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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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happens. You encourage people to sweep it under the rug. Kinda what we're talking about.

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It's it's the thing if Phil Meacher had done this with Citicorp Center. Citicorp Center

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probably would have fallen over at some point. And so having a

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blameless mindset when something goes wrong encourages people to raise their

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hand sooner, bring other people in on the solution, Let the whole organization

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learn from the the mistake that they just made. And and, you know, it's kinda

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rooted in a systems thinking mindset as well. You know, how can we Change the

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system so that a a mistake that's shaped like this is more difficult to

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make in the future. So here's a random question.

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I noticed that GitHub has something called the blame tool. I think it's part of

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Git. Mhmm. Is that is that a tongue in cheek

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reference, or is that actually, Like, actually a

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blame. Like, what are your thought? Well, I don't know the history of that,

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so maybe maybe you could tell me. And then Yeah. I mean, it it is

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from Git Self not from GitHub. It's something that just showed up in the in

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the GitHub UI from from Git. I actually, on my own system, alias

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it to get credit, so I don't have to type git blame. Oh, I like

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that. Oh, that's awesome. And that's

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I I it's definitely not my original idea. I know a lot of people that

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do that as well, just because Get blame puts you in

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sort of a certain frame of mind when you're reading code, and it's often not

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a helpful or charitable frame of mind. Whereas get credit is more like,

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okay. Who can I ask to hear this story of of why this line code

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came to be? Yeah. That was because that

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yeah. When you mentioned blameless mindset, and I was like but, I mean, I guess

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that speaks to kinda, like, you know, like, you know, the origin story

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of Git, I guess, Blame the blame tool or I don't I

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don't know. Like, it just to me, it just seemed like there's gotta be more

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to that story. Yeah. And when I first heard the tool, The guy I was

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working with, he thought it was funny. Oh, they have a blame tool, so you

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can always know who's to blame. And I was like I was like, that's kinda

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mean, actually, you know. A little bit. A little bit. I mean and again, you

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know, it gets into, like, the the prime directive of retrospectives if you've done spent

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any time in the Agile world. This idea that everybody was doing the best that

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they could at the time that they did it and made the best decision they

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could with the information they had. Right.

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What's interesting in as you see those That

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agile processes kind of happen, right? There's there's

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the theory, and then there's the practice. Mhmm. And

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Its organizational culture tends to take all the

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oxygen out of that room. Yeah. You know and and you're not

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surprised so I guess that's that's a thing You know? I

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I I like to and I forget who coined this distinction. It may

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have been kept back, the idea of big a agile versus little a agile.

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Yes. Big Agile, the idea that there's all all these off the

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shelf methodologies that you can just pick up off the shelf and adopt in your

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organization, and and suddenly the the heavens will part and will sound and you will

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be more agile. You look at something like SAFe, the

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scaled agile framework, and you can pretty clearly see that that's not the case. It's

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just Waterfall in disguise at the organizational level.

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Whereas more more little a agile is the actual principles, the

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spirit of Of sort of the agile software movement where it is more

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autonomous. It is more short planning cycles, getting feedback early,

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shipping in small increments, that sort of thing. And it's really easy to pick up

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an off the shelf agile methodology and not do any of that stuff.

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Right. I I remember hearing an interview once, a podcast,

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probably a decade ago where, someone referred

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to their, their software development life cycle

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as Scrum Bud. Mhmm. And so when we're doing

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scrum, but and then, you know, something followed that wasn't

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scrum. And it sounds a lot like what you're describing. Yep.

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Absolutely. Yeah. One of the reasons I I tend to be more with my teams,

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more Kanban inspired than Scrum inspired. And and the reason for that

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is Because I've seen too many teams try to win the

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sprint, and and it sort of creates this perverse incentive to just

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get code across the line no matter what it takes. Yeah. I I like

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the community aspect of Kanban, the swarming, and Mhmm. You know, I've

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seen that work. I I actually learned that on a real live plant

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floor. So, you know, I've got I I used to joke with

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Frank that I've got about 8 more years of books I can write,

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process engineering because I know where they're going. Yeah. And, you know,

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and and what's interesting is we've reached that phase where I was in

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manufacturing in the late, nineties, And we reached that

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phase where we learned where it wouldn't work. Mhmm. For

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instance, it didn't work in engineering.

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So it's interesting that we're kinda getting to that maturity. I guess that

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maturity would be a good description of it, where we're seeing in the context,

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Especially if software engineering that is falling over some.

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Mhmm. It works really, really well on the plant floor Mhmm. When you're

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in a manufacturing environment, that quality goes through the roof.

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Deming's methodologies are phenomenal. The,

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And maybe you've already covered this, but the culture wherein a lot

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of that, you know, from the manufacturing perspective was developed,

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is a vastly different culture than we have today in the United States.

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It wasn't even I mean, it was Japan. Right. You know? Coming

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out of post World War 2, and That's that is a

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different place. Mhmm. It's probably different than Japan today. I'm

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sure it is. Yeah. You know? So That that has a lot to do with

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it, and you did, I heard I heard the screed behind the

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words about corporate culture. That's that's a huge driver.

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Mhmm. It it just is. Alright. I'll show up. It's and it's, you know,

Speaker:

it's it's not it's really not any different than than what we're talking about about

Speaker:

off shelf agile methodologies. Right? Like, all of these things are tool are toolboxes.

Speaker:

There's useful things in all of them, and there's things that don't apply and don't

Speaker:

work On an organization by organization, team by team basis.

Speaker:

Absolutely. And the trick is you have to be able to have all of these

Speaker:

tools in your toolbox and then go up to a team and go, oh,

Speaker:

I know this shape problem, and I these are the things that we can try

Speaker:

that that will help make this better. Right. Right.

Speaker:

What's your, sorry, Anya cut your head. Go ahead. Go

Speaker:

ahead. How do how does, how

Speaker:

does a software engineering team

Speaker:

Change or leadership within software engineering change the the

Speaker:

the organizational culture, Because I think that's a

Speaker:

big problem. I think that software is eating the

Speaker:

world. I think that was a Mark Zuckerberg quote, and I think that, yeah,

Speaker:

Definitely since ChatGPT, I would say AI is

Speaker:

eating the world. Right? But but ultimately, I'm old enough to

Speaker:

remember when software people were those weird people that they they stuffed us in the

Speaker:

basement Mhmm. And did not wanna hear anything from us

Speaker:

Other than everything's working fine, everything's fine, they certainly

Speaker:

did not wanna hear, management philosophy of,

Speaker:

stump speeches from us. I imagine that's changed

Speaker:

a little, but how does how does

Speaker:

someone who's listening to this Wants to affect chains, wants to

Speaker:

kinda bring that blameless mindset into their organization. How do they

Speaker:

start? I know that's probably, like, a 3 hour talk,

Speaker:

but Where would they how

Speaker:

would they what's the first step? Yeah. I mean, what what a great

Speaker:

question. You know, I think step

Speaker:

1 is just learning and and kind of figuring out where this information

Speaker:

exists. So, like, reading some of the blog posts from John Alsbaugh when

Speaker:

he was When he was CTO at Etsy, reading some of the work

Speaker:

of Sydney Decker, that he's done on safety 2. I mean,

Speaker:

John John Osborn is still out on the speaking circuit doing talks a regular basis.

Speaker:

So there's there's plenty of material to learn from out there. I think it's

Speaker:

it's probably most at home in the SRE community right now.

Speaker:

That's that's where I see a lot of safety cultures and human factors research coming

Speaker:

out as in NSRE at the moment. It was it's still in the dev ops

Speaker:

movement as well. That's kinda where I got acquainted with it. So step

Speaker:

1's kind of learning and then just teaching, giving people the

Speaker:

opportunity to realize that There is a different way that some of the stuff can

Speaker:

be done. You know, as far as an engineering leader being able

Speaker:

to affect larger change in an in an organization, The

Speaker:

one advantage that an engineering leader has is that software

Speaker:

engineering salaries are usually one of an organization's biggest cost centers.

Speaker:

And so it's pretty easy to make a case that optimizations there will

Speaker:

pay off if you can make a A persuasive

Speaker:

case for the optimizations that you wanna make. And that's where some of the things

Speaker:

like getting into manufacturing theory and queuing theory and

Speaker:

systems thinking and being able to put together a very data driven

Speaker:

kind of case around some of the improvements that you're trying to affect and the

Speaker:

ways that you're trying to affect them. It it's funny. One

Speaker:

of one of the most common interventions that I found myself making over and over

Speaker:

again with engineering teams is putting WIP limits in place. Just

Speaker:

because when an engineering team is trying to work on too many things at the

Speaker:

same time, they end up spending so much of their time on context

Speaker:

shifting And and trying to load up new contexts and pick up a

Speaker:

project that's completely different than the one that they're currently working on so they can

Speaker:

provide effective code review, that sort of thing. And it's pretty

Speaker:

easy to kinda talk through the data of if we work on less,

Speaker:

we can get more done, but it's really counterintuitive on the

Speaker:

surface when you first hear that statement. Well, the whole drive

Speaker:

towards parallelism. Mhmm. You know, from a machine level right

Speaker:

through you know, it bleeds through. They're all leaky abstractions to throw out some

Speaker:

other Yep. Terms. But, you know, that that whole idea that if you

Speaker:

do things in parallel, you're gonna be able to accomplish more. And I've

Speaker:

seen, I'm gonna I can't remember the book. I was reading

Speaker:

reading a book by someone. It was maybe 2, 3, 4 years old,

Speaker:

and He was talking about just the exact opposite, and he had use

Speaker:

cases and it just you know, serialize it, and

Speaker:

you'll get more done. And it it it's exactly that context

Speaker:

You eliminate that. Human brains stink at constant

Speaker:

context switching. Awful at it. Yeah. Yeah. So

Speaker:

Great. Great point. Interesting.

Speaker:

So another thing that you you kinda

Speaker:

Mention is talking about compliance. Mhmm. And before everyone

Speaker:

kind of tunes off, turns off the the thing and stops,

Speaker:

stops listening. Bear with me. There's a point here, and I think it's

Speaker:

important. No one gets excited about compliance. I I know I know

Speaker:

that. My wife works in IT security compliance. No

Speaker:

one's happy to see her. I'm I'm happy to see her, but no one at

Speaker:

her job is happy to see her. Dear Roberta, you'll never

Speaker:

Alexa, order some flowers. The,

Speaker:

but With the rise of software

Speaker:

being more and more important, more critical to our, I was talking to somebody

Speaker:

else. It might have been in a preview, The another guest on

Speaker:

another completely random topic. I think

Speaker:

regulation is coming to the software industry whether we like

Speaker:

it or not, Because of its core kind

Speaker:

of nature to our, just economy and infrastructure. Mhmm. And I think that

Speaker:

compliance is gonna be one of those things where, You know, learn

Speaker:

it or, you know, learn it, love it, or, you know, leave the

Speaker:

industry. Yeah. Yeah. And and, Yeah. I'm

Speaker:

sorry. So so, like, how do you how does that it seems like

Speaker:

that would kinda dovetail into this. Right? The the the Learning from

Speaker:

mistakes and and meeting these compliance. I mean, certainly, we see it

Speaker:

in data and various data compliance schemes, but but how does he think this is

Speaker:

How does this gonna affect kind of software? Yeah. I mean, the the first thing

Speaker:

I was gonna say is you can you can already see some of this in

Speaker:

things like GDPR and the California privacy regulations, The the stuff the White

Speaker:

House has been doing lately on software bill of materials, we're starting to see it

Speaker:

kind of creep in in in the in the periphery of the things that we

Speaker:

work on. You know, it's

Speaker:

it's tempting to just look at it and go, this is dumb. This will never

Speaker:

work. It's not gonna make any difference. But there's a there's a There's a more

Speaker:

terrible way to look at it in that it's pointing at a thing that

Speaker:

actually is really important. You know, to to your point, s soft

Speaker:

reads the world as organizations hold on to more and more and more and more

Speaker:

data. That data's a liability, and

Speaker:

If if we're not taking steps to make sure that, a, we're only

Speaker:

holding the data we actually need to hold, and, b, we're doing it as

Speaker:

carefully as we can. We're putting as many walls around it as we can, and

Speaker:

still be able to do our job on on an ongoing basis.

Speaker:

You sort of have to put that responsibility hat on and and think about

Speaker:

it in terms of how can I be a good steward of the data

Speaker:

that people have entrusted to me in in this organization that our customers have given

Speaker:

us? Yeah. And and in that that perspective, when you're looking at it

Speaker:

from the Spirit of law versus the letter of the law. It makes some of

Speaker:

the controls that you need to put in place for some of these compliance regimes

Speaker:

a little bit easier to swallow, And it also gets you into sort

Speaker:

of a an outcome mindset because, you know,

Speaker:

it's really easy to go through and and comply with some of these regulations with

Speaker:

checkboxes. Just do the things they say and and not really

Speaker:

actually make any difference in the overall security of your organization.

Speaker:

But if you look at it from a perspective, this is actually a And and

Speaker:

we should actually be doing this, then you can go about it and put

Speaker:

meaningful controls in place that that don't make it harder to get work done.

Speaker:

They just make it safer to get work And that's ultimately that's ultimately the goal.

Speaker:

That's I mean, that's what we're working on at Sym. It's sort of the whole

Speaker:

point of the product. Yeah. It's a good segue. So

Speaker:

what is Sym? SYM. Not the

Speaker:

Sims. I'm sure that's not I know that's not the first

Speaker:

time you heard the joke today, but, You know? So It's it

Speaker:

is not the 1st time I've heard that joke for sure. What what is what

Speaker:

is Sym do? Like, what What

Speaker:

is the the product? It it's essentially at its core workflow

Speaker:

engine. It allows you to build simple workflows to

Speaker:

request and Orchestrate access to to

Speaker:

production systems. It's probably easiest to explain by just telling you

Speaker:

how we use the product at SEM. We have all of our production infrastructure behind

Speaker:

our own product. So when one of our engineers needs access to

Speaker:

a production system, they just they create a request in Slack, and

Speaker:

then anybody else on the engineering team can approve that request. So kind of a

Speaker:

a 2 keys to launch the rocket approach. And then in the back end,

Speaker:

there's some code that runs in AWS. We assume a role An

Speaker:

AWS that lets us escalate somebody into that

Speaker:

administrator access role or whatever permission set that they've requested

Speaker:

so they can go in and do their job. And then an hour later or

Speaker:

or 4 hours later, whatever time interval they've requested, that access expires.

Speaker:

So you don't end up over time accumulating that janitor's key ring of System access

Speaker:

that you don't actually need on a daily basis. Right.

Speaker:

That's cool. That is interesting.

Speaker:

Now and it it you said something, a a a little bit ago that

Speaker:

I thought was might have sound blasphemous to some of our listeners. Right?

Speaker:

The data is a liability. Yeah. But the more, like, you kinda unpack it,

Speaker:

oh, yeah, I mean, you're right. Like, you know, we're so conditioned to think of

Speaker:

data as an asset, and and asset only. Right?

Speaker:

That I think we will lose sight of reality. Right? Or the

Speaker:

risks of holding data. Right? And I was just thinking, like, you know, if I

Speaker:

had a company, and I had, let's just say, some kind of PII. Mhmm.

Speaker:

Right? And I, after so many

Speaker:

months, or once I'm done doing what I'm doing, I purge it. Right?

Speaker:

I probably would sleep better at night if if I heard,

Speaker:

about, like, there's a there's a breach or anything like that. Right? Like, it's kind

Speaker:

of like, I think I think that there's a, for lack of better term, data

Speaker:

hoarding happening in a lot of organizations. Yeah. And I understand it,

Speaker:

right, because there's this If we've been so conditioned to think data

Speaker:

is only an asset, right? Oh, well, why

Speaker:

not just store it? Store it is cheap, you know? Right? But if

Speaker:

you also think that it can also be a liability,

Speaker:

and obviously not all data types are created equal. Right. Yeah. Of course. And not

Speaker:

all liabilities are created equal. Mhmm. Then that becomes a pretty cold

Speaker:

calculation of, well, yeah, maybe we'll figure

Speaker:

out, you know, if they have an even or odd social security

Speaker:

number. If that means that they're more likely to buy our

Speaker:

product. Yeah. But I don't wanna even hold that stuff anymore. Right? Or

Speaker:

I'll collapse it into, you know, Flag 1, flag 2 based on

Speaker:

that. Right? So, you you know, I I I like that. I hadn't

Speaker:

really thought about that. Yeah. I mean, one of the interesting use cases, you know,

Speaker:

if you think of health care data, there's some of that that you have to

Speaker:

hold. Right. But HIPAA is pretty strict about who can access it and when they

Speaker:

can access it. So one of the workflows that we've seen set up is

Speaker:

is requesting approval to access a particular patient's

Speaker:

data with a reason for needing that access So that it's all audit logged.

Speaker:

It's all recorded, who requested it, who approved it, that there was an actual business

Speaker:

need to access that data, that it wasn't done willy nilly, or

Speaker:

that that you had the patient's permission to access that data.

Speaker:

You know, just creating that that simple little bit of

Speaker:

diligence to say, yeah, this data access happened for a reason.

Speaker:

Right. And that it's automatically documented, so then you don't have Some

Speaker:

tedious manual process where you have to fill out a form and and fax it

Speaker:

to headquarters and wait on them to contact somebody and, you know, the the typical

Speaker:

Byzantine Data access processes in health care.

Speaker:

Very cool. I I tweeted that. I didn't overheard.

Speaker:

Oh, I heard that more and more lately here, because during the pod

Speaker:

you know, the podcast recordings because, definitely trying

Speaker:

to tease season 7. And, yeah. It's

Speaker:

that's a that is a great a great line. It's it's got controversy

Speaker:

written all over it, Nicholas. Thank you. Absolutely. God, I can have

Speaker:

one. I totally agree with you, on on that. And

Speaker:

it's you know, I and I understand the drive to say data is

Speaker:

an asset Because for so long, people just looked at at data

Speaker:

as being something kinda neutral. You know? It was hanging around. Maybe they were,

Speaker:

Yeah. I was taking up space, filling up the sand Or byproduct. Or

Speaker:

byproduct. Right? Right. You know, I I always think of the story about I I

Speaker:

don't know exactly the chemical Or whatever, but apparently,

Speaker:

I guess steel mills used to produce, like, this kind of ash, and

Speaker:

it was useless until somebody figured out that it's Good for,

Speaker:

getting traction in snow or for car for for parking

Speaker:

lots or something like that. I I It's it's a bit late in the day.

Speaker:

It's been a long day, so I I don't forget exactly what it's about, but

Speaker:

I remember. So, you know, so the story goes is that, you know, whoever

Speaker:

figured that out, I mean, they the the

Speaker:

steel companies just, like, here, if you're willing to take our trash, go ahead. As

Speaker:

soon as they found out that this guy was making money off that, Suddenly, it

Speaker:

was no longer free. They charged, like, you know,

Speaker:

$5 a ton or something like that. It was just interesting how How,

Speaker:

you know, as the thing goes, 1 man's trash is another man's treasure, but as

Speaker:

soon as it becomes a treasure, then other people are gonna see

Speaker:

that. Yeah. I mean, at point in time example, Reddit's in the

Speaker:

process of making their API paid right now so that you have to pay to

Speaker:

train, like, large language models on it. Interesting.

Speaker:

I would shudder to think what a a large language model training that would

Speaker:

be. Little scary. You know, I don't wanna go to go down that

Speaker:

That's something I've been watching a lot lately, for

Speaker:

some for some playtime work I've been doing. And,

Speaker:

it dramatically dropped, The, the cost to

Speaker:

train because the large language models aren't as large any

Speaker:

Mhmm. At least the sets of tokens and such. Yeah. So it's gone

Speaker:

down to, like, less than $100. That that's on certainly less

Speaker:

than 1,000, but in some cases, like, you know, 30, $40 to train him

Speaker:

on. Yes. Which is a far cry from the 7 to 12,000,000 that

Speaker:

Right. Yeah. That some of the more popular ones have been on. So it's,

Speaker:

you know, and and and it it amuses me that, you know, you have countries

Speaker:

that are trying to ban chat gpt. Right? The the the

Speaker:

cat's out of the bag, genie's out, whatever, Genius on the bottle, like, you can't

Speaker:

stop the signal, you know, like, it's already out. And Great

Speaker:

reference, Frank. Yeah.

Speaker:

I was talking to somebody yesterday on a completely on nontechnology

Speaker:

related thing, and I said, you can't stop the signal. And he got the reference,

Speaker:

so which I thought was pretty funny.

Speaker:

But I'm sorry I cut you off, Nick. No. Oh, thought

Speaker:

I did. No. This is

Speaker:

a fascinating conversation. I think we can go on for hours, but we wanna be

Speaker:

respectful of your time and switch to our pre canned questions.

Speaker:

I will kick off number 1 because we have to change it slightly. How did

Speaker:

you find your way into technology? Did tech find you, or did that

Speaker:

Techlife, Where you found that Tech Life?

Speaker:

So I had an uncle that when I was,

Speaker:

gosh, 9 or 10, Had an old Amiga

Speaker:

computer, and that was the 1st computer I spent any significant time

Speaker:

with, and just sort of Really kinda fell in

Speaker:

love with it as a toy first. And then, you know, not long after

Speaker:

that, IBM PC's PC DOS came out.

Speaker:

Basic was everywhere. Went to a summer camp and learned how to program

Speaker:

in basic. And, the the first productive thing I ever did on a

Speaker:

computer was I wrote a 20 question quiz in Apple

Speaker:

2 Basic over Egyptian history for a

Speaker:

6th grade project. And I Nice. We didn't have a computer at home at the

Speaker:

time, so I stayed after school working on that Apple 2 to write that code.

Speaker:

And just I I obviously got a good grade on the assignment and just have

Speaker:

I've been infatuated with being able to make the the

Speaker:

magic blinking box kinda do what I want it to do ever since.

Speaker:

I like that description. Very cool. Our

Speaker:

second question is, what's your favorite part of your current gig?

Speaker:

My favorite part of my current gig is kinda it gets into what we were

Speaker:

talking about at The the top of the call, sort of

Speaker:

being able to really shape and and build a culture where the the people

Speaker:

on the engineering team are really able to thrive, and really able to support each

Speaker:

other. It's a really fun group of people

Speaker:

to get to work with, and and the way that they're able to support each

Speaker:

other in projects and in in growth and, learning new things is

Speaker:

really, really fulfilling for me from from a leadership perspective.

Speaker:

Interesting. So we have 3 complete the

Speaker:

sentence, questions. When I'm not working, I

Speaker:

enjoy blank. Trying to come up with 1 answer,

Speaker:

but this is really hard. I'm a huge soccer fan, so I'll say that. I

Speaker:

we have season tickets to Austin FC, watch a lot of EPL with my son.

Speaker:

My son plays. So Oh, cool. A a lot of a lot of 90

Speaker:

minute increments of my life are spent watching soccer matches.

Speaker:

Awesome. Our second is, I think the coolest thing in

Speaker:

technology today is Blank. That it's

Speaker:

becoming more humane. Like, the the conversation that we had at the

Speaker:

top of the call is one that is Far more common

Speaker:

today than it was 20 years ago when I started my career. And I think

Speaker:

it's only gonna get more that way, because As systems get

Speaker:

more complicated, we're gonna have more sophisticated and complicated discussions

Speaker:

about humans' roles and interacting with those systems. AI is a great

Speaker:

example. What part of jobs does this supplant? What part of jobs does

Speaker:

it augment? How do we do it in a safe way? How do we keep

Speaker:

it aligned with people? And at at at the root, Those are all questions about

Speaker:

how do humans interact with technology and with each other when technology's

Speaker:

in the room, and I think that's a really interesting bit of history to get

Speaker:

to live through. Interesting.

Speaker:

Our 3rd and final complete the sentence. I look forward to the day when I

Speaker:

can use technology to blank.

Speaker:

I just did my taxes, so autonomously do my taxes. That would

Speaker:

be nice.

Speaker:

Here's a moonshot goal. Have, some kind of large language model that can explain

Speaker:

the tax code in the United States. K. Good good luck with that one. It

Speaker:

would just Yeah. Yeah. Answers.

Speaker:

Oh, I thought of, like, 3 things to say, and I'm not gonna

Speaker:

say either of those things Because

Speaker:

We wanna keep our Itunes clean rating. I'm not gonna I'm not gonna

Speaker:

finish that segment. Yeah. Good segue to that. Share something different about

Speaker:

yourself. And do remember that we're a family show,

Speaker:

and we wanna keep that clean rating. Something different about

Speaker:

myself. I am really, really obsessively into To pour

Speaker:

over coffee. I spend an awful lot of time and

Speaker:

energy trying to dial in my daily cup because it's it's that just

Speaker:

Even the ritual of making coffee in the morning is sort of the thing that

Speaker:

mentally transitions me into work as someone who works from home. Uh-huh.

Speaker:

And, it it's one of those things that The more time I

Speaker:

spend on it, the more I learn about it, the more it rewards me with

Speaker:

a better cup of coffee. So you're doing the filter In

Speaker:

the kind of the ring, and you put the grounds in Mhmm. And then pour

Speaker:

the coffee through them. Yep. That's interesting.

Speaker:

So, yeah, I've I do a French press, but I've been doing that for I

Speaker:

don't know. It's way too long. But the, the I've

Speaker:

heard AeroPress. I've never I've had a lot of people recommend AeroPress. I've never

Speaker:

really tried it. It's great. So is it? It's a it's a really easy

Speaker:

way to get a really good cup of coffee. So what do you think the

Speaker:

big difference is then between AeroPress and pour over?

Speaker:

With AeroPress, Pressure is a component of how you're brewing. I mean, it's not

Speaker:

anything close to espresso. Yeah. But but you're generally going

Speaker:

to brew you're gonna grind a little bit Feiner for AeroPress, you're gonna

Speaker:

extract a little bit different notes out of the coffee with a little bit of

Speaker:

pressure that you add. So you kinda have to dial in the rest of things

Speaker:

to make sure you're extracting the part of the coffee that you wanna

Speaker:

drink. You said notes. Mhmm. So is that how you think about

Speaker:

it musically? Flavor notes. Flavor notes. So light. I

Speaker:

didn't understand. Yeah. I mean, you know, if you get into, like, the the one

Speaker:

of the easiest ones to taste in in lighter roast coffees is the difference between

Speaker:

a natural process and a washed processed coffee. So if

Speaker:

you get a single origin washed processed coffee, you're gonna get all kinds of citrus

Speaker:

notes from it. You're gonna get orange and lemon. If you get a natural

Speaker:

process, it's probably gonna be weighted more towards the berry side of the flavor

Speaker:

spectrum. So Interesting. A really good Ethiopian natural process

Speaker:

coffee Prepared well is gonna taste like blueberry pie in a way that you just

Speaker:

cannot miss. Wow. I've had really

Speaker:

I've had good coffee. I and I'm sitting here, like

Speaker:

Like, when I when I wake up in the morning, like, I am the only

Speaker:

thing I can functionally do is let the dogs outside

Speaker:

and Lift the Keurig machine, drop the kappa in, hit the button,

Speaker:

which I know is probably blasphemy, to

Speaker:

to to to To the purest out there, but I'm just incapable of doing.

Speaker:

However, if I am somewhere, and I can enjoy a good cup of coffee after

Speaker:

I've had my first couple of, cops to get conscious?

Speaker:

I do I do I have had that that type of Ethiopian single

Speaker:

source, and It's it's just very it's very strange.

Speaker:

Like, almost has, like, blueberry ish pie thing

Speaker:

going on. Like Like, what is in it? You know, like but and

Speaker:

then I think it was at some airport somewhere. It might have been Seattle where

Speaker:

they had, like they take coffee extremely seriously. And Mhmm. I was like, no.

Speaker:

No. No. That's just part of the thing. I was like, oh, that's interesting. So,

Speaker:

yeah, you had me at Blueberry. Now I got you at Blueberry. Yeah. I'm

Speaker:

a I'm a Blueberry fanatic. Nice. Awesome.

Speaker:

Alright. So Audible is a sponsor of Data Driven.

Speaker:

Do you do audiobooks and and do you recommend okay. Cool.

Speaker:

So, any particular lessons you would recommend to our,

Speaker:

listeners? I will give you 2. Right now, I'm listening to

Speaker:

John Scalzi's agent to the stars, narrated by Wil Wheaton, who is my

Speaker:

absolute favorite audiobook narrator. I actually pick audiobooks based on the

Speaker:

fact that he's the one that narrates them because he's just the the character

Speaker:

he brings to the book, the way he brings out the story, I just I

Speaker:

really enjoy. So that's a fun it's a really fun listen. And

Speaker:

then on the nonfiction side, my favorite management book of

Speaker:

all time is Turn the Ship Around by, admiral David Marche. It's about

Speaker:

a captain of a a nuclear submarine that sort of uses the same kind of

Speaker:

things we've been talking about to to turn around the performance of The

Speaker:

previously worst performing boat in the fleet. So kinda bucking

Speaker:

military hierarchical management traditions for for something that

Speaker:

gives the people on the boat more autonomy and ownership over over the thing that

Speaker:

they're in charge of on on the boat into some pretty spectacular results.

Speaker:

Nice. And it's it's very narrative, so it doesn't read like a business book. It's

Speaker:

a great audiobook listen. Yeah. Cool. Interesting.

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So, if you go to the data driven book.com, you will get 1 free audiobook

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on us, and then we get, Maybe enough to

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get a a nice cup of blueberry pie. One of those blueberry pack office. I

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was thinking the same thing if you sign up. If you sign up,

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health support to show helps us, kinda grow, and we're already

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in season 7, but we're recording us before season 7 launch. So hello,

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future people. And then

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finally, the final question is, where can

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people learn more about you, Nick, and Sim?

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So for me, all I've got a lot of blog posts and all of my

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talks up at my personal website, nmeans.dev. And

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then for Sim, you can visit our website sym0ps.com.

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Sign up for a free tile trial, kick the tires. We'd love to get

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feedback on it. So if any of your listeners try it, have questions about it,

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feel free to to reach out to me or anybody at Sym. We'd love to

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help you kinda get started on the platform. Excellent. Well, thank

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you very much. Any parting words, Andy? No. I'm just really sorry

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now after listening to the 2 answers that referred To the beginning of the

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show. I'm really sorry I missed that. I'm gonna have to wait. Well, we can

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use that that that machine from Spaceballs. You can go

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back And then redo it so future Andy

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will know how it all turned out.

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Perfect. Perfect. I think Nick knows that we we, you know,

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we we do a lot we do at lee there always ends up being at

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least 1 movie reference, so we got that. Nice. Yeah.

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Alright. Thank you, Nick. Any last thoughts? No. Thanks so much for having me on.

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This has been a really fun conversation. Awesome. Thank you. We'll we'll let

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Bailey finish the show. And that wraps up another

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intriguing episode of data driven. We hope you

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enjoyed our conversation with Nick Means, the VP of software

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development at Sym. From exploring the concepts of

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shame and vulnerability in the software industry Dri to diving into the

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fascinating world of engineering disasters. This episode has been a

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thought provoking journey. We delved into the importance of

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being good stewards of data and the significance of compliance with

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regulations, all while finding ways to balance security and

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efficiency. As we wrap up, we encourage you to

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reflect on the valuable insights and takeaways shared in this episode.

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The path towards a blameless mindset, fostering stronger

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organizational culture, and embracing the principles of little agile

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are just some of the actionable steps we discussed.

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Remember, mistakes happen, but it's how we learn from them and share

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our experiences that truly makes a difference.

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So let's continue to grow, adapt, and shape the software

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industry into a more resilient space.