AI Triage & Luck Via Skunk

0:02 So it's. It actually has a switch to in the interface to control whether or not it's an alkaline or a. No way. Yeah, I guess I guess it reads it differently. The battery charge level. Yeah, I guess it reads it differently. That's kind of cool. I didn't even know that was in the station that you could do. I've never read it, but yeah, I've never seen that before on a on a device.

0:27 Well, that's pretty cool. So we're talking about, on the way over here, they're talking about Novant Health using CT scans. Now, using eye CT scans. Yeah. And, here we go. Use an eye on CT scans. Yeah, here we go. Because the, actual decision making of who gets the priority comes from that selector. No way.

0:48 Yeah. So they're usually hit. And I went through no more health system. Yeah. Wow. So. So the idea is that the, you know, the the eye can determine way better than a human. They can find, you know, blood clots, nodules, leads, things like that. You know, you can see, you know, how they allocate resources. Right. So it's like the is it then that that then enters into the triage where.

1:15 Well, which makes sense. Yeah. I mean only does if you're going to if you're going to use the technology, why wouldn't you do that. Yeah. You know, it's just like all right. So you got no doubt you've got machine learning models that you're having to continuously tweak. What is this person's view of this? All right. What where what I don't see on the bike up there.

1:37 Oh, I went around twice acting weird. Yeah. So. Oh. It's fine. I hope that, ladies. Okay, that we saw that day that, like, had that wicked odor. Yeah. Dude, that was like, the smell of death, right? Yeah, she was rough, you know? Had a really new jacket on and. Yeah, but no new scarf, but almost smell like awful.

2:01 You're smelling like that. You're in bad shape. She smelled like she had an infection. Yeah. I was like that smell. Yeah. You know, we're not seeing. And that's just bad, right? She's not that walking. Oh, yeah. She's wrapped up in something. Yup. So, yeah, that's just interesting because we were talking about that like the first, our first, episode.

2:24 We were talking about that. And it's interesting because, you know, here it comes. Right, right. And it's in this, it's that's how it's going to be. It's going to be the stair step. It's going to be ratchet. Right? The roll out of this stuff is going to be this is going to keep incrementing. It's going to keep ratcheting up and up and up.

2:43 Yeah. And okay it's already on us you know. Oh wow. You had some experience applying it in a. Yeah medical setting. Sure. So I'm guessing this is one of those things is iterative. They're continuously tweaking the. Sure. The machine learning model. Yep. Yeah. So I can I think I can really simplify it, but not that you need to simplify, but.

3:10 Well I think I might and so might everybody else. Okay. So let's say that you spent your life and you're a specialist and you specialize in career pulmonary or something, right. Like. Sure. So you're really good about the heart and lungs. You know, how you know embolisms work? What type of things? Like wrong guy rales, all the different, you know, conditions, COPD, you know, etc..

3:34 And you have this lifetime experience with this. Yeah. Yeah. Just imagine. Well, a patient comes in and has certain, presents with certain, you know, symptoms and is acting a certain way, etc.. Right. Very quickly you can if that was your specialty, your whole life, you know, a whole career. Yeah. You're going to narrow it down, make a decision in a minute.

3:54 Right. And so, you know, you're valuable, valuable asset to, you know, people that come see you because they happen to fall into that domain of illness, you know, you can you hone in on it really quick and you'll put in countermeasures. Sure. And in many cases, you know, save their life. Right? So you can imagine that, really what it is what that what that person has done through their experience is they've they've taken in a tremendous amount of data specific to, you know, certain disease conditions.

4:23 Right. And their intuition guides them through this data. Yeah. Right. And so, in fact, though there's a there's a nuance here is it becomes a bit of a seeking you shall find world because the, the, the cardio pulmonologist is always looking for something leads at heart lung. Right. Got it. So let's say the, dermatologists is always looking for someone's skin.

4:48 It's just makes sense. Suggest would be right. Right. And obviously they're going to be really good at what they do. Well, you can imagine if you take the preponderance of all that data and you allow an expert, an expert statistician or data, and now it was to go through, they're probably going to find some connections in that data.

5:05 Right? Right. I mean, naturally, yeah. Yeah. Because the data, the data analysis or statistician is an expert in looking at that, at the data from that perspective. Right. Correlations. You know. Yeah. And so they'll be looking at this, this, collection of medical data a lot differently than the, medical specialists is going to be looking at it.

5:25 All right. So the idea here is that all of a sudden, boom, we saw some AI on there and put a pretty decent computer behind it. So you can sit there and sift through this information that would take a thousand data scientists. Right? Yeah. To do the same. And it does it in a day for and all of a sudden it's coming up with all these corollaries between comorbidities.

5:47 Right. And no human ever even thought of before. Right. Right. And so in a very short period of time, you can start making, you know, obviously incredible associations between health conditions, comorbidities with, you know, predictable outcome. Yeah. So there's a typical things that people know in the industry, like, you know, you lose your mobility.

6:10 This is like a really big sign. You probably have like a year or two max left. Right. Same thing. Okay. On average in general, you know, and these things have been tracked and known for years. But now, looking at this data from, you know, this incredible new set of tools, you know, not just machine learning and AI, these deep analytics, you know, being able to really make its own connection.

6:30 That's it. That really encapsulates what's going on. Deep analytics. Yeah. Something that no human mind could ever do. Yeah. Right. Not even an army of people could, could find. You know, this is not about finding it. It's about. You know, It's about, more than common. Good morning. Really about, understanding. Like, it's going to try combinations.

7:05 It's going to look at things in a different way. It's not going to be biased. It's not going to be it's not going to filter everything through the lens of its expertise that it's built up over a lifetime. Yeah. Especially if you just let it let it roll. You don't give it a direction. You just say find the connections.

7:21 Yeah, yeah. And then, which is saying is that, you know, human beings say, okay, we have, you know, the person here, a patient of the history of pulmonary embolism. Right, right. And so it just so happens that the person who had the pulmonary embolism has, you know, on average, only a 20% chance of having DVT, you know.

7:38 Yeah, something like something like that. I mean, the entire box, right. Something like that. Okay. And so, you know, a person can make those connections pretty quick and so can the computer almost instantaneously appears like, you know, I see this, you know, connection forming here between these two, you know, potential health concern, right. Yeah. Well, where it starts doing is it says, okay, well how about DVT is combined with diabetes.

8:01 What does that look like in terms of heart disease. You see. Yeah. So then it can just go through to combine two variables and see how those two and both of those are present, how those two interact. And how about three variables or 4 or 5. So when we're doing those are very IT things exhaustive way better than let's start doing this right this way to stay away from the cars.

8:24 Okay. So so we don't get polluted by the in a multivariate situation it's going to handle thing. Sure better than variables. Why not 20. Why not. Yeah right. Yeah. Why not. You know even even then start throwing overlapping data in there that no one even really thinks. So just just give it the data. But then I guess when we're talking about tweaking the machine learning model, we're tweaking goal functions, we're tweaking, right.

8:54 What does, I guess, the threshold for correlation and things like that. Yeah. So you're right, you do that, but you basically can just throw at the data. Right? Okay. Because the AI tools are sophisticated enough, but kind of off the shelf to do this. It doesn't even require much programing. Right. That's pretty cool. Yeah. I mean it's simple.

9:11 It's a it's basically just like finding the correlations. Yeah. Okay. And then you can start overlapping any data you want say shoe size right. Height weight. You know that's those kind informations would be in there right. Height weight. But you know. Yeah. Not shoe size. Right. Or you know obviously you can compute the BMI right now. Look at that across here.

9:31 How does how does BMI affect all these variables for example. Right. Ethnicity. Lifestyle choices. Right. Yeah. I mean you get really down the rabbit hole, whatever data you have. Yeah. Right. And then next thing you know, holy crap, there's this massive corollary between ethnicity and dietary choices, right? Let's say, vegan veganism. This is an option.

9:56 So let's say a vegan aboriginal. Right. Those two things combined with, a history of heart disease equals what other outcome? Oh, shit. Right. And and and the machine spitting it out, like, I mean, so fast as something funny. Something that would take a human a lifetime. So as long as you and so you formulate the query and you have an answer in hours or no minutes.

10:20 Minutes. Yeah. And not only and for simple things like that tool. But you can do it undirected. You can just say tell me what you find like said on this move over the face of the deep here. Yeah, yeah. So so so what happens when you tell a computer something like, do a two variable analysis, right? Just join any two random variables together, do an analysis of what additional comorbidities arrive out of the data set.

10:44 Right? Right. Next thing no, you know, five minutes later, boom. You have, 50 new insights that you never even modify or at least points to explore for year, for sure. And you don't necessarily need to apply any kind of bias that either. You can just let it be and then let the computer cycle that back through another analysis.

11:05 Okay. So like you might just not know why a couple of things are as a human right, you might not know why a couple things are are linked. Right. Yeah. You just might not know. Why what there is and you might not have an interesting link. The, machine, the machine may not be able to tell you either.

11:25 Yeah, but you know what I was thinking of when I was working with the information like this is like, it doesn't really matter. Just let it do its thing, right? It just let it do its thing. Don't don't try to, put certain throwing the biases in there because the probably is going to, really kind of distort really quickly what happens.

11:44 But then it's funny because the conclusions that it will start drawing is like, you know, people, people that let's say, let's say people that have a history of mental episodes. Okay. Yeah. Then, you know, don't don't have any issues, don't have any, don't have any heart issues. It's like, are very unlikely to have certain heart issues.

12:07 So like what? So it seems like an aberration in the data. Yeah, but not if you think deeply about it. It might not be maybe people with, mental distress over a long period of time are more active. Like they they move around more because they're excited. Let me give you the additional movement, you know, help! Stay off.

12:23 Heart to seeing your heart. Right. Something something just that my mind didn't connect right away. Right? Maybe if I think about it, then more deeply, I can, I can I think about it more deeply. You also analyze, hey, your data collection processes and things like that. You know, I mean, you look at every facet of it. Yeah. Right.

12:41 Yeah. The funniest, part of the part of the project was I figured out right away, like, almost right away, very quickly, that, death cures all disease. Oh, yeah. So you had to put it in there that, you know, that's not desirable. Yeah. It's like like that's that's. We're trying to prevent this. Yeah. Well, are we, you know, are we actually.

13:01 Right, right. I guess and so, you know, it's, you know, and should we and should we rather if someone has, 25 comorbidities, don't even don't even know where they are, you know, I don't know. Yeah. Yeah, but I don't want to. Yeah. Making that choice. But. Hey. Right. You want more of a you want some human input on that one, right?

13:18 I say my I don't want an angel of mercy nurse making that choice. True, true. And I mean that. Hey, the Angel of mercy nurse concept is just here. A nurse. Nurse put a pillow over your face right. That's her actual name. Yeah, yeah. And she's been hired by 12 different, in hospitals. She's been hired. Right? I, because Jessica's opposite.

13:44 Yeah. That's right. It knows that in the deep learning, it never emerged in service. No person ever put their eyes across it. But she's like the of the highest ranking nurse. Yeah.

13:53 Any additional sci fi thing we want to add? Who gives a damn? You know, that's an interesting epitaph. Anyway, that gestures all disease because, yes, of course that's true. But yeah, I think I, I believe that it gets to a point where, you know, I've seen you know what I recently went for it. So, yeah. You know, I think it gets to a point where I guess if you could just pull that switch, it would be, you know, much more humane.

14:20 We do it for animals, you know, we can't figure out it's the right thing to do for humans. Well, I, I yeah, and I don't know why we can't figure out it's the right thing to do for humans. Because if you were able to be lucid. Oh, you were in that state. You say, you know what I want.

14:36 Yeah. So why can't we go about selecting that? So, for example, why can't we say, why can't we just say it's like we can sign a DNR. Why can't we say, yeah, exactly. Exactly. Why can't we say if I don't recognize my son. Right. You know, if I don't know who my son is. Yeah. It's time, you know, or or old voice if I don't recognize it, right?

14:56 I mean, you know, if it's any criteria that maps directly to whatever you got going, you know, later that you can select for it. Yeah. If you're in the memory care community, that's the selector right there. Right. Or you can say like, if I can't pull it myself, if I yeah, if I can get myself to the bathroom then yeah, can put me out to pasture.

15:15 So that's. Yeah, that'll put you on. Good morning. Good morning. You know if we can put that pre-select selector on that and you know, that's then our will being done. And that's very human, very humane, very correct. My mind, my mind, I mean, damn right in my mind as well. I mean, because not only are you being arguably very humane, but you're also following, as you said, someone's, well, someone's, you know, you know, that's what they wanted.

15:44 They want to they want it for themselves and for their family. Because, you know, the really was burned in my mind for what happened with my mom is, you know, her her final terrible days, you know. Yes. And in fact, it didn't need to happen. Not not at all. And that's not that's not the memory that I want or would want anyone else to have.

16:04 Yeah. I mean, you know, it's closure convoluted my life relationship with her. There we go. And you know, so many people would villainize Doctor Kevorkian who was the face of assisted suicide for so long. Yeah, but really, when it comes down to it, he probably wasn't a crazy serial killer. He was a compassionate man who understood something that society wasn't ready for.

16:31 For. And, you know, the apparatus that I'm no expert, but the apparatus I recall in setting up was like a series of buttons that the person presses, you know, and it's not like somebody that doesn't know where they are. It's like, oh, person that suffering from bone cancer, you've got to be cognizant to use this machine before you.

16:48 Yeah. The tumors are growing inside the bone and the bones are breaking all throughout the person's body from the inside out. Yeah, right. They're in absolute mortal pain, 24 seven regardless of how many drugs there are. Right. You know, and those pain receptors can only block them. But yeah. And you don't want them to press a button. I mean come on.

17:07 Yeah. That's that's that's great. That's it's you know, almost like violation of HIPAA because that is doing harm. Yeah. And by allowing that person to chemically, you know, kill themselves, take, you know, end the suffering, allow them to chemically in the suffering. But like, you know, first setting themselves unconscious like in a five minute timer and then they present it in five minutes, I'm going to be unconscious.

17:32 Then presses the next button that says Release chemical. Hey. Yeah. Which stops the heart. Then lastly, release chemical. Be that, you know, this is for neuro suppression. There we go. Yeah. See, you got no rain. Chemical cocktail, no pain, unconscious. Absolutely certain. 100%. No pain because of the drugs that, And then it stops your heart, right. I mean, come on, that's a much more beautiful, an elegant and appropriate way to die.

18:01 Yes. Then, you know, writhing in agony, shuffling off this mortal coil when you choose. So, so much better. Yeah. So, what's our topic for today here? I don't know, we had this answer. Gosh at heart. Yeah, I had hope three. Zeros. It is so sticky. It's funny that, So you bought this, like, microban, stuff for the bathroom.

18:29 It's like like one of the most powerful orange scents I've ever seen. Orange or scents? Yeah, the diverse smell of my wife, and it's awesome. Like, smells really good. Why from it? The problem with it is, like, you can still smell the shit. So now. So like, just go in there is like, oh, it's fucking someone dropped a little bit, you know, be like, oh, it fucking reeks, you know?

18:50 And you're like, oh fuck, it reeks in there. Smells like oranges. So there you just have like, rotten orange. It didn't solve the problem. What I'm trying to say. And sadly, I feel like most air fresheners don't. Oh, God. Dude, I gotta tell you, Larry story I have. I already told you this contained, like, we've talked thousands of hours in our lives.

19:13 Yeah, I probably told you some, but maybe there's this this thing about the potpourri, you know? Oh, you chose the topic. Okay, so, you know, like, in high school and kids start getting their licenses and shit, and, you know, it's like the all of a sudden you stop seeing that kid on the bus, you know, the kid's like the kid.

19:31 The kid's, like, now driving to school, right? Yeah. And that's all I can. Can supply a temporary, like, popularity boost, right? Oh, hell yeah. Because all of a sudden, this person has, like, this adult, access to this adult thing is privilege. Yeah, that's privilege that, you know, a majority don't haven't quite yet. So everybody wants to be a part of their life.

19:52 Yeah. And so my high school, there's this girl, no reason that usernames. Right. Yeah. So, so so go by this girl. This girl. And, she was like, you know, maybe if you put popularity into a scorecard, you know, 1 to 100 or whatever, she was, like, hovering somewhere around 25 or something, right? Yeah. Cool. You know, 100 being the most fine.

20:11 Yeah, yeah. So she was hovering somewhere around 25, and so she was lot, court. Yes. She was just overlooked, you know, a little bit by the boys. Yeah, to some extent. And, but nobody monitors just perfectly, perfectly fine person. Yeah, yeah. Nobody like, seriously not hated, not villainized just right there. Right. She just happened to not get a lot of attention, you know?

20:31 Yeah. And so, anyway, she was one of these first people to get her license, go. Oh, shit. And she starts giving rise to people. Well, all of a sudden, you see this, like, popularity spike? I mean, yeah, to put it to numbers, I mean, she's probably now somewhere like 55, 60, you know, like pretty goddamn good punk double.

20:50 And she had this cool car, bro. Kind of was the. The car was cool. Hell, yeah. And, actually, you would see, I think, like five people. Oh, nine, six people. So, pretty rough storm. Yes. And so she's, like, going and picking up a couple of the popular people, you know, in the mornings and the people are riding in and she's riding on the coattails at the bottom of the people there gained access to the to the to the mobility.

21:12 Yeah, yeah. It's like a nice synergy. And so you get cell that like she's carrying herself a little bit different. She feels the popularity right. Yeah. Like we are in good shape here. And so everything's cool like and maybe a couple of boys, maybe possibly myself, starting to notice her a little more. There we go.

21:33 There we go. And, that was really, really good for her. Like, that was. That was awesome for her. Right. And so, she's like, hover now, like, around it after, you know, a couple months of this. I mean, she was a really early on, you know, early. Yeah. Yeah. You know, getting her vehicle. And so, you know, was the way the birthdays long.

21:52 Well, the great sort of early. Yeah. Exactly. Exactly that. You know. So anyway, so she kind of decides to bump it up a notch. So she's going to ride this fucking way, right? Oh, shit. And so she comes in, one day, and she someone her parents are on her or something, I don't know, spent a lot of money on a really, really, really nicely done perm.

22:14 Oh, fuck. So she went from relatively straight hair, maybe a little wavy into, like, this, like full on perm down. You know, it's not like this gradient gradual change. It's like a start difference. Right. And she finds out with makeup. Oh, that. Who starts wearing pretty heavy makeup. So she gives herself a makeover from head to toe.

22:32 Yeah, you got it. And, this is a funny book and story. You. So, she comes in, and it actually works, like she looks fabulous put together pretty damn well, it was like that whole 80s movie I fall flat here. Yeah, it's like the. Well, you know, it's going to. I wouldn't tell you the story. So, anyway, she comes in and, really nice.

22:54 It's like in the 80s movie where the, the, the shy, kind of homely, you know, kind of head down, tail territory, leg kind of girl. Right? Oh, yeah. She's all that. Yeah. The pretty girl takes her into the bathroom, puts the makeup. I think it was her. Right. You got it in bone. Exactly. So it was like that thing, right?

23:13 It was like that. And, so she's like, okay, like, I'm not going to lie. Looking very goddamn good at this point, right? Like, was able to pull it off. Okay. And, so a lot of guys start to really notice are like locker room talk, you know? Yeah. Dude. And so, that's where it starts. Sorry for dominating the conversation, but no, the story was fine.

23:37 So. Wow. When we're when we live in a warehouse, it's really what it looks like. It does not look good. There's so many of them around here. Fluorescent light and shit. There's so many of us around here. Like we're about to come up on another one right here. I mean, it's like this. I don't see it. I don't I don't get it.

23:54 It's not for me swallowed by this. I don't know the the elite in this area seem to feel like they want a slice of this post-modern style. And it looks like the house is made out of Legos because it's fucking blocky is shit, I totally agree. Give me the classic one with a really wraparound porch, you know, single story with lots of square footage.

24:14 Oh hell yeah, that's exactly. I want a breezeway, a wraparound porch, single story, like 4000ft². Yeah. I'm still dreaming. You know, someday, like someone in my house farting. And I don't hear it, you know, that's that's some that's like. I know I've made it when, you know, there's enough space that people could be, like, frequently. Yeah. The not here.

24:35 Yeah. The baby can go down for a nap and fart out here at downstairs. That's. I think that's why I know I've arrived. I love this. So, back to the story, right? So anyway, you sort of get a lot of attention in locker room talk with the guys. Guys talking like, you know, wow. I mean, you know, look at her.

24:53 I mean, like, she's wow. Yeah, yeah. Dare I be crass? But it wasn't fair for the time. It's like she was even, like, walking a little more upright and kind of poking her chest out a little more, just holding herself different. Yeah. Throwing out her assets. Yeah. She was like, pretty, pretty. Well, you know, she she had some pretty large breasts, and, she never really wore tight, close.

25:16 Those were baggy clothes and was always, like, hunched over a little bit. Yeah. So now all of a sudden, she's, like, looking good, dressed up nice every day, walking with her back straight, right, shoulders back and all of a sudden, like, guys were like, staring at her. What, what what is, you know, definitely above average sized breasts. And I'm so like, everything is working for this girl.

25:34 Yeah. And I'm talking she's probably like in the 75, 80 category now what popularity. All right. And it's just fucking working. And it's like showing like she has a chance to now like she upper echelon definitely upper you know ten top ten or even upper 1%. All right. Jesus. All right. And so she's, like, working her way up there.

25:52 Well, now comes the fucking hilarious part of the story. She's driving in the school one morning and she's with her friends. She's with her new now elite friends, you know, and hits a fucking skunk with the car. Oh, shit. And when she hits the skunk, the skunk, like, sprays the entire undercarriage of the car. Well, like it releases every little fucking scent land it has.

26:14 I mean, you know, a skunk smells like. All right, but, I mean, she has full, full on. She didn't just go through it after it's been run over, she gets a fresh one. Yeah. She's like julienne this fucking thing, right? Yeah. Like mincemeat. Fucking skunk ass. Like her. Her car was painted as skunk butter, you know, and I'm like it totally.

26:34 You think the people come in the school that day? Her and the 4 or 5 other, you know, five other people that were in her car. Right. And they're coming and laughing and carrying on, and they all smell like skunk. Because it just got everywhere destroyed. Who's got they all that? They wrecked us. A couple of them, like, went home, called their parents.

26:52 Right? Yeah. I'm like, I need new clothes. Right. Well, this girl had to drive her car home. Oh, well, the next day she comes in along because, damn, nobody wanted to ride in this shit. Yeah, the popular friends. Like, I'm not getting the fucking snowmobile. Yeah. Now the pressure all of a sudden is her worst enemy, because every little tiny cent of the of the, the surface area of the hair of the hairdo is so high that every molecule of skunk ass gets in the hair.

27:22 Oh, right. No way. You're telling me for days this woman was snow like motherfucker. Oh, I would say wheeze. Oh, no. Yes. And so not only did she plummet, but her probability, she was probably lower than what she was in the beginning. Right, exactly. And just due to random motherfucking chance, just due to random chance and you. And so at that point in my young life, I realized that luck is fucking a factor.

27:48 Yeah, yeah. And, I mean, there's two kinds of luck here. Not only the one kind of luck that she had was she was able to see is see an opportunity, use her skills and abilities and ratchet herself up, you know, but the other kind was just happenstance. This was just totally random. Fucking. Yeah, natural occurrence. You know, it's it does even evolve quantum theory or Eddie Kearns.

28:14 Are you going to bullshit? It's just boom fucking standard across that day. Yeah. And you are here and it is here and I'm, you know, also lucky she probably have the good sense to like, not swerve and crash. Right. So like lucky there but like, so all these good things still lining up for her except for, Yeah.

28:31 Fuck, yeah. When you walking behind her in the hall, the hair is, is like creating a wake of fucking. Oh, destruction weeks, Dude, she she must have washed her hair a thousand times. Oh, I'm sure there just. It was just there. It was just. It was just. And I'm sure she's right. Did it hurt her all or stole things?

28:51 All that stupid shit with you? Here, wash your wash. The the person or whatever with, tomato juice. So do this or that. All right. I'm sure that she probably spilled about so good with tomato juice. Yeah, but it doesn't matter. It's. It's in her car, so she's picking it up every time. Every day. Oh, and, you know, surely she had her car washed, but it just was there.

29:11 It was already in the upholstery. It was in that. Right. Well, she's not going to go out and buy a new car. No. And the car was like the symbol of what? The catalyst for her popularity. So she's not going to, like, abandon and say, I want to take the bus again. Right, right. So she's like, in this no win situation.

29:25 Oh. Shit. Fucking hilarious. Dude, that's. Yeah. And you know, I told you about the talent show my junior year is like, did talent show. And it was like, oh my God, you're so, so talented. And then their senior year fell in my face. Yeah. And, look like a fucking moron. Idiot. So I feel her pain. Exactly like rides is the same.

29:46 But. Yeah, but it was by my own hand at least. Right? Yeah. Right. And that feels a little better. Means I fell on my own sword, you know? Yeah. You're hoisted by your own petard. Yeah, but, yeah, it's like with her, it was just. There's nothing she could do. Yeah, I wasn't perfect all the all the like, back behind the scenes conversations that probably took place, but I can imagine, like, you know, the phone call coming in.

30:10 Hey, do you want me to pick you up this morning? Oh, yeah. And the and the the other popular person being like, oh, no, no, I'm going to. Yeah I'm good. Yeah. And that's a fear of being nice right? Right. More than likely your car stinks. Yeah. And then again it may have ratcheted up beyond that. They may have adopted some quick nickname for said gal.

30:33 Oh I'm sure I wasn't I wasn't in the, in that point in my life where I was like really into name calling. I was like the inside bully bully at that point. Yeah. But, I, I do remember laughing about it. Hey, sorry, but it's fucking funny. Yeah. I mean, it is hilarious and fair enough. I laughed at myself right when that same thing happened to me, right?

30:54 And so, Yeah, that's all you can. Right? And then that's the thing. Hopefully. How's he going to do it like that? Knows it was deep because she had gone so long. You know, I knew her for years. So she'd gone so long of being invisible, ignored. Yeah. So this is a real this is real, man. So it was a watershed moment for her.

31:14 And then when I've got crush. Yeah, I've lost touch with her. I bet she's this like dynamite human beings. This day I hope to God I bet you anything she is. I hope to God daughter, from that soup. Oh, I bet I bet she was. She was smart girl or good. She was like, at the end of the day, I think she's actually really cool, though.

31:32 Yeah, but, you know, fucking hilarious. Oh, really? No, no. What happened? I was like, oh, how I was going to say she was fucking hilarious, dude. She's good. Yeah. I mean, I got I don't particularly recall her being very funny. Okay. But, I do remember, like, got hurting from laughing about the situation, you know, with my with my with my boys.

31:52 Oh, yeah. Oh, yeah. And I mean, like a lie, you know, I was in my later years, I would work to be the anti-bullying as well. But there again, when something that funny. Jesus. Oh, yeah. Do another join. It's right in the locker. It's your obligation. Right. Because, I mean, you're laughing. It this confluence of random shit.

32:21 Yeah. It it's it's right. So it's great that there's, cool. Let's talk a bit about identity today and today because this, this happenstance, this thing, that, that thing that occurred with this person. Yeah. Without exaggerating. Okay. Like, has to some extent defined her identity. Well, 100%. So, so like when I think of this person in my mind's eye to this day, obviously, because I saw this story like my brain associates that with her.

32:51 Yeah, right. And I don't think like if I had a, if I reconnected this person and had an adult relationship that that would change. I mean, maybe it would subside, right? It's going to subside. Yeah. But I don't think it would change. I think that there would always be this, like identifying connection to that event. To her, it's a, you know, it's like the person that jumps in the swimming pool and breaks her neck.

33:15 Now that now they're, quadriplegic. Yeah. It's like, that's kind of now part of their identity. Yeah. I mean, nobody thinks of that person. It doesn't think of them. Undeniable. Yeah. That's the most extreme example. Yeah. Especially when you have the contrast, when you knew them, when they were walking before the incident. Right, right. And then now, like their identity has been completely reshaped by this.

33:35 Jesus, what do we got going on here? Somebody said do an early morning race. I have no idea. Look at.

33:44 Shit, I don't know. Yeah. We're in a 6 a.m. race. It's not even 6 a.m.. Just 530. Whatever. No. Yeah. It's like 630, 630. It's so funny because I almost no scope now it. Right. I saw something that almost. You don't. Oh, it kind of invokes that. Well, there could very well be a sunk in the distance because I do actually smell a faint smell of this gun.

34:10 Well, yeah. Or it could be something else. And then the story connected to Discount Smell nurture. It's one of those areas. Okay, so we lost Jack. So you know this identity thing, right? It's like we have these defining moments that are, you know, either personally or externally shaping as far as people's like, the way they identify with us and then the way we identify with ourselves.

34:32 Right. And, when we have a conversation about LGBTQ community, I really want to bring that up. This idea of like a certain attribute frontloading your, your, where you present yourself to the world whether you want it to or not. If you've ever seen a Dodge Prowler is that floats or not in the long term, anyway, I can see I'm.

34:55 I don't even know. Well, last time I seen a Dodge Prowler, right. So fucking. I agree with you. I mean, it sounds like a sex toy. Yeah, us. So. Or at least two modes of the sexual dodge and throw it depends what side of the floor you're on. You're right. It's like it's kinetic dodge.

35:20 So. Oops. Didn't get out of the way. Flat slap, slap. That's horny. So yeah, I mean, undeniably, there is these central moments in everyone's lives that, you know, the threads of fate weave around. You know, the, flare. Yeah, I'm talking about it specifically and how it's tied to identity. Right? Right. Then I'm saying that's a scene. There's central moments where everyone, everyone, even like she remembers that so vividly and it has shaped her life.

35:55 Is what you're saying, right? Yeah. She surely remembers that. And you know, the story you told, you remember it shaped your life, and your identity is part of the lens, what you filter through. Right. And this at this point in my life is a minor one. But but it's still fluid. It's got to be. Yeah, it's still there.

36:12 So the experience is still there, you know, interconnected with my neurons. Yeah. So see deeply to some extent. Yeah. And and you know more than likely where it comes to mind most is probably those moments where your empathy is triggered. Probably so. And you know, that's interesting thing. Like if you could, if you could like, inevitably prune out certain parts of your own neural net, right, right.

36:34 Like if you had that capability, I bet anything like if I were to have had a different experience, if I had the same senior experiences I had my junior year. Right. It probably would have been shaping as far as like, you know, how that affected my overall life and how you acted towards other people. Probably so. And, there's no way to tell if it's if it had been good or bad, right, like, right.

36:58 Like and it all depends on your perspective here. Right. What is good or bad. Right. Like in totality it's hard is impossible to know in being saying like sci fi idea. Go back and change that then to see how I mean, that's been done in lots of sci fi. Yeah. Like there's a story written by Isaac Asimov that I don't remember the name of, but in essence, it was the same idea.

37:21 It was it was kind of like these equivalents of these intergalactic angels saying they're at a bar, bits of speak, they're like, hey, I bet I can achieve a class A effect with a class C stimulus. That's it. You know? And so that's how your first insight about the Did pass. I thought that was a short story you're going to read.

37:44 Oh no, not that one. Well yeah I mean I could call positive and self sci fi models were they're going to get better. And in this story, the minor change that was made is a, person changed their name to. So they had an anglicized Russian name. They changed it back. Okay, okay. And, their scientific career rocketed off.

38:12 So why not? Yeah, the reason it did was because we're in the midst of the Cold War. They had a certain cachet then people. Right? Right. Rumors started. One small wrinkle to the name. Has all these secondary and tertiary effects. Yeah. That changed like all of all the whole timeline. Yeah, yeah. Just by it wasn't a name here.

38:32 Yep. Well, you know, you got to have some, some sense of that. I mean yeah. What is in a name something. Because, you know, if your name was fucking douchebag like the official name, it would affect me. It would definitely have an effect on you. We know from, like, what they said about resumes and minorities when you have an ethnic sounding name, LaWanda.

38:53 Right. Oh, that automatically puts you on a lower, you know, a hiring bragging. Yeah, they have whatever that's the right example of that actually probably working in some it. Yeah I was thinking that to you. Maybe that goes both ways. So there's this kid, Tristan Jones, who I, me and, this other guy that I worked with hired as an intern.

39:18 Now you got to bleep that right. So it's okay. Visual editing are generic. Yeah sure. But that's the well Jones there you go. It's a whole point is a it's a generic name okay. This I changed his name. To that I see because they help him out in these scenarios. Well he was applying for things and not getting any response for like six months.

39:44 I see changes his name gets like six responses. Okay, well, that also could be coincidental. Could be, you know, and it can also be it can also be like. And I'd love to believe it was a coincidental. Yeah. I mean, tongue in cheek, it wasn't. It was because that is part of a selector. You see that see a certain name and which this I said he changed his name to the whitest name he could think of.

40:07 Well, that's racist, wasn't it? But it was hilarious to hear him say that. Yeah, it sounds like it all sounds like a good story. Yeah, yeah, but, he showed me he an old idiot because I didn't believe him. I was like, you're full of shit. Yeah, and, you know. But what was the first name they changed that?

40:31 You believe Laquan or something like that? No, no no, no. The name he changed. Kristen. How is it? The whitest name? I don't think it could be, but it probably just something. It resonated with him, but that's what he was fucking. He's, you know, bad. Yeah. Freston. Yeah. Oh, the park, I mean. Well, a lot water names.

40:51 Interesting. I think you're you just must have resonated with them. Tristan doesn't come across it. And all to me is like, all of a sudden, like, I don't see a white person, right? No, no. Yeah. But also, case in point, my my name is Tristan. Funny. And he's pretty white with the. Doesn't fucking Caleb. Right, right. Then like, I'm seeing a white guy, right?

41:14 Yeah. Cain. Hey, look. My son. Oh, Adam. Owen. Owen. Yeah. Adam's my is Eric's middle name. Right? Here we go. Like vanilla, as white as possible. But there's a reason for it, right? It's not just like random, right? Right. So Adam was my, uncle's son that died in childbirth. Okay, so it's a tribute. Tribute there. And, I have a four letter name saying.

41:37 Oh, and of course, being my middle name, my son takes that on as his first name. Okay. So he's my namesake in that sense. All right. And then, and that's much less damaging to someone's psyche than being a junior. Shit. Yeah, yeah. I would never do the junior thing to somebody. This is cruel. It ain't no unusual punishment.

41:54 It really is. I mean, I've seen I fucking known as junior for your whole. Yeah, I've seen what it did to my own father. My father's a junior, and. Yeah, he's bristled under the weight of that his entire life. Sure. Like, you know, Preston Johnson the fifth. Yeah. Oh, shit. Boy, he sounds like he was just a clone.

42:13 He really does, like, this is the fifth time this this, this entity is in clone. Yeah. This is the newest incarnation or. Yeah. Yeah, it's the fifth one that lives right? We've tried this 20 times. Fifth one to made it through. You don't want to know what happened to, Zeta. Yeah, yeah, yeah. This head was born on his asshole.

42:36 I was like, motherfucker was inside or out, and you fucking live. We didn't know what to do. Yeah, thankfully, he threw himself down the stairs. Here's Bora contortionist. He didn't go back to normal. Yeah, he had a really fruitful career. And, the circus. And he lives in Florida now. You see, he sees himself. Here's his own human centipede.

43:00 Oh, damn. Oh. Oh. Oh. What does that, what is the scientific term for you yourself? Autophagy or something like that? Oh, God, I don't know. No, I think so. What? So what are these glasses we had to give ourselves? We're one of the first I'm taking. I don't even know why I'm doing this. I'm doing it.

43:24 I do know why I'm doing it. I'm trying to, like, return myself to intellectual ism. Right. So, Because I feel stale. Yeah. And, so, anyway, I'm in this group with these three, yeah. By, by comparison. Young, young guys. Right. I'm sorry. Two, two guys and a girl. And, one of the dudes is like, he's interning with some web design firm or something, and he's like, he's like, acting like he knows everything and he knows nothing.

43:50 And, you know, I'm not going to be the one eyed, hell, am I going to break that bubble? Hell no. Right. Yeah. The the industry society will do that for him. Really? Yeah. You know, and, you know, maybe I don't need to be the one. Maybe he'll see it soon enough to pivot. Doesn't look likely the way it's going, but, yeah, I'm optimistic too.

44:11 But, you know. Yeah, web design is where you want to be. Yeah, he's he's very unskilled. And, you know, that's everyone's unskilled, right? I are with. So, you know, bro, but you don't act like you're a fucking expert. You shouldn't act like you're an expert. That's the thing that got me about unique or unnatural.

44:32 A feeling of expertise in these youngins. I saw it again and again and again, and I'm like, their education is shit at pretty much. Yeah, it's coming up. Is like a Dunning-Kruger type model here. Yeah. It's like people that can turn and work it out. I guess the NCC, right. But I was an alumni. Fuck them.

44:51 Well, you know, it's there's always a bit of a on job training and, you know, a bit of like experience and all that, the skill, it's going to come in to everybody. And then you have to be fair. Right. If, if, if you but I when, when I came out, there's a lot of people that came out with me and they couldn't get jobs.

45:10 I got a job. Easy. Yeah, but it must be the name. The white name. Well, the the white name probably helped. Oh, I'm also joking. The, the experience that I got that everyone else you got in school where I actually applied the knowledge they tried to teach me. You know. Yes. So there's a bit of a natural, you know, potential.

45:31 That's that is that does exist. Right. And some people can overcome that and become, you know, geniuses and experts in the field. Right? No doubt. But there's like when you really get into it, in my opinion, when you're really into even a data science. And so really given it was almost like a natural way of looking at it, that's, that's, you know, it's not really there.

45:50 It's kind of it's kind of there. It's like the person had the potential and then their experience unlocked it. You are thing. Right. And there's some people that no matter how much they how many times they code, how much a wash they are in experience. Yeah. How much mentoring, how much cheerleaders they have. It doesn't matter. The brain's not putting together the the, you know, seeing the way, the best way to do something.

46:10 It's not built for that job. Yeah. And they're always doing, like a thousand times more coding than is necessary. And the design schematic, the arrows moving into is really inefficient. If a long time to code and then high maintenance and you know, they can maybe learn a little bit to be better over time. But if you don't have the contrasting experience, it's like you're working in a vacuum and you don't have you're not part of a team that can really show you that's it.

46:34 You can have a whole life long career in coding and not know these are that's it. That's the key. Again, I think you just said it, I didn't I was always looking for the name of this thing. But it contrasting experience to know you suck. Yeah, yeah. No. And the ability to to sidestep or abandon your own ego.

46:55 Yeah. Yeah. To embrace the lesson of that contrasting experience. Right. Just say that another is better or another has a different perspective that I can embrace and use. Yeah. So I was like, you know, when I was, when I was have had like, five employees at one point, right. Three of which, you know, four of which were were coding.

47:18 Right. That was that was exactly what was happening. I would come in and sit down to do a code review. And, you know, I couldn't help it. It was impossible to know like else in the room. Right? I'd be like, why did you program it this way? Like, you explain, you know, just just walking through. Yeah, yeah.

47:35 And I'll say it's wrong. What were you thinking? Yeah. How did you arrive at this? Was this was the code that you should get, should have applied to this problem. You know? Why did you go about it this way? You know why. And you know, the answer was never satisfying and was always. I don't want to say right or wrong, but wrong because it it was it was horrific.

47:56 Waste of time. The way this house looks. Yeah, it does look cool. Too bad they have like probably 80 people in there. I think it's a business based on the cars. Okay. It's a business. All right. Yeah, probably. Anyway, so, you know, it's pretty, pretty bad, right? Like pretty bad. And, you know, you just couldn't teach an alternative way to see the world, you know, through the lens of a programing, you know?

48:21 Okay, it's just not possible. So, you know, but it would come to that a lot of times, I'd say just to see things stopped for a second. Think about it this way. Right. Like imagine you're doing this in real life. Like. Right. Some something simple, something stupid. Simple, like, adding two numbers together. Let's be ridiculously dumb and simple, right?

48:44 Imagine that. You know, arithmetic would be a bad idea. Yeah, yeah, yeah. And this, this adage that to a man with a hammer, everything looks like a nail. You know, same thing when someone learns a certain code pattern, certain idea about thinking about code. They could have, they could have made a whole bunch of bad code. But now that's their, their, style.

49:02 And they're, they're, they're locked in that mode. That's their hammer. Yeah. And then they apply that to everything that's like, oh my god, spaghetti code. Yeah. You know, like, so something as stupid simple as adding to numbers to get a shit. You not like I could, I could do it just with that. Yeah. So any fucking normal person would say, oh, okay.

49:23 So if the two inputs. Right, write a function as an together with some guardrails on it, you know, or did a bit of checking, you know, make sure your inputs are okay. Right. What's wrong. An error in for a correct type. Looking for maybe bounding the numbers depending right. Or if you can like present size, your inputs and you know, you can guarantee that they're coming in clean.

49:43 You know all does just a plus B right. You know, give results C whatever. Yeah. Yeah. They use the built in function. Yeah. It's on first right. Right. Exactly. Good morning. And so very very interesting thing is that, you know, you look into it and you're like, well, why did you you know, let's think about what you're doing.

50:03 Are you being asked to add two numbers together? And what are those two numbers like, like what are those two numbers for the for the particular application of the software. What are those two numbers going to be right. And let's say it's like dollar amounts shared versus it. Right okay. Cool. So you know a few dollars amounts you want to come in and you know, two numbers are going to come in.

50:23 And what is this application for? Oh, it's for a soda soda vending machine. Right. Was just saying okay, well, do you really need to put a guardrail on this thing for, digits in the millions? No, because we're talking about a fucking soda machine. If anything, just to avoid the whole thing, you could say, look, we won't be dealing with an input size any bigger than.

50:47 Right? So the thing doesn't take credit cards. It takes a maximum dollar bill. Yeah, right. And then any sort of interchange. Yeah. So you don't need to put a check to see if the number is great. And that's 10,000. Yeah. The readers limitation is it can read a bunch right. You know. And so you know you get that and really then start to get in the weeds, like this thing that you ask a developer to do.

51:08 And it was spaghetti code all over the place. Absolutely. Hundreds and hundreds of lines of code that didn't even need exists. Jesus. You know, why not? Why not just have it where if the result is not within these boundaries, it just throws an error there? Why not that. Yeah, that's what I'm saying right now then. And there's one like right.

51:26 And it accomplishes the same thing. There's a, there's the arrow is going to come up anyway. Right. You're gonna throw an error. He might as well catch it. And any error you can think of, catch it, do something with it, carry it safely to ground. Yeah. And it's like, so, you know, this conversation won't happen with the employee, but, you know, I should pull out a napkin and do some quick math and do like, I just pay, you know, just pay $3,000 to this function.

51:52 Yeah. You know, not sit. I guess, figuring in, the cost for them to sit in your building, you figuring in their benefits, figuring and this and that. Yeah. Oh, that's not hard to do. So it's a do an analysis of the total expenditure that you're paying out for that one employee. Right. And then say cast that into a time.

52:11 Right. And that's not hard to do. Simple math, you know, on the back of a napkin. Yeah. And then sit there and determine the cost of what that fucked up function just cost you. Yeah. Okay. Now I gotta factor in my time for fixing this fucking thing. Right? And or scrapping it wholly and just saying, fuck this. We're going to do something completely different.

52:33 Your approach was just completely wrong. But, you know, to save myself time and money in the future, I have to correct it. I teach this person and that's it. And I mean, I saw I saw a small sliver of what you were pouring into the gentleman that attended the, function the other night, and I can only imagine how much he has improved.

52:55 But, wow. Okay. That, that looks like an impossible task. I don't even know why you kept it and kept at it other than you saw value. You could add to someone. It's called trying to, like, stop the person from dying. Yeah, yeah. There we go. So you were like, look, I will give you a purpose.

53:21 I will give you a reason to move forward. Right? You know, there was a mistake. Like when you're when you're when you need help, you shouldn't be. It may is not the best time to be helping everybody else. Well, yeah, but sometimes at rescues you do sometimes. You're right. It's in my nature. Some sometimes it's it can't break it.

53:37 Right. But, you know, rewinding back to this identity thing, wrong to do, wrong to ask you to break it. Really? Yeah. I guess we'll see. It's defining. It's it's ties in this identity conversation. It does. It does. The things that we turn back to the they habits of mind and dare I say so that we keep coming back to these things.

53:59 We gravitate to those things we do. Yeah. There's, I would be a different place in my life if I could get over, an ego thing on my own and combined with, this identifying, you know, so, like, the ego thing on my own is like, you know, I have the power to help this person, right? First of all.

54:18 Right. Right. Right. When in reality, I'm not qualified, you know? But, anyway, you know, it's like ego mode, you know, like, I can. I can fix this. Yeah, right. I can help this situation. And then the lack of reflection being like, I need, I need fixing to like, you know, in these, in these areas and then, you know, combine all that together and then empower someone like that with some resources.

54:41 The next thing you know, you're making mistakes all over the place. You're like, acting like, you know, you just, you're saying you've just created an incredible gaffe machine. You you created. Yeah, a fountain, a screw up. Yeah. Like a like a Rube Rube Goldberg existence. There. Yeah. It's all okay. Oh my God. And pulling everyone else into it like you pulling everyone around you into it to like.

55:04 No, there's a reason why the tea kettle boils and then the steam, you know, turns that that turbine, which then there's, you know, it has to be this way because of these reasons. And you all buy in. Yeah. And then being a strong enough personality and creative enough to then get them to agree. Right, right. And now next, you know I got, you know, ten people wrapped up in this really terrible life experience in this group.

55:26 Nobody's ever been down, you know, that I created. Yeah, yeah. And, you know, literally that something like that should be penalized. But the way human beings are is like, they don't know how to power those modern world. Two that's how some people carve out their niche, and they make enough money to live in support of another. Oh my goodness.

55:45 Yes, Rube Goldberg. In constructions that shouldn't exist, there is bastardization zoos. You know, like like a financial planning program in power basic, you know. Yeah, it's like stuff like that, you know, that that that's produce a result that a whole team of people have come to, to have to have this becomes a becomes a necessity. Yeah. And, you know, the foundation of it is, is horrible.

56:10 So it's like a perpetual house of cards entering everything that you do. You know, how many times have we seen that in our career? Yeah. A few thousand probably. Yeah. Like way too many. Right. So I was like, thinking about that as a, as a, as a programmer, an IT guy in general being like, what am I adding to the fabric of society through, through, you know, working in this, in this occupation?

56:33 I can do it. I can do it. I can actually, you know, solve problems and create results. Yeah. And some things that I've done have had been enduring and, you know, people have built businesses around some of the things that I built. But yeah, you know, still still with that being said, you know, there's been, you know, I don't really know in that domain how much I've actually truly went to the, you know, added to the candles, this, this idea, you know, rather than the fact.

57:01 Yeah, I'm thinking that's you time. Time as well. Yeah. So I see this news. As a landmark, knowing that now we're kind of far out.

57:16 Yeah. So, you know, if you're if you're fear not hypercritical and can suspend your ego and all that stuff for a minute, maybe you can reflect on yourself and be like, yeah, maybe my life kind of had been a roof over. Yeah. Machine. And, you know, yeah, everybody's a free. Everybody at least went through a phase of that.

57:34 If they aren't currently living it. And, you know, that might just be, Western first world nation, you know, first world problem. It could be. One more right idea. I think the idea here is, you know. Minimizing, simplifying. There are things that, don't you this is fairly natural when those people. Yeah, sure, sure. We agree we collect and and the same thing applies to identity.

58:09 As we go through life, we either openly grab pieces and bits and add them to ourselves. Kind of like a crab adorning its shell. Yeah, right. So, there is this. I remember this, like, not talk about burning too much, but I remember this, like, quintessential moment, this this old man, I don't remember, Bill. Bill. Evangelists remember him?

58:32 Do not. Anyway, he's the guy that did that. Humanity. I remember that, I mean that. Okay, so no, he had a he had like, a life philosophy that was loosely based on humanism. Okay? It was like a combination of humanism and utilitarianism. The but it was through the lens of, what do they call, psychotherapist?

58:54 He worked at a career, a sales career as a psychotherapist. I failed. Oh, yeah. Oh, yeah. And, because psychotherapy is a failed science. So what? You know, he went through the lens of he put his life through the lens of that and made all these conjectures about humanity is what were accurate insights. But really they were destructive, inaccurate tidbits of human nature that were wrong.

59:15 Damn. They use that as a foundation for an entire philosophy. And, I guess peddled this philosophy to his clients and. Yeah, and to like the people that would listen to him and, you know, there was like that kind of thing where you have this occasional gem in the shit, you know? Yeah. And so, like, every once in a while you would pull out a gem and then you, then you question the shit, you'd be like, well, maybe the shit isn't real shit.

59:37 Maybe there's more to this than I'm seeing, right? And then, like, for me, I did an intellectual dive into it to, to really see. And then I was like, wait a minute, now this ain't passing the smell test. And then reviewed it with him in for credible detail. Yeah. So I was trying to be assistive and he asked me to.

59:54 Oh shit. Okay. So he asked this. He said critique this, right. And so in doing so, you know, basically I'm uncovering the bullshit chain of logic, you know, like if A equals b b or c b and he has spent his life building A, yes, he's got an emotional investment in his reaction. Yeah. So like you can't pull on the bottom of one of the cards of the House of cards because, you know, happens.

1:00:18 Right, right. So that was his reaction. And he had all these like, mind fucked ways that he, he would go about, yeah. Justifying and defending because if he, if he were to yield and say, yeah, you're right. I see what you're saying. You would have to then redo every card above that event. Now, I mean, and he works.

1:00:40 He put too much investment into the total house of cards. I kind of look at it this way. I've had my House of cards topple a couple of times, and my main insight to that is you don't have to rebuild every card you had. Yeah, yeah, some cards you can pull out and nothing happens, right? Yeah. Some cards you can pull out, nothing happens.

1:01:01 Sometimes you realize, well, shit, I don't really need that card now. Yeah, see, we don't have an exhaustive amount of time to wiggle each card. Sometimes when you have such a massive house or just they just all topple and you have to figure it out. Yeah, well, in this case, there's such a huge time commitment in the in the thing, you know, in the total house of cards that there's like an actual threat of someone's really threatening, you know, some of those bottom cards, I mean, and guess and you're creative at it and you're creating it, right.

1:01:32 Not not even in your own mind. You don't even see it that way. Will turn right over here. All right. And you're in your own mind. You're not even seeing it that way. In your own mind. You're seeing it as he's wrong, right? Yeah. Like so. You know, if there's something that was so important that I had all these things sounded, you know, predicated on.

1:01:51 Yeah. And all these secondary ideas predicated on this one foundation right here. Your life's work. Seriously. Right. And then you're threatening that core. Yeah. Hell, yeah. I'm gonna I'm gonna find all kinds of creative way and all sorts of you say things like, you just don't understand, right? Right. You know, you're going to say because you're looking at the sum of your intellectual output, you're current, your creative output here, right?

1:02:18 Stakes. Right. Okay. And so when you challenge someone's Rube Goldberg Goldberg machine, you know, that they, they feel like is the right, mechanics, you know? Yeah. And that's really what we're building. We're we're accreting, we're selecting, we're adding to we're moving things in different directions. It's like. More or less everything we do helps securing our identity.

1:02:46 There you go. And, how do you how do you show somebody. Okay, so so back to my point. Is it this is how is this how it is able to show a team of programmers what's going wrong, like how what what's what's going wrong about this, this enduring approach and how we could do it differently. Right? Yeah.

1:03:04 It's I took the code that this guy made that has no experience. Whatever, no experience self-taught. So some of his code. Right. And I showed it and I a little now like cool. I showed the functionality of of his system that he made. Right. Yeah I showed the functionality like took 30 minutes to walk through what he created.

1:03:24 Okay, okay. So all the functionality and then I showed the code and I was really quickly can identify code all over the place that was, you know, extraneous or strings or not written appropriately. But then I also was able to show in totality with the amount of functionality versus the number of lines of code that this guy is beating.

1:03:45 Five college educated, trained programmers. So really his his line count was way lower, which you can't directly equate one coat with one coat, a long count with. Isabel. Ease of maintainability or ease of debugging. But if there's less lines, there's less to do that. Right? Yeah. Right. So he wasn't using get he wasn't using grants. He wasn't using, you know, I got Node.js.

1:04:15 Yeah. These all these libraries are just piled things upon, right? Dependencies upon him. Right, right, right. He wasn't using any of that. And I was like, look, I've never seen this code before, except for, you know, 30 minutes before I'm showing it to you. Right. And look, I can follow what's happening right here. Yeah, like like I can follow it.

1:04:33 I can see without even reading either comments. I know what it's for. I know why it's here. Right? And this one single page, granted, is, 4000 lines. Oh, shit. But here's where it connects to the database. Here's where it does this. Right. Hey, now let's contrast that to the software that we're making. Right? Like granted our software has about ten times the functionality.

1:04:57 Sure, but it has about 400,000 times the amount of code. Yeah. So something is has gone majorly wrong. Right? Right, right. And the answer is not let's find another library. No, no. The answer is simplify. Like, minimize like on steroids. Simplify, right. Yeah. And so on. That whole experience like, completely changed my philosophy. I started looking back over my code, realizing that I've made endless number of over machines.

1:05:24 Right, right. And that a lot of times your first pass, you know, or even your second pass, hey, you're still beginning to understand the problem space. Yeah. You know. Right. Right. So so that so last night. Right, while I was watching a movie, I was able from scratch to spin up an entire, interface to accept, inputs for bid items, including photos.

1:05:48 Nice. So they're having an auction at, my son's school raise money? Oh, yeah. So, they don't want to. They didn't want to pay the 5% to, some third party tool. Right. So, you know, like Sue volunteered me. Oh, she said, yo, my husband can make this right. Now, she doesn't realize I'm taking, 27 credit hours at school right now.

1:06:13 No shit. I was like, Sue, 27 credit hours, Nova social and a couple side projects and running, step in is, like, probably enough. Yeah, yeah, I'd say, but it's okay. So. But anyway. So like, now, right in one night, just not even okay in one night. Just half paying attention. You know, I was able to do that and the still probably still probably dramatically inefficient, you know, probably still.

1:06:42 Right. But it solves the problem and it brings all of your experience to bear. I would like to think learning. So I mean, more than likely, hey, it's a pretty damn good first pass because you've done many things that are analogous to it. Yeah. So also, you know, instead of instead of like thinking about, oh, how might this had been?

1:07:08 So instead of thinking about something, how might this software be used someday. Like now what functionality doesn't need? Yeah. You're looking at right now. What's the minimum? I hate to use it, but what's the minimum viable product. Right, right, right. No, it's okay to use a phrase like that when you're using for the APIs for like Grant, when it's actually applicable, not just to say that phrase right now just to get buzzword bingo.

1:07:37 Yeah, exactly. Mary told you about there. What? Oh, did I tell you about that? You know, literally doing buzzword bingo? No. Oh, shit. I did that with my friend John. You know John. Yeah, yeah, I did it with him and a couple other coworkers. I handed out buzzword bingo cards. Yeah. What was it over the whole week, you guys?

1:07:55 It it or win? No. Only one meeting. Oh, one meeting. One meeting. Yeah. Who got bingo. Oh, I think John did. That's awesome. There's a there was a sort of a star in the middle. I use the company logo. And then that was as free. Free as if you're free space. Yeah. And if the big boss probably ever saw that company logo using that manner.

1:08:16 Oh, yeah.

1:08:20 But as I was getting as I was getting terminated, I would say you used in a meeting. You weren't. You use the word fucking crunch. So therefore you have no fucking you can't say anything now. You can't say anything else. You said crunch in a fucking meeting. Oh, I haven't heard that in the meeting yet. I did look up the meaning when someone said it to me in jest.

1:08:42 I know the meeting. Yeah, I know the meaning. And I know the fucking guy that said it. Right. And he heard that at some other meeting and said, oh, oh, I can, I, can I. That sounded good, I don't know, I mean, my dear card, I don't know what that means, but I just looked it up and now I can use that word.

1:09:01 It is now part of my oh so broad lexicon. That's right. And I will have my minions put that word on my reports. Yeah.

1:09:12 That's the thing. So there's a fucking line of code if report. You know, if report four equals this person's name and fucking word turnip. Yeah. Don't use segment that they don't use, you know, the other sending in they use for everyone else's report. As for as that is there's an actual thing that happened. No. Yes. Yes yes.

1:09:31 You're not serious? I'm dead serious. You're like, this guy has a an election for this term. Let's fucking satisfy it. Yes, and I had it in the requirements. What the fuck? So it was actually called out? Yes. Specifically when the report is when this person logs into the system and generates this report instead of the usual word substitution.

1:09:53 Exactly. In this particular case, in this particular part of the Excel spreadsheet that it's creating, I mean, a huge system that was a front end to a database, okay, that created an automated series of reports that's telling you about that. Yeah, I put a lot of time into that, that shit. And I listen, that thing was spitting out killer gleaming fucking reports.

1:10:12 I'll tell you that much. I'll like you log into that system and I'll give you a report. That was exactly what you wanted to see. I know, to do your job. And, I had this, like, indirect authority, you know, like the. You have this competition between teams. Yeah, I think you're talking about it. Your job did. Oh.

1:10:28 Well, this other kind of group is pulling resources away, and so. Oh, yeah. Right. Infighting and resource grabs. Right. So so my Rube Goldberg machine is, is so fucking horribly terrible, but I've gotten a bunch of people in management to sign on to it to fight off. All right. Therefore it needs more resources. Right? I need to add the three boots that kick the ball down the track.

1:10:50 Right. And just add that in. Yeah. Right. And so, therefore our team needs more resources. It's all constrained to a bucket, you know, some kind of funding bucket. Right. And so then they say, oh, well, this hand security team over here doesn't need to have, you know, these virtual machines, Yeah. Yeah. So this person's recovered machine has created greater need.

1:11:08 Yes. Because I like it. And that's really it. Like that mousetrap. It's like, you know, you get buy in from the right people, you get a patron, so to speak. And you get a greater slice of the, resource resources. Yeah, yeah. So that happened is I was the management was, so rock hard over these, women listening reports that they started allocating more resources to them, you know, and so in that resource allocation became my, for me, a little more authority as well.

1:11:40 Well, yeah. Right. So I was able to then go to somebody and say, no, no, no. You know, management is making decisions on this data. So it cannot be it has to be accurate. Right? Right. You can't use zeros in place of null in way. You were able to clean up your data feeds. Right? Exactly. And you know, then play a much greater role in the meeting because, you know, I know that I learned quickly on my career that a visual is worth, you know, pictures of a thousand words than right.

1:12:06 And just trying to insert a small visual, visual can convince a whole room people. Yeah. You know, almost instantly. Right, right. So what I did was, showed the data set as it existed in real time at the meeting and then showed how on the report downstream that polluted the data. Right. So I showed the visual.

1:12:27 I said, here's the data as exists. Here's here's the final numbers that come in on this report. Okay. Here's the data as it should be. And here's the final number you need for data cleaning. Yes. It do. Yeah. In real in real time. Yeah. You know, because I pre-selected my data set. Yeah. So then I could just run a quick overlay.

1:12:44 You know, replace on the data, get rid of all these zeros and change them with nulls like they're supposed to be. Right? Right. And then when you do the average or whatever, your aggregate function is right, you're not getting the proper result. Yeah. Because everything's null terminated. And then put your hands on your hips and say management is making important decisions about this.

1:13:00 That's about there. So this the of course, of this, company. Right. Put your hands on your hips and start with a g force company and be like, you know, management is making decisions on this information, and it has to have this level of accuracy. Yeah. Right. And no, I'm not going to be the one that that real time filters it every time in my system.

1:13:21 Because when the same data goes into another system that then producing the incorrect result which is then feeding back, there we go. We need to clean up the feed. And now right. And so we can't have we can't have managements getting the same value from two separate reports. And that would be different. It has to be, it has to match.

1:13:35 So the source data has to be cleaned up in this way. Yeah. Right. Oh he's smart. Yep. Oh yeah. Genius. He knows that. Ever seen zero? No. Right, right. But what a genius. Here's the thing it's about. Let's see. Ability to communicate it right. People in the right way. That's the genius part. All you do is just show the the effects like right, right, right.

1:14:01 But it's it's a it's a bunch of things. It's like, you know, your, It's just, you know, your you had the balls to communicate it. You had the ability to communicate it. You were able to knock up a presentation and data transforms and everything else, a bunch of little things. Yeah. And then you look back and you're like, that's all my life is being, you know, you.

1:14:28 I saw why you had started a nonprofit and decided to be your own ball. Area off, which is not the same outcome. Like say, oh, Ozzie. No, it won't be, because at least you'll be in love with the Rube Goldberg shame that you create. For every person.