an interview once, a podcast,
Speaker:
00:21:08
probably a decade ago where, someone referred
Speaker:
00:21:11
to their, their software development life cycle
Speaker:
00:21:15
as Scrum Bud. Mhmm. And so when we're doing
Speaker:
00:21:19
scrum, but and then, you know, something followed that wasn't
Speaker:
00:21:22
scrum. And it sounds a lot like what you're describing. Yep.
Speaker:
00:21:26
Absolutely. Yeah. One of the reasons I I tend to be more with my teams,
Speaker:
00:21:30
more Kanban inspired than Scrum inspired. And and the reason for that
Speaker:
00:21:33
is Because I've seen too many teams try to win the
Speaker:
00:21:37
sprint, and and it sort of creates this perverse incentive to just
Speaker:
00:21:41
get code across the line no matter what it takes. Yeah. I I like
Speaker:
00:21:45
the community aspect of Kanban, the swarming, and Mhmm. You know, I've
Speaker:
00:21:48
seen that work. I I actually learned that on a real live plant
Speaker:
00:21:52
floor. So, you know, I've got I I used to joke with
Speaker:
00:21:56
Frank that I've got about 8 more years of books I can write,
Speaker:
00:21:59
process engineering because I know where they're going. Yeah. And, you know,
Speaker:
00:22:03
and and what's interesting is we've reached that phase where I was in
Speaker:
00:22:06
manufacturing in the late, nineties, And we reached that
Speaker:
00:22:10
phase where we learned where it wouldn't work. Mhmm. For
Speaker:
00:22:13
instance, it didn't work in engineering.
Speaker:
00:22:17
So it's interesting that we're kinda getting to that maturity. I guess that
Speaker:
00:22:21
maturity would be a good description of it, where we're seeing in the context,
Speaker:
00:22:25
Especially if software engineering that is falling over some.
Speaker:
00:22:29
Mhmm. It works really, really well on the plant floor Mhmm. When you're
Speaker:
00:22:32
in a manufacturing environment, that quality goes through the roof.
Speaker:
00:22:36
Deming's methodologies are phenomenal. The,
Speaker:
00:22:41
And maybe you've already covered this, but the culture wherein a lot
Speaker:
00:22:44
of that, you know, from the manufacturing perspective was developed,
Speaker:
00:22:48
is a vastly different culture than we have today in the United States.
Speaker:
00:22:52
It wasn't even I mean, it was Japan. Right. You know? Coming
Speaker:
00:22:56
out of post World War 2, and That's that is a
Speaker:
00:23:00
different place. Mhmm. It's probably different than Japan today. I'm
Speaker:
00:23:03
sure it is. Yeah. You know? So That that has a lot to do with
Speaker:
00:23:07
it, and you did, I heard I heard the screed behind the
Speaker:
00:23:11
words about corporate culture. That's that's a huge driver.
Speaker:
00:23:15
Mhmm. It it just is. Alright. I'll show up. It's and it's, you know,
Speaker:
00:23:19
it's it's not it's really not any different than than what we're talking about about
Speaker:
00:23:22
off shelf agile methodologies. Right? Like, all of these things are tool are toolboxes.
Speaker:
00:23:26
There's useful things in all of them, and there's things that don't apply and don't
Speaker:
00:23:29
work On an organization by organization, team by team basis.
Speaker:
00:23:33
Absolutely. And the trick is you have to be able to have all of these
Speaker:
00:23:35
tools in your toolbox and then go up to a team and go, oh,
Speaker:
00:23:40
I know this shape problem, and I these are the things that we can try
Speaker:
00:23:43
that that will help make this better. Right. Right.
Speaker:
00:23:47
What's your, sorry, Anya cut your head. Go ahead. Go
Speaker:
00:23:51
ahead. How do how does, how
Speaker:
00:23:54
does a software engineering team
Speaker:
00:23:58
Change or leadership within software engineering change the the
Speaker:
00:24:02
the organizational culture, Because I think that's a
Speaker:
00:24:05
big problem. I think that software is eating the
Speaker:
00:24:09
world. I think that was a Mark Zuckerberg quote, and I think that, yeah,
Speaker:
00:24:13
Definitely since ChatGPT, I would say AI is
Speaker:
00:24:17
eating the world. Right? But but ultimately, I'm old enough to
Speaker:
00:24:21
remember when software people were those weird people that they they stuffed us in the
Speaker:
00:24:24
basement Mhmm. And did not wanna hear anything from us
Speaker:
00:24:29
Other than everything's working fine, everything's fine, they certainly
Speaker:
00:24:32
did not wanna hear, management philosophy of,
Speaker:
00:24:37
stump speeches from us. I imagine that's changed
Speaker:
00:24:41
a little, but how does how does
Speaker:
00:24:45
someone who's listening to this Wants to affect chains, wants to
Speaker:
00:24:48
kinda bring that blameless mindset into their organization. How do they
Speaker:
00:24:52
start? I know that's probably, like, a 3 hour talk,
Speaker:
00:24:56
but Where would they how
Speaker:
00:25:00
would they what's the first step? Yeah. I mean, what what a great
Speaker:
00:25:03
question. You know, I think step
Speaker:
00:25:07
1 is just learning and and kind of figuring out where this information
Speaker:
00:25:10
exists. So, like, reading some of the blog posts from John Alsbaugh when
Speaker:
00:25:14
he was When he was CTO at Etsy, reading some of the work
Speaker:
00:25:18
of Sydney Decker, that he's done on safety 2. I mean,
Speaker:
00:25:22
John John Osborn is still out on the speaking circuit doing talks a regular basis.
Speaker:
00:25:25
So there's there's plenty of material to learn from out there. I think it's
Speaker:
00:25:29
it's probably most at home in the SRE community right now.
Speaker:
00:25:33
That's that's where I see a lot of safety cultures and human factors research coming
Speaker:
00:25:37
out as in NSRE at the moment. It was it's still in the dev ops
Speaker:
00:25:40
movement as well. That's kinda where I got acquainted with it. So step
Speaker:
00:25:44
1's kind of learning and then just teaching, giving people the
Speaker:
00:25:47
opportunity to realize that There is a different way that some of the stuff can
Speaker:
00:25:51
be done. You know, as far as an engineering leader being able
Speaker:
00:25:55
to affect larger change in an in an organization, The
Speaker:
00:25:58
one advantage that an engineering leader has is that software
Speaker:
00:26:02
engineering salaries are usually one of an organization's biggest cost centers.
Speaker:
00:26:06
And so it's pretty easy to make a case that optimizations there will
Speaker:
00:26:10
pay off if you can make a A persuasive
Speaker:
00:26:14
case for the optimizations that you wanna make. And that's where some of the things
Speaker:
00:26:17
like getting into manufacturing theory and queuing theory and
Speaker:
00:26:21
systems thinking and being able to put together a very data driven
Speaker:
00:26:25
kind of case around some of the improvements that you're trying to affect and the
Speaker:
00:26:28
ways that you're trying to affect them. It it's funny. One
Speaker:
00:26:31
of one of the most common interventions that I found myself making over and over
Speaker:
00:26:35
again with engineering teams is putting WIP limits in place. Just
Speaker:
00:26:39
because when an engineering team is trying to work on too many things at the
Speaker:
00:26:42
same time, they end up spending so much of their time on context
Speaker:
00:26:46
shifting And and trying to load up new contexts and pick up a
Speaker:
00:26:49
project that's completely different than the one that they're currently working on so they can
Speaker:
00:26:52
provide effective code review, that sort of thing. And it's pretty
Speaker:
00:26:56
easy to kinda talk through the data of if we work on less,
Speaker:
00:27:00
we can get more done, but it's really counterintuitive on the
Speaker:
00:27:03
surface when you first hear that statement. Well, the whole drive
Speaker:
00:27:07
towards parallelism. Mhmm. You know, from a machine level right
Speaker:
00:27:11
through you know, it bleeds through. They're all leaky abstractions to throw out some
Speaker:
00:27:15
other Yep. Terms. But, you know, that that whole idea that if you
Speaker:
00:27:18
do things in parallel, you're gonna be able to accomplish more. And I've
Speaker:
00:27:22
seen, I'm gonna I can't remember the book. I was reading
Speaker:
00:27:26
reading a book by someone. It was maybe 2, 3, 4 years old,
Speaker:
00:27:30
and He was talking about just the exact opposite, and he had use
Speaker:
00:27:33
cases and it just you know, serialize it, and
Speaker:
00:27:37
you'll get more done. And it it it's exactly that context
Speaker:
00:27:41
You eliminate that. Human brains stink at constant
Speaker:
00:27:45
context switching. Awful at it. Yeah. Yeah. So
Speaker:
00:27:49
Great. Great point. Interesting.
Speaker:
00:27:52
So another thing that you you kinda
Speaker:
00:27:56
Mention is talking about compliance. Mhmm. And before everyone
Speaker:
00:28:00
kind of tunes off, turns off the the thing and stops,
Speaker:
00:28:06
stops listening. Bear with me. There's a point here, and I think it's
Speaker:
00:28:09
important. No one gets excited about compliance. I I know I know
Speaker:
00:28:13
that. My wife works in IT security compliance. No
Speaker:
00:28:17
one's happy to see her. I'm I'm happy to see her, but no one at
Speaker:
00:28:20
her job is happy to see her. Dear Roberta, you'll never
Speaker:
00:28:25
Alexa, order some flowers. The,
Speaker:
00:28:30
but With the rise of software
Speaker:
00:28:33
being more and more important, more critical to our, I was talking to somebody
Speaker:
00:28:37
else. It might have been in a preview, The another guest on
Speaker:
00:28:40
another completely random topic. I think
Speaker:
00:28:44
regulation is coming to the software industry whether we like
Speaker:
00:28:48
it or not, Because of its core kind
Speaker:
00:28:52
of nature to our, just economy and infrastructure. Mhmm. And I think that
Speaker:
00:28:56
compliance is gonna be one of those things where, You know, learn
Speaker:
00:29:00
it or, you know, learn it, love it, or, you know, leave the
Speaker:
00:29:03
industry. Yeah. Yeah. And and, Yeah. I'm
Speaker:
00:29:07
sorry. So so, like, how do you how does that it seems like
Speaker:
00:29:11
that would kinda dovetail into this. Right? The the the Learning from
Speaker:
00:29:14
mistakes and and meeting these compliance. I mean, certainly, we see it
Speaker:
00:29:18
in data and various data compliance schemes, but but how does he think this is
Speaker:
00:29:23
How does this gonna affect kind of software? Yeah. I mean, the the first thing
Speaker:
00:29:26
I was gonna say is you can you can already see some of this in
Speaker:
00:29:29
things like GDPR and the California privacy regulations, The the stuff the White
Speaker:
00:29:32
House has been doing lately on software bill of materials, we're starting to see it
Speaker:
00:29:36
kind of creep in in in the in the periphery of the things that we
Speaker:
00:29:39
work on. You know, it's
Speaker:
00:29:42
it's tempting to just look at it and go, this is dumb. This will never
Speaker:
00:29:46
work. It's not gonna make any difference. But there's a there's a There's a more
Speaker:
00:29:50
terrible way to look at it in that it's pointing at a thing that
Speaker:
00:29:53
actually is really important. You know, to to your point, s soft
Speaker:
00:29:57
reads the world as organizations hold on to more and more and more and more
Speaker:
00:30:00
data. That data's a liability, and
Speaker:
00:30:05
If if we're not taking steps to make sure that, a, we're only
Speaker:
00:30:09
holding the data we actually need to hold, and, b, we're doing it as
Speaker:
00:30:13
carefully as we can. We're putting as many walls around it as we can, and
Speaker:
00:30:16
still be able to do our job on on an ongoing basis.
Speaker:
00:30:21
You sort of have to put that responsibility hat on and and think about
Speaker:
00:30:25
it in terms of how can I be a good steward of the data
Speaker:
00:30:28
that people have entrusted to me in in this organization that our customers have given
Speaker:
00:30:32
us? Yeah. And and in that that perspective, when you're looking at it
Speaker:
00:30:36
from the Spirit of law versus the letter of the law. It makes some of
Speaker:
00:30:39
the controls that you need to put in place for some of these compliance regimes
Speaker:
00:30:42
a little bit easier to swallow, And it also gets you into sort
Speaker:
00:30:46
of a an outcome mindset because, you know,
Speaker:
00:30:49
it's really easy to go through and and comply with some of these regulations with
Speaker:
00:30:52
checkboxes. Just do the things they say and and not really
Speaker:
00:30:56
actually make any difference in the overall security of your organization.
Speaker:
00:31:00
But if you look at it from a perspective, this is actually a And and
Speaker:
00:31:03
we should actually be doing this, then you can go about it and put
Speaker:
00:31:06
meaningful controls in place that that don't make it harder to get work done.
Speaker:
00:31:10
They just make it safer to get work And that's ultimately that's ultimately the goal.
Speaker:
00:31:14
That's I mean, that's what we're working on at Sym. It's sort of the whole
Speaker:
00:31:16
point of the product. Yeah. It's a good segue. So
Speaker:
00:31:20
what is Sym? SYM. Not the
Speaker:
00:31:23
Sims. I'm sure that's not I know that's not the first
Speaker:
00:31:27
time you heard the joke today, but, You know? So It's it
Speaker:
00:31:31
is not the 1st time I've heard that joke for sure. What what is what
Speaker:
00:31:35
is Sym do? Like, what What
Speaker:
00:31:38
is the the product? It it's essentially at its core workflow
Speaker:
00:31:42
engine. It allows you to build simple workflows to
Speaker:
00:31:45
request and Orchestrate access to to
Speaker:
00:31:49
production systems. It's probably easiest to explain by just telling you
Speaker:
00:31:52
how we use the product at SEM. We have all of our production infrastructure behind
Speaker:
00:31:56
our own product. So when one of our engineers needs access to
Speaker:
00:32:00
a production system, they just they create a request in Slack, and
Speaker:
00:32:03
then anybody else on the engineering team can approve that request. So kind of a
Speaker:
00:32:07
a 2 keys to launch the rocket approach. And then in the back end,
Speaker:
00:32:11
there's some code that runs in AWS. We assume a role An
Speaker:
00:32:14
AWS that lets us escalate somebody into that
Speaker:
00:32:18
administrator access role or whatever permission set that they've requested
Speaker:
00:32:22
so they can go in and do their job. And then an hour later or
Speaker:
00:32:25
or 4 hours later, whatever time interval they've requested, that access expires.
Speaker:
00:32:29
So you don't end up over time accumulating that janitor's key ring of System access
Speaker:
00:32:33
that you don't actually need on a daily basis. Right.
Speaker:
00:32:37
That's cool. That is interesting.
Speaker:
00:32:41
Now and it it you said something, a a a little bit ago that
Speaker:
00:32:44
I thought was might have sound blasphemous to some of our listeners. Right?
Speaker:
00:32:48
The data is a liability. Yeah. But the more, like, you kinda unpack it,
Speaker:
00:32:52
oh, yeah, I mean, you're right. Like, you know, we're so conditioned to think of
Speaker:
00:32:56
data as an asset, and and asset only. Right?
Speaker:
00:32:59
That I think we will lose sight of reality. Right? Or the
Speaker:
00:33:03
risks of holding data. Right? And I was just thinking, like, you know, if I
Speaker:
00:33:06
had a company, and I had, let's just say, some kind of PII. Mhmm.
Speaker:
00:33:10
Right? And I, after so many
Speaker:
00:33:13
months, or once I'm done doing what I'm doing, I purge it. Right?
Speaker:
00:33:18
I probably would sleep better at night if if I heard,
Speaker:
00:33:22
about, like, there's a there's a breach or anything like that. Right? Like, it's kind
Speaker:
00:33:26
of like, I think I think that there's a, for lack of better term, data
Speaker:
00:33:29
hoarding happening in a lot of organizations. Yeah. And I understand it,
Speaker:
00:33:33
right, because there's this If we've been so conditioned to think data
Speaker:
00:33:37
is only an asset, right? Oh, well, why
Speaker:
00:33:40
not just store it? Store it is cheap, you know? Right? But if
Speaker:
00:33:44
you also think that it can also be a liability,
Speaker:
00:33:48
and obviously not all data types are created equal. Right. Yeah. Of course. And not
Speaker:
00:33:51
all liabilities are created equal. Mhmm. Then that becomes a pretty cold
Speaker:
00:33:55
calculation of, well, yeah, maybe we'll figure
Speaker:
00:33:58
out, you know, if they have an even or odd social security
Speaker:
00:34:01
number. If that means that they're more likely to buy our
Speaker:
00:34:05
product. Yeah. But I don't wanna even hold that stuff anymore. Right? Or
Speaker:
00:34:09
I'll collapse it into, you know, Flag 1, flag 2 based on
Speaker:
00:34:13
that. Right? So, you you know, I I I like that. I hadn't
Speaker:
00:34:16
really thought about that. Yeah. I mean, one of the interesting use cases, you know,
Speaker:
00:34:20
if you think of health care data, there's some of that that you have to
Speaker:
00:34:22
hold. Right. But HIPAA is pretty strict about who can access it and when they
Speaker:
00:34:26
can access it. So one of the workflows that we've seen set up is
Speaker:
00:34:29
is requesting approval to access a particular patient's
Speaker:
00:34:33
data with a reason for needing that access So that it's all audit logged.
Speaker:
00:34:36
It's all recorded, who requested it, who approved it, that there was an actual business
Speaker:
00:34:40
need to access that data, that it wasn't done willy nilly, or
Speaker:
00:34:44
that that you had the patient's permission to access that data.
Speaker:
00:34:47
You know, just creating that that simple little bit of
Speaker:
00:34:51
diligence to say, yeah, this data access happened for a reason.
Speaker:
00:34:55
Right. And that it's automatically documented, so then you don't have Some
Speaker:
00:34:59
tedious manual process where you have to fill out a form and and fax it
Speaker:
00:35:02
to headquarters and wait on them to contact somebody and, you know, the the typical
Speaker:
00:35:05
Byzantine Data access processes in health care.
Speaker:
00:35:10
Very cool. I I tweeted that. I didn't overheard.
Speaker:
00:35:14
Oh, I heard that more and more lately here, because during the pod
Speaker:
00:35:18
you know, the podcast recordings because, definitely trying
Speaker:
00:35:22
to tease season 7. And, yeah. It's
Speaker:
00:35:25
that's a that is a great a great line. It's it's got controversy
Speaker:
00:35:29
written all over it, Nicholas. Thank you. Absolutely. God, I can have
Speaker:
00:35:33
one. I totally agree with you, on on that. And
Speaker:
00:35:36
it's you know, I and I understand the drive to say data is
Speaker:
00:35:40
an asset Because for so long, people just looked at at data
Speaker:
00:35:44
as being something kinda neutral. You know? It was hanging around. Maybe they were,
Speaker:
00:35:48
Yeah. I was taking up space, filling up the sand Or byproduct. Or
Speaker:
00:35:52
byproduct. Right? Right. You know, I I always think of the story about I I
Speaker:
00:35:55
don't know exactly the chemical Or whatever, but apparently,
Speaker:
00:36:00
I guess steel mills used to produce, like, this kind of ash, and
Speaker:
00:36:03
it was useless until somebody figured out that it's Good for,
Speaker:
00:36:07
getting traction in snow or for car for for parking
Speaker:
00:36:11
lots or something like that. I I It's it's a bit late in the day.
Speaker:
00:36:15
It's been a long day, so I I don't forget exactly what it's about, but
Speaker:
00:36:18
I remember. So, you know, so the story goes is that, you know, whoever
Speaker:
00:36:21
figured that out, I mean, they the the
Speaker:
00:36:25
steel companies just, like, here, if you're willing to take our trash, go ahead. As
Speaker:
00:36:28
soon as they found out that this guy was making money off that, Suddenly, it
Speaker:
00:36:32
was no longer free. They charged, like, you know,
Speaker:
00:36:35
$5 a ton or something like that. It was just interesting how How,
Speaker:
00:36:39
you know, as the thing goes, 1 man's trash is another man's treasure, but as
Speaker:
00:36:42
soon as it becomes a treasure, then other people are gonna see
Speaker:
00:36:46
that. Yeah. I mean, at point in time example, Reddit's in the
Speaker:
00:36:50
process of making their API paid right now so that you have to pay to
Speaker:
00:36:53
train, like, large language models on it. Interesting.
Speaker:
00:36:58
I would shudder to think what a a large language model training that would
Speaker:
00:37:01
be. Little scary. You know, I don't wanna go to go down that
Speaker:
00:37:05
That's something I've been watching a lot lately, for
Speaker:
00:37:09
some for some playtime work I've been doing. And,
Speaker:
00:37:13
it dramatically dropped, The, the cost to
Speaker:
00:37:16
train because the large language models aren't as large any
Speaker:
00:37:20
Mhmm. At least the sets of tokens and such. Yeah. So it's gone
Speaker:
00:37:24
down to, like, less than $100. That that's on certainly less
Speaker:
00:37:28
than 1,000, but in some cases, like, you know, 30, $40 to train him
Speaker:
00:37:31
on. Yes. Which is a far cry from the 7 to 12,000,000 that
Speaker:
00:37:35
Right. Yeah. That some of the more popular ones have been on. So it's,
Speaker:
00:37:39
you know, and and and it it amuses me that, you know, you have countries
Speaker:
00:37:43
that are trying to ban chat gpt. Right? The the the
Speaker:
00:37:46
cat's out of the bag, genie's out, whatever, Genius on the bottle, like, you can't
Speaker:
00:37:50
stop the signal, you know, like, it's already out. And Great
Speaker:
00:37:54
reference, Frank. Yeah.
Speaker:
00:37:57
I was talking to somebody yesterday on a completely on nontechnology
Speaker:
00:38:01
related thing, and I said, you can't stop the signal. And he got the reference,
Speaker:
00:38:05
so which I thought was pretty funny.
Speaker:
00:38:09
But I'm sorry I cut you off, Nick. No. Oh, thought
Speaker:
00:38:12
I did. No. This is
Speaker:
00:38:16
a fascinating conversation. I think we can go on for hours, but we wanna be
Speaker:
00:38:20
respectful of your time and switch to our pre canned questions.
Speaker:
00:38:24
I will kick off number 1 because we have to change it slightly. How did
Speaker:
00:38:27
you find your way into technology? Did tech find you, or did that
Speaker:
00:38:31
Techlife, Where you found that Tech Life?
Speaker:
00:38:34
So I had an uncle that when I was,
Speaker:
00:38:38
gosh, 9 or 10, Had an old Amiga
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00:38:42
computer, and that was the 1st computer I spent any significant time
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00:38:46
with, and just sort of Really kinda fell in
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00:38:49
love with it as a toy first. And then, you know, not long after
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00:38:53
that, IBM PC's PC DOS came out.
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00:38:57
Basic was everywhere. Went to a summer camp and learned how to program
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00:39:01
in basic. And, the the first productive thing I ever did on a
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00:39:04
computer was I wrote a 20 question quiz in Apple
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00:39:08
2 Basic over Egyptian history for a
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00:39:11
6th grade project. And I Nice. We didn't have a computer at home at the
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00:39:15
time, so I stayed after school working on that Apple 2 to write that code.
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00:39:19
And just I I obviously got a good grade on the assignment and just have
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00:39:22
I've been infatuated with being able to make the the
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00:39:26
magic blinking box kinda do what I want it to do ever since.
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00:39:30
I like that description. Very cool. Our
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00:39:34
second question is, what's your favorite part of your current gig?
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00:39:39
My favorite part of my current gig is kinda it gets into what we were
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00:39:41
talking about at The the top of the call, sort of
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00:39:45
being able to really shape and and build a culture where the the people
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00:39:49
on the engineering team are really able to thrive, and really able to support each
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00:39:52
other. It's a really fun group of people
Speaker:
00:39:56
to get to work with, and and the way that they're able to support each
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00:39:59
other in projects and in in growth and, learning new things is
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00:40:03
really, really fulfilling for me from from a leadership perspective.
Speaker:
00:40:10
Interesting. So we have 3 complete the
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00:40:13
sentence, questions. When I'm not working, I
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00:40:17
enjoy blank. Trying to come up with 1 answer,
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00:40:20
but this is really hard. I'm a huge soccer fan, so I'll say that. I
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00:40:24
we have season tickets to Austin FC, watch a lot of EPL with my son.
Speaker:
00:40:28
My son plays. So Oh, cool. A a lot of a lot of 90
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00:40:32
minute increments of my life are spent watching soccer matches.
Speaker:
00:40:37
Awesome. Our second is, I think the coolest thing in
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00:40:41
technology today is Blank. That it's
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00:40:45
becoming more humane. Like, the the conversation that we had at the
Speaker:
00:40:48
top of the call is one that is Far more common
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00:40:52
today than it was 20 years ago when I started my career. And I think
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00:40:55
it's only gonna get more that way, because As systems get
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00:40:59
more complicated, we're gonna have more sophisticated and complicated discussions
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00:41:03
about humans' roles and interacting with those systems. AI is a great
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00:41:06
example. What part of jobs does this supplant? What part of jobs does
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00:41:10
it augment? How do we do it in a safe way? How do we keep
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00:41:12
it aligned with people? And at at at the root, Those are all questions about
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00:41:16
how do humans interact with technology and with each other when technology's
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00:41:20
in the room, and I think that's a really interesting bit of history to get
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00:41:23
to live through. Interesting.
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00:41:27
Our 3rd and final complete the sentence. I look forward to the day when I
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00:41:31
can use technology to blank.
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00:41:35
I just did my taxes, so autonomously do my taxes. That would
Speaker:
00:41:39
be nice.
Speaker:
00:41:43
Here's a moonshot goal. Have, some kind of large language model that can explain
Speaker:
00:41:47
the tax code in the United States. K. Good good luck with that one. It
Speaker:
00:41:50
would just Yeah. Yeah. Answers.
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00:41:55
Oh, I thought of, like, 3 things to say, and I'm not gonna
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00:41:59
say either of those things Because
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00:42:03
We wanna keep our Itunes clean rating. I'm not gonna I'm not gonna
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00:42:07
finish that segment. Yeah. Good segue to that. Share something different about
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00:42:11
yourself. And do remember that we're a family show,
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00:42:15
and we wanna keep that clean rating. Something different about
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00:42:18
myself. I am really, really obsessively into To pour
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00:42:22
over coffee. I spend an awful lot of time and
Speaker:
00:42:25
energy trying to dial in my daily cup because it's it's that just
Speaker:
00:42:29
Even the ritual of making coffee in the morning is sort of the thing that
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00:42:32
mentally transitions me into work as someone who works from home. Uh-huh.
Speaker:
00:42:35
And, it it's one of those things that The more time I
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00:42:39
spend on it, the more I learn about it, the more it rewards me with
Speaker:
00:42:42
a better cup of coffee. So you're doing the filter In
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00:42:46
the kind of the ring, and you put the grounds in Mhmm. And then pour
Speaker:
00:42:49
the coffee through them. Yep. That's interesting.
Speaker:
00:42:54
So, yeah, I've I do a French press, but I've been doing that for I
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00:42:57
don't know. It's way too long. But the, the I've
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00:43:01
heard AeroPress. I've never I've had a lot of people recommend AeroPress. I've never
Speaker:
00:43:04
really tried it. It's great. So is it? It's a it's a really easy
Speaker:
00:43:08
way to get a really good cup of coffee. So what do you think the
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00:43:11
big difference is then between AeroPress and pour over?
Speaker:
00:43:17
With AeroPress, Pressure is a component of how you're brewing. I mean, it's not
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00:43:20
anything close to espresso. Yeah. But but you're generally going
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00:43:24
to brew you're gonna grind a little bit Feiner for AeroPress, you're gonna
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00:43:28
extract a little bit different notes out of the coffee with a little bit of
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00:43:30
pressure that you add. So you kinda have to dial in the rest of things
Speaker:
00:43:34
to make sure you're extracting the part of the coffee that you wanna
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00:43:37
drink. You said notes. Mhmm. So is that how you think about
Speaker:
00:43:41
it musically? Flavor notes. Flavor notes. So light. I
Speaker:
00:43:45
didn't understand. Yeah. I mean, you know, if you get into, like, the the one
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00:43:48
of the easiest ones to taste in in lighter roast coffees is the difference between
Speaker:
00:43:52
a natural process and a washed processed coffee. So if
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00:43:55
you get a single origin washed processed coffee, you're gonna get all kinds of citrus
Speaker:
00:43:59
notes from it. You're gonna get orange and lemon. If you get a natural
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00:44:02
process, it's probably gonna be weighted more towards the berry side of the flavor
Speaker:
00:44:06
spectrum. So Interesting. A really good Ethiopian natural process
Speaker:
00:44:10
coffee Prepared well is gonna taste like blueberry pie in a way that you just
Speaker:
00:44:13
cannot miss. Wow. I've had really
Speaker:
00:44:17
I've had good coffee. I and I'm sitting here, like
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00:44:21
Like, when I when I wake up in the morning, like, I am the only
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00:44:24
thing I can functionally do is let the dogs outside
Speaker:
00:44:27
and Lift the Keurig machine, drop the kappa in, hit the button,
Speaker:
00:44:31
which I know is probably blasphemy, to
Speaker:
00:44:35
to to to To the purest out there, but I'm just incapable of doing.
Speaker:
00:44:38
However, if I am somewhere, and I can enjoy a good cup of coffee after
Speaker:
00:44:42
I've had my first couple of, cops to get conscious?
Speaker:
00:44:47
I do I do I have had that that type of Ethiopian single
Speaker:
00:44:51
source, and It's it's just very it's very strange.
Speaker:
00:44:55
Like, almost has, like, blueberry ish pie thing
Speaker:
00:44:59
going on. Like Like, what is in it? You know, like but and
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00:45:03
then I think it was at some airport somewhere. It might have been Seattle where
Speaker:
00:45:06
they had, like they take coffee extremely seriously. And Mhmm. I was like, no.
Speaker:
00:45:10
No. No. That's just part of the thing. I was like, oh, that's interesting. So,
Speaker:
00:45:13
yeah, you had me at Blueberry. Now I got you at Blueberry. Yeah. I'm
Speaker:
00:45:17
a I'm a Blueberry fanatic. Nice. Awesome.
Speaker:
00:45:23
Alright. So Audible is a sponsor of Data Driven.
Speaker:
00:45:27
Do you do audiobooks and and do you recommend okay. Cool.
Speaker:
00:45:31
So, any particular lessons you would recommend to our,
Speaker:
00:45:34
listeners? I will give you 2. Right now, I'm listening to
Speaker:
00:45:38
John Scalzi's agent to the stars, narrated by Wil Wheaton, who is my
Speaker:
00:45:42
absolute favorite audiobook narrator. I actually pick audiobooks based on the
Speaker:
00:45:45
fact that he's the one that narrates them because he's just the the character
Speaker:
00:45:49
he brings to the book, the way he brings out the story, I just I
Speaker:
00:45:52
really enjoy. So that's a fun it's a really fun listen. And
Speaker:
00:45:55
then on the nonfiction side, my favorite management book of
Speaker:
00:45:59
all time is Turn the Ship Around by, admiral David Marche. It's about
Speaker:
00:46:03
a captain of a a nuclear submarine that sort of uses the same kind of
Speaker:
00:46:07
things we've been talking about to to turn around the performance of The
Speaker:
00:46:10
previously worst performing boat in the fleet. So kinda bucking
Speaker:
00:46:13
military hierarchical management traditions for for something that
Speaker:
00:46:17
gives the people on the boat more autonomy and ownership over over the thing that
Speaker:
00:46:21
they're in charge of on on the boat into some pretty spectacular results.
Speaker:
00:46:24
Nice. And it's it's very narrative, so it doesn't read like a business book. It's
Speaker:
00:46:28
a great audiobook listen. Yeah. Cool. Interesting.
Speaker:
00:46:32
So, if you go to the data driven book.com, you will get 1 free audiobook
Speaker:
00:46:36
on us, and then we get, Maybe enough to
Speaker:
00:46:39
get a a nice cup of blueberry pie. One of those blueberry pack office. I
Speaker:
00:46:43
was thinking the same thing if you sign up. If you sign up,
Speaker:
00:46:47
health support to show helps us, kinda grow, and we're already
Speaker:
00:46:50
in season 7, but we're recording us before season 7 launch. So hello,
Speaker:
00:46:54
future people. And then
Speaker:
00:46:58
finally, the final question is, where can
Speaker:
00:47:02
people learn more about you, Nick, and Sim?
Speaker:
00:47:06
So for me, all I've got a lot of blog posts and all of my
Speaker:
00:47:09
talks up at my personal website, nmeans.dev. And
Speaker:
00:47:12
then for Sim, you can visit our website sym0ps.com.
Speaker:
00:47:17
Sign up for a free tile trial, kick the tires. We'd love to get
Speaker:
00:47:21
feedback on it. So if any of your listeners try it, have questions about it,
Speaker:
00:47:25
feel free to to reach out to me or anybody at Sym. We'd love to
Speaker:
00:47:27
help you kinda get started on the platform. Excellent. Well, thank
Speaker:
00:47:31
you very much. Any parting words, Andy? No. I'm just really sorry
Speaker:
00:47:35
now after listening to the 2 answers that referred To the beginning of the
Speaker:
00:47:39
show. I'm really sorry I missed that. I'm gonna have to wait. Well, we can
Speaker:
00:47:41
use that that that machine from Spaceballs. You can go
Speaker:
00:47:45
back And then redo it so future Andy
Speaker:
00:47:49
will know how it all turned out.
Speaker:
00:47:52
Perfect. Perfect. I think Nick knows that we we, you know,
Speaker:
00:47:56
we we do a lot we do at lee there always ends up being at
Speaker:
00:47:59
least 1 movie reference, so we got that. Nice. Yeah.
Speaker:
00:48:03
Alright. Thank you, Nick. Any last thoughts? No. Thanks so much for having me on.
Speaker:
00:48:06
This has been a really fun conversation. Awesome. Thank you. We'll we'll let
Speaker:
00:48:10
Bailey finish the show. And that wraps up another
Speaker:
00:48:14
intriguing episode of data driven. We hope you
Speaker:
00:48:18
enjoyed our conversation with Nick Means, the VP of software
Speaker:
00:48:21
development at Sym. From exploring the concepts of
Speaker:
00:48:25
shame and vulnerability in the software industry Dri to diving into the
Speaker:
00:48:28
fascinating world of engineering disasters. This episode has been a
Speaker:
00:48:32
thought provoking journey. We delved into the importance of
Speaker:
00:48:36
being good stewards of data and the significance of compliance with
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00:48:39
regulations, all while finding ways to balance security and
Speaker:
00:48:43
efficiency. As we wrap up, we encourage you to
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00:48:46
reflect on the valuable insights and takeaways shared in this episode.
Speaker:
00:48:51
The path towards a blameless mindset, fostering stronger
Speaker:
00:48:54
organizational culture, and embracing the principles of little agile
Speaker:
00:48:58
are just some of the actionable steps we discussed.
Speaker:
00:49:02
Remember, mistakes happen, but it's how we learn from them and share
Speaker:
00:49:05
our experiences that truly makes a difference.
Speaker:
00:49:09
So let's continue to grow, adapt, and shape the software
Speaker:
00:49:13
industry into a more resilient space.
