WEBVTT

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You know, usually when we talk about diagnosing

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a problem, like say a medical diagnosis, there's

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this expectation of precision. Right. It feels

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clean. Very objective. Yeah, exactly. You break

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your arm, the x -ray shows that jagged white

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line, the doctor points to it, and that's it.

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You know exactly what's wrong. And you know exactly

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what needs to be fixed. We really do like things

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to be visible. you know, to be categorized easily.

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Well, the human brain craves that kind of binary

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simplicity. I mean, it is either broken or it

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is not broken. Right. But then you step into

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the world of software development or really any

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complex system management, and you are staring

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at a product with hundreds of thousands of users.

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Oh yeah, suddenly that pristine x -ray machine

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is completely useless. Totally useless. Yeah.

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You are looking at a diagnostic landscape that

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is entirely chaotic. Because you've got this

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massive segment of users screaming on social

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media about like a typo on the homepage. Exactly.

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While somewhere deep in the server, a silent

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error is slowly corrupting critical financial

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data. And when every single dashboard is flashing

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red and every user thinks their specific problem

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is the absolute end of the world. Which they

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always do. Right, they always do. Relying on

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intuition or just the volume of complaints is

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a guaranteed way to fail. You need a mechanism

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to decide what actually needs your attention

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first. Without letting panic... dictate the workflow.

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And, you know, that is the exact chaos we are

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cutting through today. Welcome to this deep dive.

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Glad to be here for this one. It's a fun topic.

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It really is because today we are cracking open

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a highly specific mathematical framework used

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by software testers. It's used to bring objective

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order to that exact kind of overwhelming situation.

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And I have to say, the single source we're using

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today is beautifully ironic. Oh, it's so good.

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We are pulling from a Wikipedia article simply

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titled Defect Criticality. It is a phenomenal

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example of a text embodying the very problem

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it is trying to solve. It really is. Because

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think about it. It's an article entirely about

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software quality control, right? About identifying,

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prioritizing, and fixing flaws. But the article

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itself is flagged by Wikipedia for having its

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own glaring defects. It's incredible. At the

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very top, it is plastered with these warning

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banners. One says it has been lacking citations

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since April 2015. A whole decade ago. Yeah. And

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the other banner says it has had unclear notability

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since August 2025. It is an article about identifying

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flaws, wearing its own flaws right on its sleeve.

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Yet, despite those warnings, the actual text

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contains a remarkably elegant, masterclass -level

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framework for triage and prioritization. Exactly.

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So, our mission today is to extract this specific

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framework and show you how it can completely

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change how you look at problem solving. And not

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just in code, but in your own daily life. Okay,

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let's unpack this. What exactly is this metric?

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And how does it separate the noise from the actual

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emergencies? Well, what's fascinating here is

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that the framework physically prevents developers

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from just fixing what is annoying the loudest

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customer. Which is human nature, right? Yeah.

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To just make the yelling stop. Totally. But defect

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criticality, officially, is a metric used in

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software quality assessment to quantify the potential

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impact of a software defect. So it translates

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a feeling of panic into a hard, objective number.

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Exactly. And that number is generated by a very

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specific master formula. Criticality equals severity

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multiplied by likelihood multiplied by class.

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Severity times likelihood times class. Okay,

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when I first read this formula, it instantly

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reminded me of medical triage in an emergency

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room. Oh, that's a great way to look at it. Right.

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Imagine you are the triage nurse standing in

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front of a packed waiting room. You don't just

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treat the person who is crying the loudest. Because

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that might just be a stubbed toe. Exactly. And

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you don't just take people in the order they

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walk through the door. You evaluate three distinct

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things. First, what system is failing? Is it

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the heart or is it a scraped knee? That's the

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class. All right. Makes sense. Second, how badly

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is it failing? Is it a total arterial blockage

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or just a minor palpitation? That is the severity.

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Right. And third, how much of the body is affected?

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That is the likelihood. The ER analogy works

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beautifully, but with one major caveat that makes

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software triage even harder. In software, the

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patient is a million people at once. Oh, wow.

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Yeah, I guess that's true. You aren't just looking

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at one failing heart. You are looking at a million

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scraped knees simultaneously. That sounds like

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a nightmare. It is. And because human beings

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are incredibly visual creatures, a very common

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trap in problem solving is confusing how bad

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it looks with how critical it actually is. I

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do that all the time. We all do. You might have

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a massive garish error message that pops up on

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the screen, taking up the whole display. It looks

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terrifying to the user. Like the whole computer's

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melting down. Exactly. But technologically, it

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might only be affecting a tiny cosmetic teacher.

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While at the same time, a tiny line of invisible

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code is quietly calculating tax percentages wrong

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for every user in the database. Precisely. And

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if you don't forcibly separate class, severity,

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and likelihood, human nature guarantees you will

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panic over the ugly error message. And completely

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miss the silent data corruption. Exactly. This

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three -pronged mathematical approach forces the

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developer to decouple their visual -emotional

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reaction from the objective reality of the failure.

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OK, so relying on the causality of this framework,

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we have to start by defining the ecosystem of

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the failure itself. Right, the foundation. According

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to the source, you cannot even begin to score

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how bad an issue is until you define its fundamental

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context. Every single defect must first be assigned

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a class. Yeah. The class defines the domain of

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the defect. It answers the foundational question,

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what kind of issue is this? The framework breaks

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this down into distinct tiers, starting at zero,

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and class zero is reserved for critical system

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-level survival. Like the servers are on fire?

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Literally or metaphorically, yeah. This includes

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stability, reliability, availability, and security.

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It also covers storage, specifically preventing

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data loss or corruption. Here's where it gets

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really interesting, though, because the source

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states that Class Zero also includes legal issues.

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It does. Liability, ADA compliance for accessibility,

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and copyright infringement. Essentially lumps

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losing user data in with getting sued over a

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stolen image. Yep, they share the exact same

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rank. I have to admit, that threw me. I mean,

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why is a legal liability treated mathematically

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the same as a server literally catching on fire?

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That legal inclusion is usually what trips people

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up. But think about it from the perspective of

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the application's actual survival in the real

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world. OK. A bug isn't just bad code. It is a

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mechanism that interacts with society. Oh, I

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see what you mean. Right. If your software isn't

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Adyay compliant or you are accidentally displaying

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copyrighted material, a judge can issue an injunction

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that pulls your application offline completely.

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Oh, wow. So from the user's perspective, the

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app being legally banned from the App Store is

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functionally identical to the server's crashing.

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The result is exactly the same. The system ceases

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to exist. Therefore, it is a foundational class's

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existential threat. That is a massive perspective

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shift. It forces the engineer to step out of

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the code and look at the actual business consequences.

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Which engineers don't always naturally do. Right.

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OK, so class EO is life or death. Once you move

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past that, the framework essentially starts measuring

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different levels of friction. Exactly. Instead

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of reading down the entire list sequentially,

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let's look at how Classes 1, 2, and 3 behave.

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They cover everything from a sluggish loading

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screen, to a future doing the wrong math, to

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a frustrating user interface. The system isn't

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dying, but it is making the user's life progressively

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more difficult. And these middle tiers represent

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the bulk of everyday software issues. Oh, absolutely.

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Class 1 deals with performance. The software

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works, but it's hogging all your computer's memory.

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Classic. down to logical correctness. So the

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math is wrong or the system isn't talking to

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other software properly. Okay, got it. And then

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Class 3 drops further down to user experience

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and workflow. The menus are confusing or the

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documentation is poorly written. And notice how

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far away we are getting from actual systemic

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collapse. We're miles away from it. But a massive

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percentage of angry user complaints live right

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here in Class 3. Right, because they are frustrated

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because the workflow is clunky, but their actual

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data is perfectly safe. Exactly. Which brings

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us to the absolute bottom of the barrel, Class

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4. Presentation and cosmetic defects. Typographical

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errors, grammatical mistakes, aesthetics, or

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visual cosmetic issues. Basically, a typo is

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rock bottom. And that rock bottom ranking is

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completely intentional. But the source text lays

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out a crucial rule for how class interacts with

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everything else. And it is vital to understand.

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Later. The class provides the unbreakable context

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for evaluating the symptom. Meaning what exactly?

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Well, for example, a class is your issue. Let's

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say a critical stability flaw that only presents

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with a minor visual symptom must still be treated

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more seriously than a class 4 cosmetic issue

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with the exact same visual symptom. Can you give

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me a concrete example of how that plays out in

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reality? Sure. Imagine a user reports that a

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specific button on the dashboard flickers for

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half a second when they log in. Okay. Visually,

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it is just a flicker. Right. Now, if the developers

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investigate and realize that Flickr is caused

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by a simple CSS coding typo, it is a class four

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aesthetic bug. It is a super low priority. Makes

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sense. But what if they investigate and realize

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that the flicker is happening because the backend

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server is quietly rebooting itself and nearly

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crashing every time someone logs in? Oh, wow.

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And the flicker is just the visual artifact of

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that near collapse. And the symptom is identical,

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but the disease is entirely different. Exactly.

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You do not treat the symptom, you treat the underlying

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class of the disease. So the framework forces

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developers to investigate the root cause rather

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than just slapping a visual bandaid on a flickering

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button and Exactly. It prevents lazy debugging.

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But knowing that a bug is a fundamental security

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flaw doesn't necessarily tell the developers

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how much it is actually hurting the user right

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now, in this given moment. No, it doesn't. That

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requires a totally different metric, which brings

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us to the second piece of the formula. Severity.

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Right. Severity measures the degree to which

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the defect affects the users or the system operation.

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And the way this scale is structured is totally

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fascinating to me. It's entirely built around

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the concept of the workaround. It really is.

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A severity zero means the defect affects critical

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data or functionality and leaves the user with

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absolutely no workaround. They're dead in the

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water. Totally paralyzed. They cannot do their

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job. But the moment a workaround exists, the

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severity drops. A severity 1 still affects critical

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functionality. but it forces the user to employ

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a workaround. Right. They can still barely get

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by. And the middle tiers, severity two and three,

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they also heavily factor in whether a workaround

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is forced or available for non -critical functions.

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And finally, severity four purely affects aesthetics

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and doesn't hinder functionality at all. I have

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to push back on this reliance on the workaround,

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though. Oh, how so? Well, isn't a broken feature

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still fundamentally broken? I mean, if I buy

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a brand new car and the driver's side door is

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jammed shut, but I can technically climb in through

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the passenger side, the car is still broken.

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That is a very fair point. Right. Why does the

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mere existence of a workaround change the mathematical

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severity score so drastically that it drops it

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out of the highest emergency tier? Well, if we

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connect this to the bigger picture, it reveals

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the true pragmatic philosophy behind this entire

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metric. Which is? The framework acknowledges

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a harsh reality. Engineering resources are finite.

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Ah. You simply cannot fix everything at once.

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You can't. You have a limited number of developers

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and a limited number of hours. So the inclusion

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of the workaround acts as a vital pressure valve

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for the team. So it's not about whether the user

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is annoyed. It's about whether they are completely

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paralyzed. Exactly. If the office worker can

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still export their broken data to Excel... fix

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it manually, and re -import it to get their report

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done, they are going to be miserable. They're

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essentially climbing through the passenger door

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of the car. Perfectly said. But they are not

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entirely blocked from operating. That workaround,

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as exhausting as it is for the user, buys the

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developers the one thing they need most during

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a crisis. Yes. Time. It drops a severity zero

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down to a severity one. It acknowledges the human

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reality of using the system and prioritizes the

00:12:45.330 --> 00:12:47.909
people who are truly dead in the water over the

00:12:47.909 --> 00:12:50.309
people who are merely severely inconvenienced.

00:12:50.429 --> 00:12:53.330
That is incredibly pragmatic. It is triage in

00:12:53.330 --> 00:12:56.250
its purest form. Right. Okay. So we have the

00:12:56.250 --> 00:12:58.350
class, which tells us what is broken. Right.

00:12:58.389 --> 00:13:00.649
We have the severity, which tells us how badly

00:13:00.649 --> 00:13:03.169
it is disrupting the workflow. Now we need the

00:13:03.169 --> 00:13:05.919
final piece of the formula. Likelihood Crowd

00:13:05.919 --> 00:13:08.740
Exactly. How many people are actually experiencing

00:13:08.740 --> 00:13:11.100
this pain? The likelihood measures visibility.

00:13:11.389 --> 00:13:13.649
And instead of reciting the specific percentage

00:13:13.649 --> 00:13:16.370
brackets, the core concept is understanding the

00:13:16.370 --> 00:13:18.950
scale of exposure. A likelihood of one means

00:13:18.950 --> 00:13:21.389
the defect is highly visible, encountered by

00:13:21.389 --> 00:13:24.169
95 % or more of the user base. It's front and

00:13:24.169 --> 00:13:26.549
center. Everyone sees it. Right. On the opposite

00:13:26.549 --> 00:13:28.690
end, a likelihood of four means it is buried.

00:13:29.129 --> 00:13:31.789
It is seen by fewer than a third of users, perhaps

00:13:31.789 --> 00:13:34.529
hidden deep in a rarely used settings menu. But

00:13:34.529 --> 00:13:36.850
wait, why is likelihood treated as a separate

00:13:36.850 --> 00:13:39.789
multiplier at the end? If a huge volume of users

00:13:39.789 --> 00:13:42.669
are screaming about an issue, doesn't that inherently

00:13:42.669 --> 00:13:45.389
make it a severe problem that should be prioritized?

00:13:45.629 --> 00:13:47.870
Well, this is where the framework protects developers

00:13:47.870 --> 00:13:50.610
from the vocal minority, particularly in the

00:13:50.610 --> 00:13:53.190
age of social media. Oh, that makes sense. Right.

00:13:53.789 --> 00:13:56.970
A thousand angry users posting online feels like

00:13:56.970 --> 00:13:59.470
a massive system -wide failure. It feels like

00:13:59.470 --> 00:14:01.350
a likelihood of one. It feels like everyone.

00:14:01.500 --> 00:14:04.919
But if your software has 10 million active users,

00:14:05.500 --> 00:14:08.159
those thousand angry voices represent a fraction

00:14:08.159 --> 00:14:10.299
of a percent of your user base. It is actually

00:14:10.299 --> 00:14:12.659
a likelihood of four. That's a huge difference.

00:14:12.740 --> 00:14:15.360
It is. By forcing the developer to calculate

00:14:15.360 --> 00:14:18.240
the actual mathematical percentage of users affected,

00:14:18.700 --> 00:14:21.299
it strips away the psychological pressure of

00:14:21.299 --> 00:14:23.960
the loud crowd. It forces you to look at the

00:14:23.960 --> 00:14:26.500
silent majority. So what does this all mean when

00:14:26.500 --> 00:14:28.360
we put the pieces together? We have our three

00:14:28.360 --> 00:14:31.659
numbers. Class. severity, and likelihood. And

00:14:31.659 --> 00:14:34.000
the formula dictates that we multiply them together

00:14:34.000 --> 00:14:36.299
to get our ultimate defect criticality score.

00:14:36.740 --> 00:14:40.340
Right. The exact ranges of the resulting matrix

00:14:40.340 --> 00:14:42.779
don't matter as much as how the math manipulates

00:14:42.779 --> 00:14:45.720
the extremes. Let's look at the cosmetic typo

00:14:45.720 --> 00:14:48.919
on a rarely used screen. OK. A typo is cosmetic,

00:14:49.299 --> 00:14:51.879
making it a class 4. Yep. It's a minor aesthetic

00:14:51.879 --> 00:14:54.740
issue, so it's a severity 4. And it's on a rarely

00:14:54.740 --> 00:14:57.149
used screen, giving it a likelihood of 4. So

00:14:57.149 --> 00:15:00.009
you multiply 4 times 4 times 4, and the formula

00:15:00.009 --> 00:15:03.110
multiplies out to 64. Which mathematically banishes

00:15:03.110 --> 00:15:05.529
it to the very bottom tier of the priority list.

00:15:05.629 --> 00:15:08.070
It becomes a low criticality defect. And that

00:15:08.070 --> 00:15:10.730
mathematical banishment is so necessary because

00:15:10.730 --> 00:15:13.429
human nature dictates that developers will actually

00:15:13.429 --> 00:15:15.429
want to fix that typo first. Oh, absolutely.

00:15:15.590 --> 00:15:18.399
It is the trap of the quick win. Right. Fixing

00:15:18.399 --> 00:15:20.519
a typo takes 30 seconds. It gives the developer

00:15:20.519 --> 00:15:22.679
a quick dopamine hit of accomplishment. They

00:15:22.679 --> 00:15:25.080
can close a ticket and feel productive. But spending

00:15:25.080 --> 00:15:28.000
time fixing a typo while a complex, difficult

00:15:28.000 --> 00:15:30.919
database error sits untouched is terrible resource

00:15:30.919 --> 00:15:34.000
management. The math forces the score so high

00:15:34.000 --> 00:15:36.639
that the developer is essentially forbidden from

00:15:36.639 --> 00:15:39.240
prioritizing the easy work over the important

00:15:39.240 --> 00:15:42.159
work. I love that. But the true brilliance of

00:15:42.159 --> 00:15:45.139
this formula lies in a specific mathematical

00:15:45.139 --> 00:15:47.740
quirk at the other end of the spectrum. Oh, the

00:15:47.740 --> 00:15:50.899
zero multiplier. Yes, because the formula relies

00:15:50.899 --> 00:15:54.919
entirely on multiplication. Any zero in the equation

00:15:54.919 --> 00:15:57.620
acts as an absolute override. Because if you

00:15:57.620 --> 00:16:00.179
multiply anything by zero, the result is zero.

00:16:00.379 --> 00:16:03.080
Exactly. So if an issue is a class zero data

00:16:03.080 --> 00:16:05.879
thread or a severity zero blockage, the final

00:16:05.879 --> 00:16:08.519
criticality score automatically becomes zero.

00:16:08.700 --> 00:16:10.940
And this raises an important question about how

00:16:10.940 --> 00:16:13.379
we design systems to protect their core functions

00:16:13.379 --> 00:16:16.679
against human bias. How so? Well, this mathematical

00:16:16.679 --> 00:16:19.820
quirk is not a mistake. It is an automatic, non

00:16:19.820 --> 00:16:22.299
-negotiable circuit breaker. OK, give me an example.

00:16:22.679 --> 00:16:25.240
Let's say you discover a class zero defect, a

00:16:25.240 --> 00:16:27.840
massive security hole that exposes user passwords.

00:16:27.879 --> 00:16:30.679
Horrifying. But it is buried so deep in legacy

00:16:30.679 --> 00:16:33.200
code that only one single user out of a million

00:16:33.200 --> 00:16:35.700
will ever accidentally trigger it. That is a

00:16:35.700 --> 00:16:38.419
likelihood of four. Extremely rare. But because

00:16:38.419 --> 00:16:40.519
it's a class zero, the math is zero multiplied

00:16:40.519 --> 00:16:43.320
by four. The result is zero. Exactly. It forces

00:16:43.320 --> 00:16:46.320
the final score into the top tier critical category.

00:16:46.679 --> 00:16:49.659
So the math demands that it be treated as an

00:16:49.659 --> 00:16:51.940
absolute emergency, regardless of how few people

00:16:51.940 --> 00:16:54.379
are actually experiencing it. It physically prevents

00:16:54.379 --> 00:16:57.220
the developers from saying, well, hardly anyone

00:16:57.220 --> 00:16:59.799
uses that feature, so let's just ignore the security

00:16:59.799 --> 00:17:02.600
leak. Wow. It prevents the crowd from dictating

00:17:02.600 --> 00:17:05.099
the safety of the system. It brings us right

00:17:05.099 --> 00:17:08.039
back to that emergency room analogy. The triage

00:17:08.039 --> 00:17:11.079
nurse isn't fooled if a patient having a massive

00:17:11.079 --> 00:17:13.720
internal hemorrhage happens to be sitting quietly

00:17:13.720 --> 00:17:15.839
in the corner. Invisible to the rest of the room.

00:17:15.900 --> 00:17:18.859
Right. invisible while 50 other people in the

00:17:18.859 --> 00:17:20.819
waiting room are loudly complaining about sore

00:17:20.819 --> 00:17:24.960
throats. The formula acts as the ultimate objective

00:17:24.960 --> 00:17:28.039
triage nurse. It really does. It identifies the

00:17:28.039 --> 00:17:31.420
silent but deadly systemic failures and pushes

00:17:31.420 --> 00:17:33.480
them straight to the operating table completely

00:17:33.480 --> 00:17:35.680
overriding the noise around them. And conversely

00:17:35.680 --> 00:17:38.000
it stops you from rushing a patient into emergency

00:17:38.000 --> 00:17:41.690
surgery just because they have a very loud, very

00:17:41.690 --> 00:17:44.089
visually disturbing, but ultimately completely

00:17:44.089 --> 00:17:47.069
harmless cosmetic rash. It forces you to allocate

00:17:47.069 --> 00:17:49.809
your limited energy entirely toward what sustains

00:17:49.809 --> 00:17:52.049
the life of the system, which is exactly why

00:17:52.049 --> 00:17:55.250
this deep dive is so valuable. We took a seemingly

00:17:55.250 --> 00:17:58.789
dry, ironically flawed Wikipedia article about

00:17:58.789 --> 00:18:01.809
software testing and uncovered a total master

00:18:01.809 --> 00:18:05.430
class in decision making. It's surprisingly universal.

00:18:05.630 --> 00:18:08.269
It is. You can take this exact formula class,

00:18:08.549 --> 00:18:11.569
severity, likelihood, and apply it to your own

00:18:11.569 --> 00:18:14.269
life the second this audio finishes. Totally.

00:18:14.569 --> 00:18:17.250
When you look at your overwhelming email inbox

00:18:17.250 --> 00:18:20.269
or your massive to -do list or a complex challenge

00:18:20.269 --> 00:18:22.509
at work, you don't have to feel paralyzed by

00:18:22.509 --> 00:18:24.589
the sheer volume of demands. You don't have to

00:18:24.589 --> 00:18:27.029
just react to whichever client or problem is

00:18:27.029 --> 00:18:29.670
yelling the loudest. You can stop, assign a class

00:18:29.670 --> 00:18:32.190
to understand the domain, rate the severity based

00:18:32.190 --> 00:18:34.670
on actual blockage, calculate the likelihood

00:18:34.670 --> 00:18:37.210
of impact, and let the objective math do the

00:18:37.210 --> 00:18:39.769
heavy lifting for you. It is an incredibly powerful

00:18:39.769 --> 00:18:42.589
tool for reclaiming your clarity. But before

00:18:42.589 --> 00:18:44.250
we wrap up today, I want to leave you with one

00:18:44.250 --> 00:18:46.289
final thought to mull over as you apply this

00:18:46.289 --> 00:18:48.809
framework to your own world. Go for it. We talked

00:18:48.809 --> 00:18:51.769
at length about how a workaround drops the severity

00:18:51.769 --> 00:18:54.569
of a problem. It buys developers time, but it

00:18:54.569 --> 00:18:57.450
leaves the underlying issue completely unresolved.

00:18:57.450 --> 00:19:01.259
Right. If you applied this exact defect criticality

00:19:01.259 --> 00:19:03.579
formula to the everyday frictions, stresses,

00:19:03.920 --> 00:19:06.619
and systemic problems in your own life, what

00:19:06.619 --> 00:19:08.940
silent class zero issues have you been completely

00:19:08.940 --> 00:19:11.339
ignoring simply because you managed to find an

00:19:11.339 --> 00:19:13.960
exhausting temporary workaround? Wow. That is

00:19:13.960 --> 00:19:15.660
something to think about. Until next time, keep

00:19:15.660 --> 00:19:16.200
digging deeper.
