Also media, Hello and welcome to Better Offline. I'm your host ed zet Trunk. Also today, I'm joined by Carl Brown, a veteran software engineering host of the excellent YouTube channel Internet of Bugs. Cayl, thank you for joining me.

Also media, Hello and welcome to Better Offline. I'm your host ed zet Trunk. Also today, I'm joined by Carl Brown, a veteran software engineering host of the excellent YouTube channel Internet of Bugs. Cayl, thank you for joining me.

Thanks for having me.

Thanks for having me.

So I'm going to start with an easy one. What is the software developer like? What actually is that?

So I'm going to start with an easy one. What is the software developer like? What actually is that?

So?

So?

Basically what we do is we take ideas about problems that people want to solve, generally, and we write software. We write code that tells computers instructions how to make the computer do the thing that needs to do to solve the problem the person else is to solve.

Basically what we do is we take ideas about problems that people want to solve, generally, and we write software. We write code that tells computers instructions how to make the computer do the thing that needs to do to solve the problem the person else is to solve.

Right.

Right.

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

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

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

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

It depends on how good you you're the people that are asking for stuff. Is As a general rule, I would say maybe between ten percent and twenty five percent.

It depends on how good you you're the people that are asking for stuff. Is As a general rule, I would say maybe between ten percent and twenty five percent.

Okay, just really want to be ten to twenty Even if we say thirty percent of the job, which is more than you said, that means the majority of this job is not actually writing.

Okay, just really want to be ten to twenty Even if we say thirty percent of the job, which is more than you said, that means the majority of this job is not actually writing.

Code right now.

Code right now.

That's that's largely for folks that are farther up the chain, Right, 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 for any of that kind of stuff. Yet 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 talking to people and stuff than actually code.

That's that's largely for folks that are farther up the chain, Right, 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 for any of that kind of stuff. Yet 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 talking to people and stuff than actually code.

Right. The reason I asked that, and the reason we're doing this as well, is the there have been a lot of stories around like LM's replacing code as LLLMS replacing engineers, claiming that junior software engineers will be a thing of the past due to LLLMS. How much validity is there in.

Right. The reason I asked that, and the reason we're doing this as well, is the there have been a lot of stories around like LM's replacing code as LLLMS replacing engineers, claiming that junior software engineers will be a thing of the past due to LLLMS. How much validity is there in.

That, Well, when it comes to the really really really fresh out of school kids, right.

That, Well, when it comes to the really really really fresh out of school kids, right.

That you have to basically break everything.

That you have to basically break everything.

Down in hand, the little chunks of work, and LM can kind of do that, although the kid will get better over time and the LLM is pretty much fixed right right, But past that it doesn't do a good job of being able to do any kind of long term thinking, and that's largely the job, right, I mean this is this is not a set of you know, I come in today, I do a thing today, I come in tomorrow and having no understanding of what happened yesterday, and do another self contained thing and so on and so forth.

Down in hand, the little chunks of work, and LM can kind of do that, although the kid will get better over time and the LLM is pretty much fixed right right, But past that it doesn't do a good job of being able to do any kind of long term thinking, and that's largely the job, right, I mean this is this is not a set of you know, I come in today, I do a thing today, I come in tomorrow and 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.

Right, that's not the job.

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 that's what it's supposed to do.

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 that's what it's supposed to do.

So I think that I've known, and one of the reasons I had you on as well, is that really there are so many of these stories that claiming that, like this software engineer's job is gone, that these companies be writing all of their code with AI, and it doesn't even seem like that is possible. One of your videos, you did a really good thing around like the twenty to thirty percent a link to this in the notes, twenty to thirty percent of code that behind meta and I think Google it was is written by AI. Now, again, how much valuidity is there to them?

So I think that I've known, and one of the reasons I had you on as well, is that really there are so many of these stories that claiming that, like this software engineer's job is gone, that these companies be writing all of their code with AI, and it doesn't even seem like that is possible. One of your videos, you did a really good thing around like the twenty to thirty percent a link to this in the notes, twenty to thirty percent of code that behind meta and I think Google it was is written by AI. Now, again, how much valuidity is there to them?

Well, I mean so if one of the quotes was something to the effect of thirty percent of the code is suggestions that were given by autocomplete that a human accepted, right, which could be as much as you know, the thing said, oh wait, you spelled this wrong.

Well, I mean so if one of the quotes was something to the effect of thirty percent of the code is suggestions that were given by autocomplete that a human accepted, right, which could be as much as you know, the thing said, oh wait, you spelled this wrong.

Let me give you a suggestion about how to spell it correctly.

Let me give you a suggestion about how to spell it correctly.

Right, right, I mean how much of the actual text that you write is you know, it is corrected by a spell checker?

Right, right, I mean how much of the actual text that you write is you know, it is corrected by a spell checker?

Right?

Right?

If all that counts as AI, then what percentage of your stuff is written by AI?

If all that counts as AI, then what percentage of your stuff is written by AI?

Right?

Right?

Well, in my case, absolutely nothing. But that's just kind of a free I'm a just a complete free But no, I get your point, and it's without being a code of myself. It's something I've really noticed across these stories where people just kind of blindly push them out and they say, oh, it's twenty to thirty percent of the code is written by but there's no verifying this. 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 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 if you don't know why that was written because you had something generated. Is that not a huge problem?

Well, in my case, absolutely nothing. But that's just kind of a free I'm a just a complete free But no, I get your point, and it's without being a code of myself. It's something I've really noticed across these stories where people just kind of blindly push them out and they say, oh, it's twenty to thirty percent of the code is written by but there's no verifying this. 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 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 if you don't know why that was written because you had something generated. Is that not a huge problem?

Yes?

Yes?

But worse, what 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.

But worse, what 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.

You do it a different way.

Can you give me an example.

Can you give me an example.

So, for example, when you need to go fetch a thing from a server, right, well, you overhear in this code you fetch a thing from a server. Over Here in the code you fetch a different thing from the server. Normally, you'd be able to use the same block of code to do that, so that if there's a mistake in it, you can change it once and it's fixed everywhere, right, Right, But the way the llms work is you say, hey, I want to fetch a thing from the server, and it says cool, and it writes a whole thing.

So, for example, when you need to go fetch a thing from a server, right, well, you overhear in this code you fetch a thing from a server. Over Here in the code you fetch a different thing from the server. Normally, you'd be able to use the same block of code to do that, so that if there's a mistake in it, you can change it once and it's fixed everywhere, right, Right, But the way the llms work is you say, hey, I want to fetch a thing from the server, and it says cool, and it writes a whole thing.

For you that may or may not work the same way as the previous one.

For you that may or may not work the same way as the previous one.

Right, And so now you find, okay, under some circumstances, we're having a problem fetching things from the server. I don't know which one of these twelve implementations that go fetch from the server is the one that's actually causing the problem.

Right, And so now you find, okay, under some circumstances, we're having a problem fetching things from the server. I don't know which one of these twelve implementations that go fetch from the server is the one that's actually causing the problem.

Right, Well, so isn't there isn't there a security issue of having large language models, Like wouldn't all the code be quite similar or at least more similar depending on if everyone's using Claude or everyone's using well get hub copile.

Right, Well, so isn't there isn't there a security issue of having large language models, Like wouldn't all the code be quite similar or at least more similar depending on if everyone's using Claude or everyone's using well get hub copile.

I guess this Claude now, No, not really.

I guess this Claude now, No, not really.

It basically kind of picks a random number at the beginning and goes okay, So that's the I think if it kind of like you deal a deck of cards, right, whichever deck of card gets turned over first, that's the beginning of the autocomplete that it starts. And so depending on which example it's I don't want to say thinking of, but depending on which example represents that, I'm grastically over simplifying. But depending on which example is represented by that card, it's going to go down one path or another.

It basically kind of picks a random number at the beginning and goes okay, So that's the I think if it kind of like you deal a deck of cards, right, whichever deck of card gets turned over first, that's the beginning of the autocomplete that it starts. And so depending on which example it's I don't want to say thinking of, but depending on which example represents that, I'm grastically over simplifying. But depending on which example is represented by that card, it's going to go down one path or another.

Right, And so what they actually what these large language model coding tools actually good for? Because I get a lot of people who who respond by saying, this is proof that AI is a big deal, and I'm just kind of like, I'm not even looking for a particular answer, just truly what's useful about them?

Right, And so what they actually what these large language model coding tools actually good for? Because I get a lot of people who who respond by saying, this is proof that AI is a big deal, and I'm just kind of like, I'm not even looking for a particular answer, just truly what's useful about them?

So they are decent at when you know what you want and what you want is a fairly simple, self contained thing, and you know how to tell whether or not in the self can think thing does what you want, It can type it faster than you can, like wells so correct. Basically, Yes, it's like auto complete if you if you know exactly what you want. Yeah, I mean so I use it a lot because I programm in a bunch of different programming languages a lot, right 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?

So they are decent at when you know what you want and what you want is a fairly simple, self contained thing, and you know how to tell whether or not in the self can think thing does what you want, It can type it faster than you can, like wells so correct. Basically, Yes, it's like auto complete if you if you know exactly what you want. Yeah, I mean so I use it a lot because I programm in a bunch of different programming languages a lot, right 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?

Now?

Okay, how do I do this in this language?

Okay, how do I do this in this language?

Right?

Right?

So it's kind of you can.

So it's kind of you can.

Actually understand the generation when it comes.

Actually understand the generation when it comes.

To 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. So I use it kind of like a Google Translate kind of thing to go from one programming language to another sometimes.

To 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. So I use it kind of like a Google Translate kind of thing to go from one programming language to another sometimes.

But you wouldn't trust it to build a full software package.

But you wouldn't trust it to build a full software package.

Oh not at all?

Oh not at all?

Why not?

Why not?

Well it wouldn't work to start with.

Well it wouldn't work to start with.

Why wouldn't it work?

Why wouldn't it work?

Well, I mean, so I've done some experimentation on that where I've taken fairly complicated.

Well, I mean, so I've done some experimentation on that where I've taken fairly complicated.

Challenges.

Challenges.

Challenges are intended for programmers to basically get better at their craft and that kind of thing. And I've run ai you told it, you know, step by step, okay, the the challenge says, this is your next step.

Challenges are intended for programmers to basically get better at their craft and that kind of thing. And I've run ai you told it, you know, step by step, okay, the the challenge says, this is your next step.

Do this.

Do this.

The challenge says, this is your next step.

The challenge says, this is your next step.

Do this on really simple challenges in programming languages like Python that it's got a lot and a lot of examples for it does okay 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 it all.

Do this on really simple challenges in programming languages like Python that it's got a lot and a lot of examples for it does okay 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 it all.

Huh, why is there? Why does so many engineers swear by it? Then?

Huh, why is there? Why does so many engineers swear by it? Then?

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, My group is getting copilot gemmed on our throats whether we want it or not. And the executives are all really excited about it, and none of us are interesting.

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, My group is getting copilot gemmed on our throats whether we want it or not. And the executives are all really excited about it, and none of us are interesting.

So it's executive. I've 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.

So it's executive. I've 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, there's a lot of wish fulfillment.

Sorry, 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, and we're just gonna hope that the AI thing is going to be, you know, just as good as the programmers are close to us, just as good as the programmers, and not nearly as annoying.

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, and we're just gonna hope that the AI thing is going to be, you know, just as good as the programmers are close to us, just as good as the programmers, and not nearly as annoying.

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

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

Yeah, I mean, those terms get mashed to keep yeah, I mean.

Yeah, I mean, those terms get mashed to keep yeah, I mean.

So part of the problem is that in like I live in Texas, and in Texas you're not allowed to call yourself an engineer unless you passed the engineering exam. Right, So I can't literally, I literally can't call myself a software engineer legally in Texas As. I understand it. I'm not a lawyer, but that's my understanding. So it's like the terms get all confused.

So part of the problem is that in like I live in Texas, and in Texas you're not allowed to call yourself an engineer unless you passed the engineering exam. Right, So I can't literally, I literally can't call myself a software engineer legally in Texas As. I understand it. I'm not a lawyer, but that's my understanding. So it's like the terms get all confused.

Right, So somewhat related, what is it that people misunderstand about the job?

Right, So somewhat related, what is it that people misunderstand about the job?

Then, 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. 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, the solution of the problem that you're trying to solve.

Then, 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. 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, the solution of the problem that you're trying to solve.

Another thing is that.

Another thing is that.

A lot of the problem with the job is that every little decision builds up over time, and at some point a bug is going to happen. They're inevitable, and when that happens, basically there's this process where what you need to do, if you're being competent, is roll back through the 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, And that kind of long term thinking is not a thing I've ever seen LM exhibit at all. I talk about it like l limbs or generative AI is good at solving riddles, but actual software development is more like solving a murder.

A lot of the problem with the job is that every little decision builds up over time, and at some point a bug is going to happen. They're inevitable, and when that happens, basically there's this process where what you need to do, if you're being competent, is roll back through the 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, And that kind of long term thinking is not a thing I've ever seen LM exhibit at all. I talk about it like l limbs or generative AI is good at solving riddles, but actual software development is more like solving a murder.

Yes, you said that in that wonderful video. Yeah, I And it almost feels as if we are building towards an actual calamity of sorts, maybe not an immediate one. 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 inline, 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, So you've just got a generation of kind of pumping the internet and organizations with sloppier code.

Yes, you said that in that wonderful video. Yeah, I And it almost feels as if we are building towards an actual calamity of sorts, maybe not an immediate one. 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 inline, 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, So you've just got a generation of kind of pumping the internet and organizations with sloppier code.

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, 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.

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, 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.

Basically, a senior or a mid level developer with.

Basically, a senior or a mid level developer with.

The benefit of AI, with the benefit of AI that's in air quotes, 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. There's some statistics about how the people that are fresh out of school these days are historically underemployed relative to the general population, at least in the US where I live.

The benefit of AI, with the benefit of AI that's in air quotes, 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. There's some statistics about how the people that are fresh out of school these days are historically underemployed relative to the general population, at least in the US where I live.

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 patity. 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 just learning how to fill in blocks they'll kin within the job.

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 patity. 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 just learning how to fill in blocks they'll kin within the job.

Yeah, I mean.

Yeah, I mean.

The the trick is that those of us that have spent a whole lot of time debugging software right and like finding the problems and digging into them and trying to figure out what's going on that kind of stuff. It's going to be really hard for younger folks to get hired into those jobs so that they have time to build the experience to be able to do that. 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. And then it's going to be a real mess, especially since from what I can tell, the code that the AI's generated are a lot buggier and buggier in weirder like randomish kind of ways. 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, you know, all that kind of stuff AI code is different. It's just like, Okay, 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.

The the trick is that those of us that have spent a whole lot of time debugging software right and like finding the problems and digging into them and trying to figure out what's going on that kind of stuff. It's going to be really hard for younger folks to get hired into those jobs so that they have time to build the experience to be able to do that. 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. And then it's going to be a real mess, especially since from what I can tell, the code that the AI's generated are a lot buggier and buggier in weirder like randomish kind of ways. 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, you know, all that kind of stuff AI code is different. It's just like, Okay, 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.

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

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

I guess so.

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.

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.

Yeah, it's just 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. Would you mind walking me through what that means?

Yeah, it's just 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. Would you mind walking me through what that means?

Yeah, So basically what that study found, there were 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. And code churn is basically when you push something you like, add a line of code, you push it into two test or to production, 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, right. So basically what that means is that the line of code that got created, 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, right, And the percentage of lines or the number of lines that that get changed fairly quickly after they get submitted, has gone way up since the since the implementation of get hub copilot. So and this is across like most of the giant you know, millions of lines of codes on GitHub and.

Yeah, So basically what that study found, there were 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. And code churn is basically when you push something you like, add a line of code, you push it into two test or to production, 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, right. So basically what that means is that the line of code that got created, 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, right, And the percentage of lines or the number of lines that that get changed fairly quickly after they get submitted, has gone way up since the since the implementation of get hub copilot. So and this is across like most of the giant you know, millions of lines of codes on GitHub and.

For a simpleton me, why does it being changed? Why is changing it so often bad?

For a simpleton me, why does it being changed? Why is changing it so often bad?

Like? Well, I mean, so, I mean if you do it right the first time, you can move on to the next thing.

Like? Well, I mean, so, I mean if you do it right the first time, you can move on to the next thing.

Ah.

Ah.

Right.

Right.

If it's like you know, if you're writing a document and you put put the document in there and then you like you're get you're in in Google Docs and you're like tracking changes and it's like, Okay, this sentence has changed seventeen times.

If it's like you know, if you're writing a document and you put put the document in there and then you like you're get you're in in Google Docs and you're like tracking changes and it's like, Okay, this sentence has changed seventeen times.

Obviously the person isn't happy with that, right.

Obviously the person isn't happy with that, right.

So the generative code isn't good, right, and so people see you need to change.

So the generative code isn't good, right, and so people see you need to change.

That's the presumption, yes, and.

That's the presumption, yes, and.

So I 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 were other things as well, So.

So I 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 were other things as well, So.

They measured that they measured.

They measured that they measured.

Uh like moved code.

Uh like moved code.

Yeah, that the move code.

Yeah, that the move code.

The thing I was talking about earlier, where the uh you've got a bunch of different places in the code that all do the same You try to do the same function, but they do it.

The thing I was talking about earlier, where the uh you've got a bunch of different places in the code that all do the same You try to do the same function, but they do it.

In different ways. Normally, what would happen is you'd have your you do it.

In different ways. 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 do that thing again in a different place. 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 because it already works, right, And then that way you've got you know, however, you go that stuff from the server, you're fetching it the same way, but with this thing. Basically instead of doing that, you've got copy paste. Okay, when we put another one here, and we put another one here, let me put another one here, and it's a it's a maintenance nightmare.

You do a thing here, right, and then at some point in the future you need to do that thing again in a different place. 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 because it already works, right, And then that way you've got you know, however, you go that stuff from the server, you're fetching it the same way, but with this thing. Basically instead of doing that, you've got copy paste. Okay, when we put another one here, and we put another one here, let me put another one here, and it's a it's a maintenance nightmare.

So for the for the audience as well, how does the software developer actually use GitHub? Like really simple stuff? I realized, but I think it's important for people to It just occurred to be like, this may be something that most listeners don't know, which is good to I think it's good.

So for the for the audience as well, how does the software developer actually use GitHub? Like really simple stuff? I realized, but I think it's important for people to It just occurred to be like, this may be something that most listeners don't know, which is good to I think it's good.

Yeah.

Yeah.

So so what we do is we basically make changes to code. We get to the point where we the developer, are happy with the way it's set up on our machine, and then we do what it's called a push, and we basically send all that code, submit all that code up to get hub, 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 and that kind of stuff. And then at some point we have a thing called a poor request, which is basically a thing that says, Okay, I would like this to go into production now, or more or less, 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, go look at this or that kind of thing, right, And the poor requests is kind of the unit of work kind of.

So so what we do is we basically make changes to code. We get to the point where we the developer, are happy with the way it's set up on our machine, and then we do what it's called a push, and we basically send all that code, submit all that code up to get hub, 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 and that kind of stuff. And then at some point we have a thing called a poor request, which is basically a thing that says, Okay, I would like this to go into production now, or more or less, 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, go look at this or that kind of thing, right, And the poor requests is kind of the unit of work kind of.

So with get hub you almost use it like an organizational code dump, centralize all the code. Sorry just for the non coding as well. And I think it's I think that the LLLM industry has done a really good job of dancing around these terms and selling them to people like me. While 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 co pilot, that's good, and this is good because software is coding. But it kind of feels like, I don't know, all of this is taking the one thing, like one major pot out of software development and ruining it. And I don't even mean coding. I mean it's the intentionality behind software design and infrastructure and maintain Like there's it seems like they're removing intention in multiple parts.

So with get hub you almost use it like an organizational code dump, centralize all the code. Sorry just for the non coding as well. And I think it's I think that the LLLM industry has done a really good job of dancing around these terms and selling them to people like me. While 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 co pilot, that's good, and this is good because software is coding. But it kind of feels like, I don't know, all of this is taking the one thing, like one major pot out of software development and ruining it. And I don't even mean coding. I mean it's the intentionality behind software design and infrastructure and maintain Like there's it seems like they're removing intention in multiple parts.

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 hacking code, right, And so what they're saying is that basically the job of a developer is basically just you know, typing, basically, right, 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, all that work is basically not important.

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 hacking code, right, And so what they're saying is that basically the job of a developer is basically just you know, typing, basically, right, 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, all that work is basically not important.

And I mean I two words which would probably annoy you this is I feel like vibe coating is the other part of this. So if I'm correct, correct me if I'm wrong, vibe coating is just typing stuff into an LEM and software comes out and hopefully it works.

And I mean I two words which would probably annoy you this is I feel like vibe coating is the other part of this. So if I'm correct, correct me if I'm wrong, vibe coating is just typing stuff into an LEM and software comes out and hopefully it works.

Yeah. Vibe coating is basically when you intentionally try it.

Yeah. Vibe coating is basically when you intentionally try it.

Well, I don't know, but intentionally, but basically you make a point of not digging into the code and looking at what the LM is doing, 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, 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? 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, and you just hope that this whatever you look at and has the right vibe and that you know, 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.

Well, I don't know, but intentionally, but basically you make a point of not digging into the code and looking at what the LM is doing, 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, 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? 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, and you just hope that this whatever you look at and has the right vibe and that you know, 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.

How do you feel about vibe coating?

How do you feel about vibe coating?

So I do it.

So I do it.

Sometimes vicoding is great for a thing that you're going to do once and then throw away.

Sometimes vicoding is great for a thing that you're going to do once and then throw away.

Yeah.

Yeah.

Right, So if it's like, you know, okay, I want to I want to do a thing. 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. No big deal, right, like a prototype almost, yeah, basically, 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, and then let me see what I can learn from that to move into my big maintainable project. But for anything that's like, you know, this thing needs to run for a while, this thing's needs to not get hacked.

Right, So if it's like, you know, okay, I want to I want to do a thing. 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. No big deal, right, like a prototype almost, yeah, basically, 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, and then let me see what I can learn from that to move into my big maintainable project. But for anything that's like, you know, this thing needs to run for a while, this thing's needs to not get hacked.

This thing needs to you know, not crash. It's a really bad idea.

This thing needs to you know, not crash. It's a really bad idea.

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

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

Yeah.

Yeah.

And the other thing is that there's an adversarial component, right, so people will intentionally try to go hack that thing that's sitting on the internet, right, Yeah, in a way that they don't intentionally try to go mess with the story that you wrote, right, 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. And if they can break it, then that's a whole other set of problems that you now have.

And the other thing is that there's an adversarial component, right, so people will intentionally try to go hack that thing that's sitting on the internet, right, Yeah, in a way that they don't intentionally try to go mess with the story that you wrote, right, 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. And if they can break it, then that's a whole other set of problems that you now have.

It feels like quality assurance is just never part. Oh no, they are they claiming they're going to do quality assurance with large language models. Yet they must some.

It feels like quality assurance is just never part. Oh no, they are they claiming they're going to do quality assurance with large language models. Yet they must some.

People are Yeah, I mean, to be honest, a lot of companies have just been getting rid of quality assurants over the years.

People are Yeah, I mean, to be honest, a lot of companies have just been getting rid of quality assurants over the years.

Right.

Right.

Really, when I worked at IBM, we didn't have quality assurance at all. They would, no, seriously, they would do this. I was in IBM's Cloud group and they would do these these what do they call them, uh, packathon kind of things that they didn't call that.

Really, when I worked at IBM, we didn't have quality assurance at all. They would, no, seriously, they would do this. I was in IBM's Cloud group and they would do these these what do they call them, uh, packathon kind of things that they didn't call that.

I don't know what they called it.

I don't know what they called it.

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, But they didn't have dedicated testers anymore because they decided I guess that they didn't think they were worth the money.

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, 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.

I don't know, but we had some issues because of that.

When spinal movement happened.

When spinal movement happened.

I was in I don't know, so I was at IBM in like twenty seventeen, twenty eighteen, right, so it would have been sometime prior to that.

I was in I don't know, so I was at IBM in like twenty seventeen, twenty eighteen, right, so it would have been sometime prior to that.

When I got there, they didn't have any QA folks.

When I got there, they didn't have any QA folks.

Really just feels like the it's the management problem as well. It's the management cotton people.

Really just feels like the it's the management problem as well. It's the management cotton people.

I would think.

I would think.

So it's a real shame as well. And I 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.

So it's a real shame as well. And I 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.

Well that's that's my expert, right, Yeah, just a potential worry, right.

Well that's that's my expert, right, Yeah, just a potential worry, right.

Right, so that the more of this we get and the more issues that we have, 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 it will take.

Right, so that the more of this we get and the more issues that we have, 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 it will take.

The crypto bubble took way longer to pop than I expected.

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

So I don't know how long it's going to be before this one does, but 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 is has all of these vulnerabilities that nobody's bothering to check for at the moment.

Right, and those vulnerabilities again non technical way, I read that it was like the call upon things on GitHub that don't exist, so bad actors create something that resembles what it's pulling from.

Right, and those vulnerabilities again non technical way, I read that it was like the call upon things on GitHub that don't exist, so bad actors create something that resembles what it's pulling from.

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 eighties, right right, you know, the Morris worm and that kind of stuff. And basically there are no own ways that code if you have to write it in a particular way in order for it to be secure, right right, And even then sometimes people come up with novel ways of making something not secure, and.

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 eighties, right right, you know, the Morris worm and that kind of stuff. And basically there are no own ways that code if you have to write it in a particular way in order for it to be secure, right 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 it's possible to explain.

How how do you have to write it to make it secure? 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. 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. You have to make sure that it doesn't have the opportunity to be able to write to places on your disc that it shouldn't be able to write to. 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, you know, all that kind of stuff. And when those things don't happen, you end up with you know, so and so got hacked. You know, turns out that somebody, we think maybe China, is reading the email of the you know, people in Congress. You get another letter in the mail that says your social Security number has been you know, leaked by you know, some credit checking firm or something like that.

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. 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. You have to make sure that it doesn't have the opportunity to be able to write to places on your disc that it shouldn't be able to write to. 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, you know, all that kind of stuff. And when those things don't happen, you end up with you know, so and so got hacked. You know, turns out that somebody, we think maybe China, is reading the email of the you know, people in Congress. You get another letter in the mail that says your social Security number has been you know, leaked by you know, some credit checking firm or something like that.

Even even like I think it was what the big hot target data breach from a while back was through the HVAC system. It was it was it's just except now we've got and that was with humans writing the code right, imagine if we didn't know. Oh god, it really does feel like the young people are going like that. 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. 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.

Even even like I think it was what the big hot target data breach from a while back was through the HVAC system. It was it was it's just except now we've got and that was with humans writing the code right, imagine if we didn't know. Oh god, it really does feel like the young people are going like that. 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. 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.

Yes, I mean, there's an argument that says we never got it right in the first place. But I mean, I mean, if you think about it, software has been a thing for what fifty years, sixty years, seventy years, right, I mean compare that to like construction engineering or bridge building or that kind of stuff. Right, we're still, you know, relatively speaking, in the infancy, In our infancy as a as an industry. You know, it's been a it's been a constant evolution, and a lot of times the things that were the things that we did to solve a problem that we had ended up causing other problems.

Yes, I mean, there's an argument that says we never got it right in the first place. But I mean, I mean, if you think about it, software has been a thing for what fifty years, sixty years, seventy years, right, I mean compare that to like construction engineering or bridge building or that kind of stuff. Right, we're still, you know, relatively speaking, in the infancy, In our infancy as a as an industry. You know, it's been a it's been a constant evolution, and a lot of times the things that were the things that we did to solve a problem that we had ended up causing other problems.

Right.

Right.

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 project, you know, construction projects. And it turns out that when you're going to build a bridge, you know beforehand what you need to build a bridge to do. 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 and they're like, oh, why don't we put this over here, 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. And so we gotten this problem where you would create these project plans about how you were going to to build this thing, and you would never be anywhere close to on time because things would change the whole time. And so they created this thing called the agile methodology. I'm drastically simplifying. There were steps in the middle, but basically, so this agile thing is where we instead of saying, okay, so this is what the whole project's going to look like, we're gonna 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 it depends. 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, 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, and what do we want to do next? 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. The problem with that is kind of the same way that dates always ran out in water 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, 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.

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 project, you know, construction projects. And it turns out that when you're going to build a bridge, you know beforehand what you need to build a bridge to do. 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 and they're like, oh, why don't we put this over here, 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. And so we gotten this problem where you would create these project plans about how you were going to to build this thing, and you would never be anywhere close to on time because things would change the whole time. And so they created this thing called the agile methodology. I'm drastically simplifying. There were steps in the middle, but basically, so this agile thing is where we instead of saying, okay, so this is what the whole project's going to look like, we're gonna 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 it depends. 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, 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, and what do we want to do next? 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. The problem with that is kind of the same way that dates always ran out in water 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, 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?

When are we going to wrap this up?

Right? And how has that led to things agting worse? Is it that just software culture software development culture has been focused on short term perpetually.

Right? And how has that led to things agting worse? Is it that just software culture software development culture has been focused on short term perpetually.

Is the short term is part of it.

Is 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.

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 right, That's that's always the case. But the other thing is that you end up with a real.

It, right right, That's that's always the case. But the other thing is that you end up with a real.

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.

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, some kind of thing. You know, companies are only worried about what happens next quarter.

Know, some kind of thing. You know, companies are only worried about what happens next quarter.

Right.

Right.

If you're only worried about what's going to happen the next week or the next four weeks, the things that you look on, look at, you know, tends not to have the longer term implications that sometimes you need. Right And there are times you get close to the end and you're like, oh, you know, we didn't think about this problem yeaheah.

If you're only worried about what's going to happen the next week or the next four weeks, the things that you look on, look at, you know, tends not to have the longer term implications that sometimes you need. Right And there are times you get close to the end and you're like, oh, you know, we didn't think about this problem yeaheah.

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

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

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

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

Is this a problem throughout organizations of all sizes? Is this a consultancy problem. Is it everywhere?

Is this a problem throughout organizations of all sizes? Is this a consultancy problem. Is it everywhere?

It's most places, Huh, there are, there are some places that are.

It's most places, Huh, there are, there are some places that are.

Usually in startups, we're a lot more ad hoc and we're a lot more you know, focused on trying to get things done. The basically, the the 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, the more of this overhead you put in place, and the more complicated things get as just as a as a management structure kind of thing.

Usually in startups, we're a lot more ad hoc and we're a lot more you know, focused on trying to get things done. The basically, the the 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, the more of this overhead you put in place, and the more complicated things get as just as a as a management structure kind of thing.

And this in the big So this is something you'd seem like a Google and an Amazon as well.

And this in the big So this is something you'd seem like a Google and an Amazon as well.

Oh absolutely so.

Oh absolutely so.

Do you do you think it has the same organizational effects.

Do you do you think it has the same organizational effects.

Or largely yes.

Or largely yes.

The so those organizations tend to be well, those organizations historically have tended to be.

The so those organizations tend to be well, those organizations historically have tended to be.

Before the recent like in shitification wave.

Before the recent like in shitification wave.

Those I'm assuming I can swear on this, Yeah, yeah, 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, and so they tend to try at least we try to run interference with management and to try to, you know, make sure everybody's on the same page and that kind of stuff. A lot of a lot, not all, but a lot of problems can get get lessened if you have people in the organization that are at 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 right, to.

Those I'm assuming I can swear on this, Yeah, yeah, 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, and so they tend to try at least we try to run interference with management and to try to, you know, make sure everybody's on the same page and that kind of stuff. A lot of a lot, not all, but a lot of problems can get get lessened if you have people in the organization that are at 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 right, to.

Make sure people aren't building the same thing I'm guessing, or are building the right thing in the right way.

Make sure people aren't building the same thing I'm guessing, or are building the right thing in the right way.

Yeah, and that 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.

Yeah, and that 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.

Yes, So, based on my analysis at these companies, that's definitely gone out the window. I mean, even with LLLM integrations. So there was a Johnson and Johnson story that went out Wall Street General a couple of weeks ago where it was like they had eight hundred and ninety LM project Generative AI project, of which Taitla the Pereto principle wins again ten fifteen percent of them were actually useful. And the thing that stunned me about that of them, the fact to confirmed my biases, which I love, was the fact that they were eight hundred and ninety at the fucking things and no one was like should we have this many that There was no like like selfare 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 boxes.

Yes, So, based on my analysis at these companies, that's definitely gone out the window. I mean, even with LLLM integrations. So there was a Johnson and Johnson story that went out Wall Street General a couple of weeks ago where it was like they had eight hundred and ninety LM project Generative AI project, of which Taitla the Pereto principle wins again ten fifteen percent of them were actually useful. And the thing that stunned me about that of them, the fact to confirmed my biases, which I love, was the fact that they were eight hundred and ninety at the fucking things and no one was like should we have this many that There was no like like selfare 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 boxes.

Yeah, I mean so the other thing.

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 generative AI. People didn't expect, right. 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 rottocomplete.

So understand that again greatly oversimplifying a lot of the new stuff that's happened with large language machines, large language models, and generative AI. People didn't expect, right. 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 rottocomplete.

Stuff as it is.

Stuff as it is.

It was, right, And so there's this belief that 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 that hasn't seemed to really pan out the last couple of years from what I can see, but that 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. 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, and so we don't want to get left behind. It kind of reminds me of the rumors that they talked about back in the eighties when the CIA was doing all this psychic research, because supposedly the Russians were doing psychic research 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.

It was, right, And so there's this belief that 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 that hasn't seemed to really pan out the last couple of years from what I can see, but that 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. 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, and so we don't want to get left behind. It kind of reminds me of the rumors that they talked about back in the eighties when the CIA was doing all this psychic research, because supposedly the Russians were doing psychic research 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.

LMM Kultrum exactly. Yes, the title of the episode, So, okay, koltr aside, is this something you're seeing in software development though, because I know I've seen that in management or it's just going to like shut the ship in there. This seems like it's an important thing, right or is this Are you seeing it within software development?