CZM Rewind: The Truth About Software Development with Carl Brown

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Speaker 22 Hello, and welcome to Better Offline. I'm your host, Ed Zetron.

Speaker 22 Today, I'm joined by Carl Brown, a veteran software engineer and host of the excellent YouTube channel Internet of Bugs.

Speaker 23 Carl, thank you for joining me.

Speaker 2 Thanks for having me.

Speaker 22 So, I'm going to start with an easy one. What is a software developer? Like, what actually is that?

Speaker 24 So, basically, what we do is we take

Speaker 24 ideas about

Speaker 24 problems that people want to solve generally,

Speaker 24 and we

Speaker 24 write

Speaker 24 software, we write code

Speaker 24 that tells computers instructions how to make the computer do

Speaker 24 the thing that needs to do to solve the problem the person asked us to solve. Right.

Speaker 24 Gaming programming is a little bit different, but that's most software development is basically that.

Speaker 22 And this is another quite silly question, but necessary. How much of that is actually writing code?

Speaker 24 It depends on how good

Speaker 24 you're the people that are asking for stuff is as a general rule I would say maybe

Speaker 24 between 10% and 25%

Speaker 22 okay just really want to be 10 to 20

Speaker 22 even if we say 30% of the job which is more than you said that means the majority of this job is not actually writing code right now that's that's largely for for folks that are farther up the chain, right?

Speaker 24 So if you're fresh out of school and you don't really, you're not in the job, in the, you don't understand how to manage requirements or any any of that kind of stuff yet.

Speaker 24 Someone's going to basically hand you a thing to do. And in that kind of case, you're going to be spending a lot more time writing code than that.
But for me, it's, you know, it's far, far more

Speaker 24 talking to people and stuff than actually writing code.

Speaker 22 Right. And the reason I asked that, and the reason we're doing this as well is that there have been a lot of stories around like LLMs replacing coders, LLMs replacing engineers,

Speaker 22 claiming that junior software engineers will be a thing of the past due to LLMs. How much validity is is there in that?

Speaker 24 Well, when it comes to the really, really, really fresh out of school kids, right?

Speaker 24 That you have to basically break everything down and hand them little, little chunks of work, an LLM can kind of do that, although the kid will get better over time and the LLM is pretty much fixed, right?

Speaker 24 Right.

Speaker 24 But past that,

Speaker 24 it doesn't do a good job of being able to do any kind of long-term thinking.

Speaker 24 And that's largely the job, right? I mean,

Speaker 24 this is not a set of, you know,

Speaker 24 I come in today, I do a thing today, I come in tomorrow having no understanding of what happened yesterday and do another self-contained thing and so on and so forth, right? That's not the job.

Speaker 24 The job is a long sequence of building up on things day after day after day after day until we get to the point where the whole thing together works and does what it's supposed to do. So

Speaker 22 I think that I've noticed, and one of the reasons I had you on as well is that really, there are so many of these stories.

Speaker 22 They're claiming that like the software engineer's job is gone, that these companies will be writing all of their code with AI. And it doesn't even seem like that is possible.

Speaker 22 One of your videos, you did a really good thing around like the 20 to 30%, I linked to this in the notes, 20 to 30% of code behind Meta, and I think Google it was, is written by AI now.

Speaker 22 Again, how much validity is there to that?

Speaker 24 Well, I mean, so if.

Speaker 24 One of the quotes was something to the effect of 30% of the code is suggestions that were given by autocomplete that a human accepted, right? Right. Which could be as much as, you know,

Speaker 24 the thing said, oh, wait, you spelled this wrong. Let me give you a suggestion about how to spell it correctly, right? I mean,

Speaker 24 how much of the actual text that you write is, you know, is corrected by a spell checker, right? If all that counts as AI, then what percent of your stuff is written by AI, right? Well,

Speaker 22 in my case, absolutely nothing, but that's just a freak. I'm just a complete freak.
But no, I get your point.

Speaker 22 And it's without being a coder myself, it's something I've really noticed across these stories where people just kind of blindly push them out and they say, oh, yes, 20 to 30% of the code is written by, but there's no verifying this.

Speaker 22 And also, it feels like it might create a bigger problem, which is, say we accept this idea, even though I don't, and it sounds like a pretty spurious one, kind of silly to do so.

Speaker 23 At some point, Isn't code not just the series of things that you write to make a program work? It's connected to a bazillion other things, which

Speaker 23 if you don't know why that was written, because you had something generate it, is that not a huge problem?

Speaker 24 Yes, but worse,

Speaker 24 what we're finding when code gets generated is that basically you end up doing the same thing in a bunch of different places, but in each one of those different places, you do it a different way.

Speaker 22 Can you give me an example?

Speaker 24 So, for example,

Speaker 24 when you need to go fetch a thing from a server, right? Well, over here in this code, you fetch a thing from a server. Over here in the code, you fetch a different thing from the server.

Speaker 24 Normally, you'd be able to use the same block of code to do that. So if there's a mistake in it, you can change it once and it's fixed everywhere, right?

Speaker 24 But the way the LLMs work is you say, hey, I want to fetch a thing from the server, and it says, cool.

Speaker 24 And it writes a whole thing for you that may or may not work the same way as the previous one, right? And so now

Speaker 24 you find, okay, under some circumstances, we're having a problem fetching things from the server.

Speaker 24 I don't know which one of these 12 implementations that go fetched from the server is the one that's actually causing the problem. Right.
Also,

Speaker 22 isn't isn't there a security issue of having large language models? Like, like, wouldn't all the code be quite similar?

Speaker 22 Or at least more similar, depending on if everyone's using Claude or everyone's using, well, GitHub Copilot, I guess, is Claude now.

Speaker 24 No, not really. It basically kind of picks a random number at the beginning and goes, okay, so that's the, I think of it kind of like you deal a deck of cards, right?

Speaker 24 Whichever deck of card gets turned over first, that's the beginning of the autocomplete that it starts.

Speaker 24 And so depending on which example it's, I don't want to say thinking of, but depending on which example represents that,

Speaker 24 I'm drastically oversimplifying, but depending on which example is represented by that card, it's going to go down one path or another.

Speaker 22 Right.

Speaker 22 And so, what are they actually large language model coding tools actually good for? Because I get a lot of people who respond by saying, This is proof that AI is a big deal.

Speaker 22 And I'm just kind of like, I'm not even looking for a particular answer. I'm just truly, what's useful about them?

Speaker 24 So, they are decent at when you know what you want, and what you want is a fairly simple self-contained thing

Speaker 24 and you know how to tell whether or not the self-contained thing does what you want, it can type it faster than you can.

Speaker 24 Like autocorrect. Basically, yes.
It's like autocomplete.

Speaker 24 If you know exactly what you want, yeah. I mean, so I use it a lot because I program in a bunch of different programming languages a lot, right?

Speaker 24 On different projects at the same time or on the same day or the same week. And it's really easy for me to go, okay, wait, which language am I in right now?

Speaker 24 Okay, how do I do this in this language, right?

Speaker 22 So it's kind of like you can actually understand the generation, though, when it comes to that.

Speaker 24 Yeah, it's like I know what kind of loop I want, but I don't remember the syntax for this particular language where I don't want to.

Speaker 24 So it's, I use it kind of like a Google Translate kind of thing to go from one programming language to another sometimes.

Speaker 22 But you wouldn't trust it to build a full software package?

Speaker 24 Oh, not at all.

Speaker 22 Why not?

Speaker 24 Well, it wouldn't work to start with. Why wouldn't it work? Well, I mean, so I've done some experimentation on that where I've taken fairly complicated

Speaker 24 challenges. Challenges that were intended for programmers to basically get better at their craft and that kind of thing.
And I've run AI, you know, told it step by step, okay,

Speaker 24 the challenge says this is your next step, do this. The challenge says, this is your next step, do this.

Speaker 24 On really simple challenges in programming languages like Python that it's got a lot and a lot of examples for, it does okay.

Speaker 24 past the point where you're in the really simple kind of language things, they just, they sometimes get to the point where they can't even create anything that builds at all. Huh.

Speaker 22 Why is there, why do so many engineers swear by it then?

Speaker 24 Honestly, I'm not sure to what extent the engineers are swearing by it. I've talked to a lot of folks who are like, you know, my group, you know, this big bank, you know, friend of mine,

Speaker 24 my group is getting co-pilot jammed on our throats whether we want it or not. And the executives are all really excited about it, and none of us are.

Speaker 22 Interesting. So it's executive.

Speaker 22 I've personally had this theory that it's like executive pushed and that it's all about, it's all about what the bosses want to see rather than even do. Sorry, no.

Speaker 22 It's time to move my cat out of the way.

Speaker 24 There's a lot of wish fulfillment. There's a lot of like, we want to not have to deal with these programmers anymore.
So we would rather deal with the AI thing.

Speaker 24 And we're just going to hope that the AI thing is going to be, you know, just as good as the programmers or close to, it's just as good as the programmers and not nearly as annoying.

Speaker 22 Seems Seems like a definitional, well, maybe that's not the right word.

Speaker 22 Seems like the difference between a software engineer and a software developer almost, because it's not just about flopping code out. It's about making sure the code does stuff.

Speaker 24 Yeah, I mean, those, those terms get

Speaker 24 mashed together. Yeah, I mean, so part of the problem is that in, it's like, I live in Texas, and in Texas, you're not allowed to call yourself an engineer unless you've passed the engineering exam.

Speaker 24 Huh.

Speaker 24 Right. So

Speaker 24 I can't literally, I literally can't call myself a software engineer legally in Texas, as I understand understand it. I'm not a lawyer, but that's my understanding.

Speaker 24 So it's like the terms get all confused.

Speaker 22 Right. So, somewhat related.
What is it that people misunderstand about the job then?

Speaker 24 Well, I mean, so one of it is what you said earlier, which is that a very small percentage of the job is actually slinging code.

Speaker 24 A lot of it is basically trying to figure out what it is the code should do based on what you've been told that the problem, you know,

Speaker 24 the solution to the problem that you're trying to solve.

Speaker 24 Another thing is that

Speaker 24 a lot of

Speaker 24 the problem with the job

Speaker 24 is that every little decision builds up over time. And at some point, a bug is going to happen.
They're inevitable.

Speaker 24 And when that happens, basically, there's this process where what you need to do if you're being competent is roll back through those series of decisions, figure out what caused that bug, and then figure out what other bugs are likely to have been caused by that same set of decisions, and then fix not just the bug you're working on, but the bugs that, you know, not just the bug that's been reported, but the bugs that might have also been caused by the same problem, right?

Speaker 24 And that kind of long-term thinking is not a thing I've ever seen an LLM exhibit at all.

Speaker 24 I talk about it like LLMs or, you know, generative AI is good at solving riddles, but actual software development is more like solving a murder.

Speaker 22 Yes, you said that in that wonderful video. Yeah.

Speaker 22 And

Speaker 22 it almost feels as if we are building towards an actual calamity calamity of sorts. Maybe not an immediate one.

Speaker 22 Maybe it'll be kind of sectioned off into areas because you've got a new generation of young people coming into software engineering or what have you, learning to use AI tools rather than, your videos definitely talk about this as well, actually how to develop software and make sure it works and make sure that it has the infrastructural side in line.

Speaker 22 And also that you're building it with the long-term thinking of someone else might need to understand how this works. And they're not learning that.

Speaker 22 So you've just got a generation of kind of pumping the internet and organizations with sloppier code.

Speaker 24 Yes, although, I mean, one of the problems we're having at the moment is that the hiring process for really junior engineers is actually pretty broken at the moment.

Speaker 24 And a lot of people are not hiring people that are fresh out of school because they're expecting that the AI will be able to do that.

Speaker 24 Basically, a senior or a mid-level developer with the benefit of AI, with the benefit of AI, that's in air quotes, quotes,

Speaker 24 will be able to do the work of that person plus a couple of fresh outs that they normally would have hired, but they're not hiring at the moment.

Speaker 24 There's some statistics about how the people that are fresh out of school these days are historically

Speaker 24 underemployed relative to the general population, at least in the US where I live.

Speaker 22 It also feels like there's no intention behind the code. Like it's just, if you're just generating it, you don't really know why you made any particular.

Speaker 22 You could say I chose these lines, but is that at some point if you have large amounts of software developers using it however large but the young people in an organization using it to generate their code they're neither learning to write better code nor are they learning how to develop they're just learning how to fill in blocks they'll never grow within their job yeah i mean the the The trick is that those of us that have spent a whole lot of time debugging software, right?

Speaker 24 And like finding the problems and digging into them and trying to figure out what's going on,

Speaker 24 that kind of stuff,

Speaker 24 it's going to be really hard for younger folks to get

Speaker 24 hired into those jobs so that they have time to build the experience to be able to do that.

Speaker 24 And I'm afraid we're going to end up with basically an older generation or generations retiring and a newer generation that hasn't had the experience of doing that kind of debugging.

Speaker 24 And then it's going to be a real mess, especially since from what I can tell, the code that the AI has generated are a lot buggier and buggier in weirder, like random-ish kind of ways.

Speaker 24 Stuff just kind of comes out of nowhere in a way that I don't. I mean, I've debugged code from people that don't speak the same languages as I do and all that kind of stuff.
AI code is different.

Speaker 24 It's just like, okay,

Speaker 24 why would anyone want to put that block there? That doesn't have anything to do with what we're trying to do at the moment.

Speaker 22 And why is that? Is it just because it's probabilistic?

Speaker 24 I guess so. I mean, it's hard to say why.
I mean, the idea of why an LLN does what it does is kind of a, you know, anybody's guess.

Speaker 22 Yeah, it's just,

Speaker 22 I keep thinking of the word calamity because you sent me these studies as well about how they found like a downward pressure on the quality of code on GitHub.

Speaker 24 Would you mind walking me through what that means?

Speaker 24 Yeah, so basically what that study found, there have been a couple of them, but what that particular study found is that there's what they call code churn has gone up.

Speaker 24 And code churn is basically when you push something, you like add a line of code, you push it into test or to production.

Speaker 24 And then in a short period of time, like I don't remember exactly what the definition was, like in a month or two months, that line of code changes.

Speaker 24 Right. So basically, what that means is that the line of code that got created,

Speaker 24 somebody decided after it got put in, oh, wait, no, that doesn't work right. We don't, we're not happy with that.
We're going to change it to be something else, right?

Speaker 24 And the percentage of lines or the number of lines that

Speaker 24 get changed fairly quickly after they get submitted has gone way up since the

Speaker 24 since the implementation of GitHub Copilot.

Speaker 24 And this is across like most of the giant millions of lines of codes on GitHub.

Speaker 22 And for a simpleton, me,

Speaker 22 why does it being changed, why is changing it so often bad?

Speaker 24 Well, I mean, so, I mean, if you do it right the first time, you can move on to the next thing. Ah.
Right.

Speaker 24 If it's like, you know, if you're writing a document and you put the document in there and then you like,

Speaker 24 you're in

Speaker 24 Google Docs and you're like tracking changes. And it's like, okay, this sentence has changed 17 times.
Obviously, the person isn't happy with the way that sentence is. Right.

Speaker 22 So the generative code isn't good. Right.
And so people see the need to change it.

Speaker 24 That's the presumption, yes.

Speaker 22 And

Speaker 22 so it also said the code quality itself, is that the only way they, is that the only way they measured it? Or is it, there are other things as well

Speaker 24 um so they measured that um they measured um

Speaker 24 uh

Speaker 22 like uh moved code yeah the the

Speaker 24 thing i was talking about earlier where um the uh you've got a bunch of different places in the code that all do the same

Speaker 24 try to do the same function, but they do it in different ways.

Speaker 24 Normally, what would happen is you'd have your, you do it, you do a thing here, right? And then at some point in the future, you need to to do that thing again in a different place.

Speaker 24 And so, what you do is you would move that original block that does the thing someplace else, and then you would call that block from both places, right?

Speaker 22 Because it already works, right?

Speaker 24 And then that way, you've got, you know, however you go fetch stuff from the server, you're fetching it the same way.

Speaker 24 Um, but with this thing, basically, instead of doing that, you've got copy-paste, okay, let me put another one here, let me put another one here, let me put another one here, and it's it's a maintenance nightmare.

Speaker 3 This is Sophie Cunningham from Show Me Something.

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Speaker 5 If anyone has ever said you snored loudly or if you spend your days fighting off excessive tiredness, irritability, and concentration issues, it may be due to OSA.

Speaker 14 OSA is a serious condition where your airway partially or completely collapses during sleep, which may cause breathing interruptions and oxygen deprivation.

Speaker 16 Learn more at don'tsleep on osa.com.

Speaker 4 This information is provided by Lilly, a medicine company.

Speaker 18 Mic check one, two,

Speaker 18 are we recording.

Speaker 18 Hi, I'm Michelle Brinstein, an award-winning chef, restaurateur, and mom. I have a lot on my plate, including my psoriatic arthritis symptoms.
That's why I was prescribed Cosentix.

Speaker 18 It helps me move better.

Speaker 19 Cosentix Seccukenumab is prescribed for people two years of age and older with active psoriatic arthritis. Don't use if you're allergic to COSENTIX.
Before starting, get checked for tuberculosis.

Speaker 19 An increased risk of infections and lowered ability to fight them may occur, like tuberculosis or other serious bacterial, fungal, or viral infections. Some were fatal.

Speaker 19 Tell your doctor if you have an infection or symptoms like fevers, sweats, chills, muscle aches, or cough, had a vaccine or plan to, or if inflammatory bowel disease symptoms develop or worsen.

Speaker 19 Serious allergic reactions and severe eczema-like skin reactions may occur. Learn more at 1-844-COSENTIX or COSENTIX.com.

Speaker 18 Ask your rheumatologist about Cosentix.

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Speaker 23 So

Speaker 22 for the audience as well, how does a software developer actually use GitHub?

Speaker 22 Like really simple stuff, I realize, but I think it's important for people to, it just occurred to me that this may be something that most listeners don't know, which is good to, I think it's good.

Speaker 24 Yeah. So, so what we do is we basically make changes to code.

Speaker 24 We get to the point where we, the developer, are happy with the way it's set up on our machine.

Speaker 24 And then we do what's called a push and we basically send all that code, submit all that code up to GitHub.

Speaker 24 And then theoretically, you know, there can be automatic processes that kick in that like check that code for particular things and run tests on it and that kind of stuff.

Speaker 24 And then at some point, we have a thing called a pull request, which is basically a thing that says, okay, I would like this to go into production now, or more or less.

Speaker 24 I would like this to get promoted into the next phase now. And then someone theoretically will look at it and go, okay, that's fine.
And then click the yes button or say, hey, you forgot about this.

Speaker 24 Go look at this or that kind of thing. Right.

Speaker 24 And the pull request is kind of the unit of work kind of.

Speaker 22 So with GitHub, you almost use it like an organizational code dump. Or where you centralize all the code code.
Sorry, just for the

Speaker 22 media and non-coding as well.

Speaker 22 And I think it's i think that the llm industry has done a really good job of dancing around these terms and selling them to people like me well they weren't selling they didn't work on me i am too stupid but it's where they've just like been like okay yeah well lots of people use copilot that's good and this is good because software's coding but it kind of feels like i don't know all of this is taking the one thing like one major part out of software development and ruining it and I don't even mean coding.

Speaker 22 I mean it's the intentionality behind software design and infrastructure and maintenance. Like there's, it seems like they're removing intention in multiple parts.

Speaker 24 So the way I would say it is when they talk about the AI being able to do the work of a programmer, what they're doing is they're devaluing all of the stuff that's not just

Speaker 24 hacking code. Right.

Speaker 24 And so what they're saying is that basically the job of a developer is basically just, you know, typing, basically.

Speaker 24 And that all of the work that we do to understand what the problem actually is and how it needs to work and, you know, what other problems are likely to show up when we try to do that and how to avoid those things as we go and that kind of thing.

Speaker 24 All that work is basically not important.

Speaker 22 And

Speaker 22 I mean,

Speaker 22 I'm going to say two words, which will probably annoy you. This is, I feel like vibe coding is the the other part of this.

Speaker 22 So, if I'm correct, correct me if I'm wrong, vibe coding is just typing stuff into an LLM and software comes out, and hopefully it works.

Speaker 24 Yeah, vibe coding is basically when you

Speaker 24 intentionally try. Well, I don't know about intentionally, but basically, you make a point of not digging into the code and looking at what the LLM is doing.

Speaker 24 And you basically say, okay, I would like something that does X, right? I would like a game where I fly airplanes around a city or something, right? And then you get what it spits out.

Speaker 24 And then you say, you know, okay, let me try it. Okay.
Well, can we have more airplanes? And okay, can we have some balloons with, you know, signs on them now? And can we do this kind of thing?

Speaker 24 And then you don't think about what the side effects are. You don't think about what things could go wrong.
You don't think about air conditions, that kind of stuff.

Speaker 24 And you just hope that this, whatever you look at and has the right vibe and that, you know, if it, if it, if it looks like kind of what you wanted, that probably it's going to be fine or hopefully it's going to be fine.

Speaker 22 How do you feel about vibe coding?

Speaker 24 So I do it sometimes. Vibe coding is great for a thing that you're going to do once and then throw away.
Yeah. Right.
So if it's like, you know, okay, I want to, I want to do a thing.

Speaker 24 I want to translate this thing to, you know, I want to make this table go into this format over here or that kind of thing. You do it.
You get the output you want. You throw the code away.

Speaker 24 No big deal. Right.

Speaker 22 Like a prototype almost.

Speaker 24 Yeah, basically.

Speaker 24 And so, you know, we call them spikes or tracer bullets sometimes. It's like a, you know, let me get a thing that works at all, right?

Speaker 24 And then let me see what I can learn from that to move into my big maintainable project.

Speaker 24 But for anything that's like, you know, this thing needs to run for a while, this thing needs to not get hacked, this thing needs to, you know, not crash, it's a really bad idea.

Speaker 22 Yeah.

Speaker 22 And at some point, I feel like someone building a product that they don't really understand the workings of, it's kind of almost identical to generating a story with ChatGPT, except kind of more complex and more prone to errors.

Speaker 24 Yeah.

Speaker 24 And the other thing is that there's an adversarial component, right? So

Speaker 24 people will intentionally try to go hack that thing that's sitting on the internet. Oh, right.
In a way that they don't intentionally try to go mess with the story that you wrote.

Speaker 22 Right.

Speaker 24 Right. And so even if it works all by itself, that doesn't mean it's going to work when somebody starts pounding on it intentionally trying to break it.

Speaker 24 And if they can break it, then that's a whole other set of problems that you now have.

Speaker 22 It feels like quality assurance is just never part. Oh, no, are they claiming they're going to do quality assurance with large language models yet? They must.

Speaker 24 Some people are, yeah. I mean, to be honest, a lot of companies have just been getting rid of quality assurance over the years, right? Oh, really?

Speaker 24 When I worked at IBM, we didn't have quality assurance at all.

Speaker 24 They would, no, seriously, they would do this. I was in IBM's cloud group and they would do these,

Speaker 24 what do they call them?

Speaker 24 Hackathon kind of things. They didn't call them that.
I don't know what they called it.

Speaker 24 But basically, everybody in all the other development groups would get together and basically bang on the code that was about to get released from some other group to try to see if they could break it, right?

Speaker 24 But they didn't have dedicated testers anymore because they decided, I guess, that they didn't think they were worth the money. I don't know, but we had some issues because of that.

Speaker 24 Unsurprisingly, movement happen.

Speaker 24 Um, I was in, I don't know, so I was at IBM in like 2017, 2018. Right.
So, it would have been sometime prior to that. When I got there, they didn't have any QA folks.

Speaker 22 Really just feels like it's the management problem as well. It's the management guitar people.

Speaker 24 I would think so.

Speaker 22 It's a real shame as well. And

Speaker 22 forgive me if I'm forgetting exactly where. You've mentioned as well that there is like compound scar tissue from AI-generated code, a larger problem of lots of this code being generated with AI.

Speaker 24 Well, that's.

Speaker 24 That's my expectation, right?

Speaker 22 Yeah, just a potential worry.

Speaker 24 Right, right.

Speaker 24 So the more of this we get and the more issues that we have um the more stuff we're gonna have to dig out of right and what i'm honestly envisioning at some point in the i don't know how long this will take the the crypto bubble took way longer to pop than i expected so i don't know how long it's going to be before this one does but um i'm expecting that there's going to be this big push to try to clean up a bunch of this crap here in a few years once people realize that a lot of the code that's being written and generated right now um is

Speaker 24 has all of these vulnerabilities that nobody's bothering to check for at the moment. Right.

Speaker 22 And those vulnerabilities, again, non-technical way, I read that it was like they call upon things on GitHub that don't exist. So bad actors create something that resembles what it's pulling from.

Speaker 24 That's so that's that's a more specific kind of one. I mean, there are a lot of things.
I mean, so there have been computer viruses since the 80s, right? Right.

Speaker 24 You know, the Morris worm and that kind of stuff. And basically there are known ways that code,

Speaker 24 if you, you have to write it in a particular way in order for it to be secure right and even then sometimes people come up with novel ways of making something not secure and how how do you have to write it to make it secure if if it's possible to explain well i mean there's a big long list of rules right i mean one thing you can do is you can use languages that are what they call safer right um but still you have to make sure that any input that you get from the network you're really really careful to make sure that it doesn't get to overwrite parts of your program that actually execute things.

Speaker 24 You have to make sure that it doesn't have the opportunity to be able to write to places on your disk that it shouldn't be able to write to.

Speaker 24 You have to be able to make sure that it doesn't have access to read data that it shouldn't be able to read,

Speaker 24 all that kind of stuff. And when those things don't happen, you end up with, you know,

Speaker 24 so-and-so got hacked. You know, turns out that somebody we think maybe China is reading the email of the

Speaker 24 people in Congress.

Speaker 24 You get another letter in the mail that says your social security number has been

Speaker 24 leaked by some credit checking firm or something like that.

Speaker 22 Even like, I think it was what, the big target data breach from a while back was through the HVAC system.

Speaker 22 It's just, except now we've got, and that was with humans writing the code.

Speaker 24 Right.

Speaker 22 Imagine if we didn't know.

Speaker 22 Oh, God, it really does feel like the young people are going.

Speaker 22 Actually, no, I take it back. You were talking about Agile the other day.
I'm going to ask you to explain that in a second.

Speaker 22 But it's like, it sounds like for almost decades, they've been gnawing away at management's been gnawing away at the sides of building good software and building good software culture.

Speaker 24 Yes, I mean, there's an argument that says we never got it right in the first place. But I mean,

Speaker 24 I mean, if you think about it, software has been a thing for what, 50 years, 60 years, 70 years, right?

Speaker 24 I mean, compare that to like construction engineering or bridge building or that kind of stuff, right? We're still, you know, relatively speaking

Speaker 24 in our infancy as a

Speaker 24 industry.

Speaker 24 You know, it's been a, it's been a constant evolution. And a lot of times the things that were

Speaker 24 the things that we did to solve a problem that we had ended up causing other problems, right?

Speaker 24 So going back to Agile, in the long, long ago, right, we used to manage software projects the same way we manage like build, you know, bridge building and building building progress, you know, construction projects.

Speaker 24 And it turns out that when you're going to build a bridge, you know beforehand what you need to build the bridge to do.

Speaker 24 When you're building software, a lot of times people are changing their minds as you go, right? And you build a thing and you show it to them. They're like, oh, why don't we put this over here?

Speaker 24 And why don't we change this and that kind of thing, right? Right. Because you don't have the same kind of constraints, physical constraints that you do when you're trying to build a bridge.

Speaker 24 And so we got in this problem where you would create these project plans about how you were going to build this thing and you would never be anywhere close to on time because things would change the whole time.

Speaker 24 Right. And so they created this thing called the Agile methodology.
I'm drastically simplifying.

Speaker 24 There were steps in the middle, but basically, so this, this agile thing is where we, instead of saying, okay, so this is what the whole project's going to look like.

Speaker 24 We're going to be doing, we're going to be done in six months and then things changing along the way. We basically block off a thing called a sprint.
It's a week or two or a month, maybe, depends.

Speaker 24 And then, you know, everybody picks their own sprint length. And then you go, okay, I'm only going to talk about what's going to happen in the next sprint or two, right?

Speaker 24 And then you get to the end of that two weeks and you go, okay, cool. This is what we got done.
What do we want to do next? And then, okay, that's what we got done. What do we want to do next?

Speaker 24 And that kind of thing. And that way, as you go, you have the opportunity to change things.
You have an opportunity to roll changes into the process, that kind of thing, right?

Speaker 24 The problem with that is kind of the same way that dates always ran out

Speaker 24 in waterfall land. Projects can go way, way longer than they were expected to at the beginning because everybody's focused on just two weeks at a time.

Speaker 24 And you never kind of take a big step back like you ought to and go, okay, wait, you know, we were supposed to be done, you know, two months ago. When are we going to wrap this up?

Speaker 24 Right.

Speaker 22 And how has that led to things getting worse? Is it that just software culture, software development culture has been focused on short term perpetually?

Speaker 24 The short term is part of it. Part of it is there are, you know, unscrupulous developers out there that basically want to extend the length of the project so they can get more money out of it.
Right.

Speaker 24 Right. that's that's always the case but the other thing is that you end up with a real um

Speaker 24 a lot of times you end up with a real lack of like long-term planning and long-term understanding right right because everybody's you know same kind of thing you know companies are only worried about what happens next quarter right if you're only worried about what's going to happen the next week or the next four weeks um the the things that you look on look at you know tend not to have the longer-term implications that sometimes you need right?

Speaker 24 And there are times you get close to the end, and you're like, oh, you know, we didn't think about this, what are we doing?

Speaker 24 Yeah.

Speaker 22 And also, if you're in a two- or three-week thing, you're probably not thinking even what you did last sprint.

Speaker 24 Like, it

Speaker 24 maybe last one, but not like two or three, two or three ones ago.

Speaker 22 Is this a problem throughout organizations of all sizes? Is this a consultancy problem?

Speaker 22 Is it everywhere?

Speaker 24 It's most places.

Speaker 24 There are some places that are

Speaker 24 usually in startups, we're a lot more

Speaker 24 ad hoc and we're a lot more

Speaker 24 focused on trying to get things done.

Speaker 24 Basically,

Speaker 24 the idea is the larger you get as an organization and the more money you're throwing at it and the more management control you want,

Speaker 24 the more of this overhead you put in place and the more complicated things get as as just as a management structure kind of thing.

Speaker 22 And does in the bigger, so this is something you'd see in like a Google and an Amazon as well?

Speaker 24 Oh, absolutely. So

Speaker 22 do you think it has the same organizational effects or?

Speaker 24 Largely, yes.

Speaker 24 So those organizations tend to be, well,

Speaker 24 those organizations historically have tended to be

Speaker 24 before

Speaker 24 the recent inshitification wave.

Speaker 24 Those,

Speaker 24 I'm assuming I can swear on this. Yeah, yeah, yeah.
Fuck shit.

Speaker 24 Those organizations have historically been fairly more engineering driven, which means that you typically have people higher in the organization that are technical and have been programmers and who understand some of the implications.

Speaker 24 And so they tend to try, at least we try, to run interference with management and to try to make sure everybody's on the same page and that kind of stuff.

Speaker 24 A lot of,

Speaker 24 a lot, not all, but a lot of problems can get

Speaker 24 lessened if you have people in the organization that are at a higher level whose job is not to manage people, but whose job is basically to keep track and coordinate between different groups that are doing different technical things.

Speaker 22 Right. To make sure people aren't building the same thing, I'm guessing, or are building the right thing in the right way.

Speaker 24 Yeah. And that, and that.

Speaker 24 how what this group is building is going to impact what this group is building at some point in the future And making sure that when you get to the point where those two things need to talk to each other, they're both aware enough of what the other one is doing that the two things hook together correctly.

Speaker 22 Yeah. So based on my analyses of these companies, that's definitely gone out the window.

Speaker 23 I mean, even with LLM integration, so there was a Johnson Johnson story that went out in Wall Street Journal a couple of weeks ago where it was like they had 890 LLM projects or generative AI projects, of which the Pareto principle wins again.

Speaker 23 10 to 15% of them were actually useful. And the thing that stunned me about that, other than the fact it confirmed my biases, which I love, was the fact that there were 890 of the fucking things.

Speaker 23 And no one was like, should we have this many?

Speaker 23 That there was no like

Speaker 23 software engineering culture that was like, hey, are we all chasing our tails? Is this useless? But it sounds like they were all focused on their little, the little boxes.

Speaker 24 Yeah, I mean, so the other thing, so understand that, again, greatly oversimplifying. A lot of the new stuff that's happened with large language machines, large language models and

Speaker 24 generative AI, people didn't expect, right?

Speaker 24 It was kind of a surprise when you throw a whole bunch more data at a large language model and it started spitting out text in a way that nobody really, there was no like mathematical reason to expect it to be able to be as good at generating autocomplete stuff as it as it was, right?

Speaker 24 And so there's this belief that

Speaker 24 if we did the thing and we unexpectedly got more than we asked for, if we do more of the thing, maybe we'll unexpectedly get more of what we wanted, right?

Speaker 24 That hasn't seemed to really pan out the last couple of years from what I can see, but

Speaker 24 that

Speaker 24 we don't really understand enough about this to know whether it's going to work. So we might as well throw spaghetti at the wall and see if it sticks because it might

Speaker 24 kind of mentality is kind of pervasive at the moment. And everybody's, there's a lot of FOMO.
There's a lot of like, you know, well, our competitors are probably doing this.

Speaker 24 And so we don't want to get left behind. It kind of reminds me of the

Speaker 24 rumors that they talked about back in the 80s when the CIA was doing all this psychic research because supposedly the Russians were doing psychic research.

Speaker 24 And it was all complete crap, but both sides were convinced that the other side was making some progress. And so everybody was dumping a ton of money into it.

Speaker 22 LLMMK Ultra.

Speaker 24 Exactly. Yes.

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Speaker 22 So, okay, LM Kay Ultra aside, is this something you're seeing in software development, though? Because I know I've seen it in management where it's just kind of like, shove the shit in there.

Speaker 22 This seems like it's an important thing right or is this are you seeing it within software development

Speaker 24 so I am seeing it within

Speaker 24 software planning right so when when managers are sitting down and saying okay we need to build this new thing we need to create a new group we need to split this group apart we need to decide what our headcount is going to be for next year there's a lot of okay and what do we think the ai is going to do next year and how many headcount do we think that's going to save us and that kind of thing right there are some companies uh duolingo is one klarna is one Yeah.

Speaker 24 OP, sorry, BP, the former British Petroleum, what, last year had a thing where they said they were cutting 70% of their contract software developers.

Speaker 22 And in most of these, they've kind of rolled them back as well.

Speaker 24 I don't think Duolingo has yet.

Speaker 22 No, this is just being unfair to you. They like a day ago.

Speaker 24 Really?

Speaker 22 Ah, we're kind of.

Speaker 22 It's so funny. It's so funny that this just keeps happening in exactly the same way.
It's like, oh, what a surprise. Human beings to do stuff.
Yeah.

Speaker 22 But it kind of gets back to, I think, what you've said about everything with LLMs.

Speaker 23 It's like, you can teach something to say, yeah, I think the right, the thing you're looking for is this, but you can't teach it context. And that's been a point you've made again and again.

Speaker 23 Like, it seems the job of a software engineer is highly contextual, unless you're like in the earlier days.

Speaker 24 Yeah. And I liken it sometimes to the memento guy from the memento movie, right? Where like can't form long-term memories.

Speaker 24 And do you, do you really want the memento guy to be the person that's building the software that makes the 737 Max

Speaker 24 be able to compensate for its control input.

Speaker 22 Yeah.

Speaker 23 Well, the thing is, though, with that argument, they would argue, and I know that there is a better argument here.

Speaker 22 They would argue, well, what if we just give it everything that's ever happened? What if we just show every single thing we've ever done on GitHub? Surely then it would understand.

Speaker 24 So,

Speaker 24 what I have seen from the papers that I have read is that LLMs have a basically squishy middle context problem, kind of the way that you do, right?

Speaker 24 So if somebody gives you a big document to read or a big long documentary to watch or something, and then they ask you questions, what they're going to find is that you remember a lot more from the beginning of that and the end of that than you do from the middle of that, right?

Speaker 24 And LLMs have the same kind of problem, right?

Speaker 24 And the other problem that the LLMs seem to have is that when you give them a whole bunch of instructions, just instructions, piled on instructions, piled on instructions,

Speaker 24 they can either get confused and forget some of the instructions or they deadlock or they just start going, okay, I can't satisfy all of these, so I'm not even going to bother to satisfy any of them, or they'll pick one or two.

Speaker 24 The fact that you can take a million tokens and you can stick that in the memory block that

Speaker 24 the GPU is going to process doesn't necessarily believe, doesn't necessarily mean that all of the tokens in that memory block are actually going to be treated equally and going to be understood, right?

Speaker 24 In theory,

Speaker 24 maybe

Speaker 24 if you could

Speaker 24 train

Speaker 24 your,

Speaker 24 if you could like custom train an LLM and modify all of its weights based on exactly what your stuff was and do that like day after day after day after day as things changed, you would theoretically get better.

Speaker 24 I still don't think it would be, you know, I still don't think it would understand the context as well, but that would be ridiculously expensive.

Speaker 22 Yeah. And at that point, you could train a person.

Speaker 24 Yes. I mean, the person would probably be more annoying.

Speaker 24 That's, I mean, the point, I mean, a lot of this seems to be really, you know, we don't like dealing with the Prima Donna programmer kind of thing, right?

Speaker 24 There's this, you know,

Speaker 24 I mean, not just programmers, right? We don't also don't want to deal with the

Speaker 24 Primadonna reporters or the Prima Donna illustrators or

Speaker 24 get rid of these people. Right.

Speaker 22 These annoying, they ask for stuff and they want money.

Speaker 24 Yeah.

Speaker 24 And days off and sick leave and, you know, healthcare.

Speaker 22 And this is just disgusting. How dare?

Speaker 22 It's, it's so, it's frustrating as well because it across software development and everything, but especially with software developers, it feels just very insulting because it doesn't seem like this stuff.

Speaker 22 Actually, here's a better question. have you seen much of an improvement with like 01 03 like these reasoning do you think do reasoning models change things for the better and if so how um

Speaker 24 so

Speaker 24 a little

Speaker 24 um

Speaker 24 that they don't make as many stupid mistakes um is basically what it what what it boils down to um going back to your your first thing though right i mean so there was a piece uh actually a couple pieces recently um one of them was about you know, tech workers are just like the rest of us.

Speaker 24 They're miserable.

Speaker 24 I'll give you links to these. The other one was a Corey Doctorow piece that was like,

Speaker 24 the future of

Speaker 24 Amazon coders is the present of Amazon warehouse workers or vice versa.

Speaker 24 There has been a lot of deference given to software developers

Speaker 24 over time because

Speaker 24 we have been kind of the engine that's made a lot of the last 20, 30 years work.

Speaker 24 And there's a desire to make that not so anymore, right? And to make us just as interchangeable as everybody else.

Speaker 24 I guess, you know, from an economic standpoint, I kind of don't blame them. I understand why they're trying to do what they're doing.

Speaker 24 I don't, I mean, I don't think that the warehouse workers should be treated the way the warehouse workers are treated, you know, much less everybody else gets treated that way.

Speaker 24 And it's been a lot worse since the giant layoffs at Twitter, now X,

Speaker 24 when that happened and the thing didn't crash and completely burn like everybody was, or not everybody, but a lot of people were expecting it to.

Speaker 24 The sentiment became, well, maybe

Speaker 24 all these software developers aren't as important as they, you know, we've always thought they were.

Speaker 24 And, you know, We will see over time what the end result of that is. My guess is it's going to end up being a mess.

Speaker 24 But, you know,

Speaker 24 I'm a software developer, right? I'm going to,

Speaker 24 it behooves me for it to be a mess, right? So it might just be my bias that's getting in the way.

Speaker 22 I actually, I think that you're right, though, because I remember back in 2021 and onward, the kind of post-remote work, the remote work, there was the whole anti-remote work push, but there was this, the whole quiet quitting and things like that, 2022, where it was like software engineer, they just, they expect to be treated so well because 2021 saw the insane hiring.

Speaker 22 You saw tech companies like parking software workers.

Speaker 22 I think that played into it as well, where all of these companies who chose to pay these software engineers, they were the ones that made the offers, got pissed off that they'd done so and thought we should cut all labor down to size.

Speaker 22 And then along comes coding.

Speaker 23 Almost makes me wonder if most of these venture capitalists talking about this don't know how to code themselves.

Speaker 2 You gotta wonder.

Speaker 24 I don't know many that do.

Speaker 22 Yeah.

Speaker 24 I know some that have at some point, but

Speaker 23 at some point, it's like they're not part of modern software development culture, which I know sounds kind of wanky, but I mean, just how an organization builds software feels like something they should know.

Speaker 23 But then again, they don't know how to build a real organization either. So who the fuck?

Speaker 24 Yeah. Well, I mean, honestly, a lot of it.

Speaker 24 I've been in organizations that VCs basically killed. Right.
Because,

Speaker 24 we built a thing, that thing was

Speaker 24 a reasonable business, but VCs don't want a reasonable business. They want either 100x return or they want a tax write-off and they don't want anything in between.

Speaker 24 So, I mean, what they're looking for is really, I mean, they're not trying to run a regular business, right? They're not trying to do the normal process.

Speaker 24 They're trying to either, you know, hit one out of the park or throw it away and move on.

Speaker 24 And so the rules for them are different because what they're trying to accomplish is not what the rest of us are trying to accomplish as a general rule.

Speaker 22 It's a constant theme of the fucking show.

Speaker 22 It's just like you have these people that don't code saying how coders should code.

Speaker 22 Dario Ama Day the other day saying that this year we're going to have the first one-person software company with a billion dollars revenue or something like that. And it's just,

Speaker 22 I feel like there are some people who should not be allowed to speak as much sometimes.

Speaker 24 But it's just frustrating and insulting.

Speaker 22 And it's, but now that you've got me thinking about it, it does feel like this is an attempt to reset the labor market finally coming for software developers. And I don't mean finally in a good way.

Speaker 24 Right.

Speaker 24 I mean, it feels like that being in the, being in that organ, um, being in that industry at the moment, it, it really feels like that. Is it scary right now?

Speaker 22 Is it scary right now?

Speaker 24 Um, not for me, um, because I'm old enough to be semi-retired, right? Um,

Speaker 24 but I, I mean, I've been talking to a lot of folks. Um, I've been having a interviewing a bunch of folks that are listeners to my channel and kind of trying to get a feel for what's going on.

Speaker 24 And I've talked to folks that are, you know, like I said, I talked to some folks that were like, you know, I work for a big bank. They're cramming Copilot down our throat whether we want it or not.

Speaker 24 I've talked to some folks that are like, every time I sit down with my boss, I'm thinking that, you know, this is going to be the day that I'm going to find out that my group is getting cut the way the other three groups in

Speaker 24 the company is getting cut. There's a lot of

Speaker 24 artificial productivity requirement increases kind of thing, which is like what?

Speaker 24 Just, you know, we, you know, we expect more tickets closed per, you know, two-week period than we've had before because we're giving you this AI now, so you ought to be more productive, that kind of thing.

Speaker 22 Would a ticket necessarily be something that you just write code for?

Speaker 24 Or is it more than just that?

Speaker 24 Well, so generally, it's more than just that, but generally the ticket, that's kind of the way that we track the work that we do

Speaker 24 in a lot of organizations. And some tickets are like, I'm building a new thing, and those are kind of easier to predict.
And some tickets are, this thing isn't behaving right.

Speaker 24 Go figure out where the bug is. And those are a lot harder to predict.

Speaker 24 They have these things. Agile has this thing called a velocity graph, where basically you see how many tickets per person get closed over time.

Speaker 24 And people want to see the slope of that line change because they're giving you AI.

Speaker 24 Wow.

Speaker 22 And I'm guessing the people telling you to change that don't know what they're talking about.

Speaker 24 That seems to be the case.

Speaker 22 Great.

Speaker 24 So, I mean,

Speaker 24 the good news in theory, right? I don't know to what extent this is going to happen, but in theory,

Speaker 24 if they keep telling people, you know, that slope of that line should be changing because you have AI now, over time, if we see the slope of that line not changing,

Speaker 24 right? Then theoretically, it will be proof that the AI is not providing the return that people expected.

Speaker 22 Or you're not using it right.

Speaker 24 Well, yes, there's always that you're not prompting it right.

Speaker 22 That is basically what I am people.

Speaker 22 One of the many reasons what you want is like, I want to have people that actually code on to talk about this stuff because it's really easy as a layman myself and for others to just be like, oh, but this does replace coding, right?

Speaker 22 And it does. It sounds like it really doesn't.

Speaker 24 Like, it can help.

Speaker 24 It can be like a force multiplier to an extent, but even past the initial steps it just isn't there well i mean so the the best analogy i've i've always found to writing code is actually just writing

Speaker 24 right i mean you can get chat gbt to spit out a few paragraphs for you right

Speaker 24 but you know you end up with you know the legal briefs that have the story that's made up or the you know just things that aren't connected to reality or stuff that you know when people read them they're like i mean you've you've you can tell the difference between an ai slop generated, you know, like the, the stupid, um, the, the insert from the Chicago Sun-Times and the Philadelphia Inquirer, you know,

Speaker 24 all the books, all the things you can do this summer, right?

Speaker 24 That like made up books and all that kind of, I mean, like, but even the, even the articles that weren't the ones that were making up stuff, you read the, you know, this is what's going to be happening this summer.

Speaker 24 This is what the weather is going to be like or whatever. And you're reading and you're like, this, this, there's no like insight here.
There's no thought here.

Speaker 24 There's no, you know, there's nothing in here that I get to the end of this. I've read the whole thing.
I understand the whole thing, but I don't have anything I can walk away with.

Speaker 22 Right. And AI agents aren't coming along to replace software developers.

Speaker 22 You're not scared of Devin?

Speaker 24 I am not scared of Devin.

Speaker 24 So, I, well, actually, I kind of am. I am scared that Devin is going to make a mess of things and that more things are going to get hacked.

Speaker 24 And that's going to end up being worse for everybody on the internet, right? How would it do that?

Speaker 24 By, like we were talking about before, right? So when you write code that isn't secure, right?

Speaker 24 And you write code that uses a library that's got an old version of a thing that there's a known bug in it, but you don't bother to check to see if there's a fix for that bug, or you don't use best practices when it comes to writing code and that kind of thing.

Speaker 24 Or you don't think about the kinds of maintainability issues that you're going to have, and you do things like you ship out code

Speaker 24 in an Internet of Things thing, a light bulb, right? Or

Speaker 24 Internet Wi-Fi router that cannot be patched over the Internet that has a bug in it.

Speaker 24 Right. And now it's like that thing is going to have a bug in it forever.

Speaker 24 And you're going to have to find all of the ones on the earth and turn them off before someone's not going to be able to take them and be able to hack them and use them to attack somebody else from there.

Speaker 22 I mean, IoT is a huge problem. Oh, yeah.
But the cheaper ones have like the spyware stuff and crypto mining.

Speaker 24 It just. But yeah, the ones that that have like really nasty vulnerabilities and they have no way of being updated once they leave the factory.

Speaker 24 Right. And it's just as long as they're out there, they're going to be a problem literally for everybody on the internet.
Jesus. Well, what can

Speaker 24 this to wrap us up?

Speaker 22 What can a new engineer, someone new to software development, what can they learn right now? You've kind of done a video on this, but I think it's a good place to wrap us up.

Speaker 22 What can they start learning to actually get ahead, to actually prepare for all of this?

Speaker 24 That's a really good question. So you can't, these days,

Speaker 24 you can't really be able to be an engineer.

Speaker 24 You can't get hired as an engineer without some ability to talk about being able to do prompts and use, you know, some kind of AI code editor, that kind of thing.

Speaker 24 It's just an expectation of the job now. Whether it should be or not, it's a different thing.

Speaker 24 I mean, like I said before,

Speaker 24 there are situations where you tell it what you want and it will type faster than you you possibly can so you know that's not necessarily bad you need to understand that um you need to figure out well okay i'll get back to something else um you need to figure out basically how to test the thing right so how do you make sure that the code that it spits out does what you meant it to do um and what i'm expecting is that we're going to spend more time thinking about testing and thinking more about you know trying to find exceptions and that kind of thing than we have in the past because the code that's actually being generated is going to be less likely to be quality than it was in the past.

Speaker 24 The problem is

Speaker 24 it has become the case in the programming industry that the things you need to do to get through the interview to get hired have very little resemblance to the things that you actually do on the job that you need to actually do a good job.

Speaker 24 And so

Speaker 24 that's a whole different, we could probably have a whole other podcast episode just about the interviewing problem.

Speaker 24 But the main thing right now, it's so

Speaker 24 right now, the whole hiring thing, and this isn't, I don't think, true for just programmers, but it's especially true for programmers,

Speaker 24 is all

Speaker 24 bots that customize your resume and write a custom cover letter and then send them over to the

Speaker 24 submit the thing to the bot that's screening the resume and screening the cover letter, right? And that getting it to the point where you can actually talk to a human is a nightmare right now.

Speaker 24 So the whole hiring system is kind of broken.

Speaker 24 So the actually getting to the point where you can get hired is a, is a nightmare at the moment.

Speaker 24 But the thing that you can do is figure out what kinds of things that AI are good at, is good at.

Speaker 24 And one of the things that AI is pretty good at is things that don't matter as much, right? So, like, you know, AI can pick the layout of a site potentially, right?

Speaker 24 And you could have it pick two or three of them, and you can basically do what's called an A-B test, and you can randomly assign people to it.

Speaker 24 You can figure out which one of them performs better, and you can throw the rest of them away.

Speaker 22 And even then, at some point, you will probably want the design customized.

Speaker 24 Yeah, I mean, but, but

Speaker 24 I think there will be a lot of things where

Speaker 24 people can kind of get something that's kind of good enough to get started.

Speaker 2 Right. Right.

Speaker 24 Um, and I think that to some extent, this is going to be kind of a boon for the industry in the longer term, where somebody who can't program right now, um, but who has some idea of kind of what they want, can do like a vide coding thing.

Speaker 24 They can validate that the market that they want to try to attack exists right and that people want to use the kind of thing that they built and then they can bring in somebody to actually build it right

Speaker 24 you know what i mean and those kinds of things wouldn't necessarily have been able to happen um in the complete absence of ai so it's not i don't think completely useless um and there there are times when as a as a developer there are things that we're not good at like you know writing marketing copy and that kind of stuff that if we're trying to do a project for ourselves you know a lot of that stuff we can just outsource to the ai because it's not the thing that keeps the project from actually breaking and getting hacked and that kind of thing, right?

Speaker 24 So it's kind of like there's this concept where you need to keep the things that are part of your competitive advantage in-house and everything else you can kind of outsource to somebody else.

Speaker 24 The kinds of things you can outsource to somebody else are the kinds of things that you potentially you could throw an AI at because they're not even corporate.

Speaker 22 But even then, it's like, it doesn't seem like that's a ton of things right now or will be.

Speaker 24 Again, it's it's the so it's it's basically two things. It's things that were

Speaker 24 the quality of the thing doesn't matter really,

Speaker 24 right? Which every business has those kinds of things, right?

Speaker 24 And they're the kinds of things where you can define a metric that you can test the AI against and let it try over and over and over and over and over again until it gets to the point where it's good enough.

Speaker 24 Yeah. Right.
So if your metric is more people click on this button than

Speaker 24 the button before, right? Then you can have the AI create a whole bunch of different ways to skin that button, right?

Speaker 24 And then you can say, okay, so the one that tested best is the one we're going to keep. That's a thing you can throw an AI at, right?

Speaker 24 Because you've got a well-defined way of checking and no telling how long it's going to take, but you have a well-defined way of checking to see if it's working right or not.

Speaker 24 Yeah.

Speaker 22 I mean, for years, I've had the theory that this industry was a $20 to $25 billion total addressable market, pretending to be a trillion dollar one.

Speaker 22 And everything you're saying really suggests, it's like you're describing things like platform as a service, like

Speaker 22 things that you use in tandem with very real people and intentional ideas.

Speaker 24 Yeah, this is, I don't see a world in which this is a,

Speaker 24 we replace all the humans, you know,

Speaker 24 the whole like, you know, this is going to displace 80% of the white color workers in the world.

Speaker 24 I just, you know,

Speaker 24 the only the only people that are really going to be replaced anytime soon are people that either weren't doing a great job to start with or people whose bosses don't understand what they were doing to the point that the boss thought that what they were doing mattered.

Speaker 24 And my guess is that there's going to be regret at that point and that at some point they're going to have to bring those people back.

Speaker 22 Well, Carl, this has been such a wonderful conversation.

Speaker 23 Where can people find you?

Speaker 24 I am internetofbugs at YouTube is probably the easiest place to find me. And then there are links on that channel to point at other things.

Speaker 22 And you've been listening to me, Ed Zitron. You've been listening to Better Offline.
Thank you, everyone, for listening. And yeah, we'll catch you next week.

Speaker 23 Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matosowski.
You can check out more of his music and audio projects at matosowski.com.

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