Speaker 1: All zone media, mother father, come quick, it's better offline.
Speaker 1: The tech podcast I'm Your host ed Zetron What. A
Speaker 1: few weeks ago, the Internet was captivated by the work
Speaker 1: of one particularly pissed off software developer who claimed, and
Speaker 1: I quote the title of his blog, I will fucking
Speaker 1: pile drive you if you mention AI again. The writer,
Speaker 1: based in Australia, lays out in detail how infuriating a
Speaker 1: distraction AI has become from the wider problems riddling many
Speaker 1: modern tech companies, as well as the noxious, nasty presence
Speaker 1: of grift and management consultant types that are deliberately keeping
Speaker 1: it inflated, regardless of whether it actually means anything. One
Speaker 1: particular quote stood out to me. You see, while hype
Speaker 1: is nice, it's only nice in small bursts. For practitioners,
Speaker 1: we have a few things that a grifter does not have,
Speaker 1: such as job stability, genuine friendships and souls. What we
Speaker 1: do not have is the ability to trivially switch fields
Speaker 1: the moment the gold rush is over, due to the
Speaker 1: sad fact that we actually need to study things and
Speaker 1: build experience. Grifters, on the other hand, wield the omnitool
Speaker 1: that they self aggrandizingly call politics. That is to say,
Speaker 1: it turns out that the core competency of smiling and
Speaker 1: promising people things that you can't actually deliver is highly transferable.
Speaker 1: This piece caught both my eye and that of Cool
Speaker 1: Zone Media's Robert Evans, who assured me he promised that
Speaker 1: I'd be allowed to leave the Cool Zone Media pain
Speaker 1: cage if I was able to get the author of
Speaker 1: the piece on the show. So that's what I did.
Speaker 1: Adjoining us to talk about this incredibly aggressive blog is
Speaker 1: Nikol Suresh, who's the director at Hermit Technology and an
Speaker 1: excellent blogger. Nick, thank you so much for joining us.
Speaker 2: Oh, thank you for the very kind words. I'm super
Speaker 2: excited to be here. When that piece came out, at
Speaker 2: least three people said, hey, have you heard of ed
Speaker 2: Citron And I was like, well, I'm talking to Tomorrow'll
Speaker 2: be excited now I will.
Speaker 1: So you're angry, I think we've kind of got that,
Speaker 1: and I share your anger. But what is it about
Speaker 1: this that really boils your blood that makes you want
Speaker 1: to pile drive folks?
Speaker 3: Yeah.
Speaker 2: So it's interesting because a lot of people read that
Speaker 2: piece and they reached out and thought that, you know,
Speaker 2: I'm actually super angry about AI specifically, but a pretty
Speaker 2: consistent through line through my blog.
Speaker 3: It's on a lot of traffic over the past year
Speaker 3: and a half.
Speaker 2: It's not about AI specifically, it's about this massive class
Speaker 2: of non technical managers that have entered the IT space
Speaker 2: and you're essentially cause playing and doing software engineering. The
Speaker 2: thing that is infuriating about the LLLM thing in particular
Speaker 2: is that it's uniquely suited for drifting. So if you
Speaker 2: look at the average company that they can't ship incredibly
Speaker 2: basic applications. And even if you look at something like
Speaker 2: the crypto space, which I don't like, but you look
Speaker 2: around Melbourne, crypto companies actually have some level of engineering discipline.
Speaker 2: You know, they use newer technology, they've got there's things
Speaker 2: in the job descriptions to indicate seriousness.
Speaker 1: Right.
Speaker 2: AI companies don't have that, and I don't think at
Speaker 2: big corporations CEOs are aware that their stoff for just
Speaker 2: typing an import open AI. You know, you're not doing
Speaker 2: any complex work. You just call like an API. You
Speaker 2: just you just send data to a company in the US.
Speaker 2: They do everything, and people down here in Melbourne are
Speaker 2: making out like they're the greatest engineers ever, their thought leaders.
Speaker 2: You should put them on comper stages. It's not hard.
Speaker 2: It's so easy. It takes like a week to make
Speaker 2: something from scratch.
Speaker 4: Yeah.
Speaker 5: I really appreciated that part of your piece because it
Speaker 5: gets at something that's like frustrated me as well, which
Speaker 5: is and I'm not coming at this from the same
Speaker 5: kind of technical background you are, but knowing that there's
Speaker 5: there's legitimate technology here, but all of the people being
Speaker 5: trusted with marshaling it and marshaling these companies that are
Speaker 5: supposed to deliver it to us are on their face. Conman,
Speaker 5: I'm thinking about Sam Altman today, or at least the
Speaker 5: clip came out today where he's like, soon you'll be
Speaker 5: able to just ask asking chat GPT to solve physics for.
Speaker 4: You, solveys.
Speaker 5: That's just a nonsense statement. That's just that's absurd. The
Speaker 5: way we know that, right, we can all tell that
Speaker 5: that's nonsense.
Speaker 2: If if you're not defaming him, that's a crazy thing.
Speaker 3: Like if you guess those are the.
Speaker 4: Woods, I'll find the exact quote.
Speaker 1: But yeah, no, he he, he was very much. That's
Speaker 1: what he said. You've spoken of this kind of like
Speaker 1: organizational cancer inside tech films? Is it this kind of grift?
Speaker 2: Yeah, yeah, it's not specific to technology. It's just the
Speaker 2: technology makes it very very easy. I don't know of
Speaker 2: any industry that doesn't have this massive horde of people
Speaker 2: who don't really know what they're doing, right, but they
Speaker 2: just kind of bulldoze peaceeople socially put it this way.
Speaker 2: So I think my blog is done two million hits
Speaker 2: in the past year and a million realized. And when
Speaker 2: people talked about, you know, offering me work or anything,
Speaker 2: they said they would give me a reference at their workplace,
Speaker 2: but they wouldn't mention that piece because leadership would be
Speaker 2: so embarrassed, like they can't have someone like me around
Speaker 2: going to someone yeah somewhat cool things, it says, fuck
Speaker 2: sometimes can't have that. But no, it's just because like
Speaker 2: the Emperor very clearly has no clothes. I don't even
Speaker 2: really get hate mail because people know I'll just point
Speaker 2: out that they're drifting and they'll have no defense, so
Speaker 2: they just leave me alone.
Speaker 1: Yet, So, how do you think that this has happened?
Speaker 1: It clearly isn't something that happened overnight, but it feels like,
Speaker 1: especially the tech industry, has just been poisoned by product
Speaker 1: managers and management concerns. How did this happen?
Speaker 2: Off the top of my head, something that really influences
Speaker 2: this is just very strange ideas on how things scale.
Speaker 2: There is this I listened to those two episodes you suggested,
Speaker 2: and I think the main one is the Rot Combobble,
Speaker 2: which people should go listen to. And there is this
Speaker 2: idea that everything should scale up forever, and the only
Speaker 2: way to handle that communicatively is like this hierarchical structure.
Speaker 3: But it's really hard to find good people.
Speaker 2: And I think a huge hierarchy can work if you
Speaker 2: only have really great people in it, but it's really hard.
Speaker 3: There's one good.
Speaker 2: Software engineering company I know in Melbourne, Flip Down in
Speaker 2: the CBD, and they regularly interview forty people for one role,
Speaker 2: right because just the quality of candidates not there. If
Speaker 2: you insist you need this massive structure and you need
Speaker 2: a hierarchy for it, you're just going to have to
Speaker 2: insert people who don't know what they're talking about. You
Speaker 2: can't find good people fast enough, and then those people
Speaker 2: who aren't very good to hire other people who aren't
Speaker 2: very good, and soon that's the whole industry.
Speaker 1: Right, and that feels something I'd be writing that will
Speaker 1: end up being a podcast that may run before or off.
Speaker 1: This is just this idea of shareholder supremacy, that the
Speaker 1: companies have been engineered to make a market need work
Speaker 1: to hit analyst expectations. Jack Welch, classic bastard. And it
Speaker 1: feels like this that llms in particular have become the
Speaker 1: ultimate form like the super Saiyan of rock capitalism, where
Speaker 1: people just kind of, like you said, just bullshit about them.
Speaker 1: It's like, yeah, you can do all this shit, right, Yeah,
Speaker 1: it's the future. What is your actual background?
Speaker 2: So I've got a four year qualification in psychology, so
Speaker 2: I mostly did cognitive psychology and circadian science, and then
Speaker 2: I moved over to a postgraduate qualification at one of
Speaker 2: Australia's bigger universities, so that was in data science. I
Speaker 2: did Masters with a little bit of a thesis work
Speaker 2: in it, so I'm reasonably good. I'm not a PhD,
Speaker 2: but I do know what I'm talking about.
Speaker 3: In the space.
Speaker 5: I did want to drill into something because you're coming
Speaker 5: at this like from the perspective of somebody who was
Speaker 5: working in a technical capacity, seeing the way this group
Speaker 5: of people who are talking nonsense are coming in and,
Speaker 5: as you said, kind of like bulldozing their way into
Speaker 5: conversations with people. Can you talk socially about the way
Speaker 5: that kind of happens, because we all sort of see
Speaker 5: the way these people try to monopolize conversations about technology
Speaker 5: at events, you know, if you're coming at it from
Speaker 5: like press at something like CEES, but also just kind
Speaker 5: of if you're looking at things on Twitter or looking
Speaker 5: at just sort of the way popular conversations go. But
Speaker 5: I'm I'm curious about like the social dynamics of these
Speaker 5: people who are coming into organizations full of real people
Speaker 5: trying to do real things and hijacking that for the
Speaker 5: purpose of cashing out.
Speaker 2: Yeah, I think a lot of them are latching onto
Speaker 2: some pre existing level of grift that's just been in
Speaker 2: the industry. So when I entered around twenty eighteen twenty nineteen,
Speaker 2: that's when I got into the Australian tech market, MLMs
Speaker 2: were not this massive thing, right. There were a couple
Speaker 2: of GPT two demos, but there is no way for
Speaker 2: you at a normal company to roll out something like Jenai, right,
Speaker 2: you really had to know what you were doing. You
Speaker 2: didn't have the resources, like you couldn't just hit an
Speaker 2: endpoint somewhere and get a result. And I cannot emphasize
Speaker 2: that enough for like non technical listeners, it's like two
Speaker 2: lines of Python to use open AI. People making these
Speaker 2: chatbots are not serious practitioners. I could teach like my
Speaker 2: thirteen year old cousin how to do this, but there's
Speaker 2: this kind of this pre existing class of person that talkslot,
Speaker 2: gets on stages, doesn't really know what's been going on.
Speaker 2: But they were much smaller back then. They did talk
Speaker 2: about AI relentlessly. But the difference between twenty nineteen and
Speaker 2: twenty twenty four is those people in twenty nineteen didn't
Speaker 2: have any working products. They would talk and then they
Speaker 2: would leave organizations every two years before they were on
Speaker 2: the hook for their failed projects. The difference now is
Speaker 2: people are going to those same people, so you just
Speaker 2: turn up and you go, hey, I'm going to be
Speaker 2: your lead data scientist, your chief.
Speaker 3: Data officer, whatever you want.
Speaker 2: I'm going to do this AI revolution for you, and
Speaker 2: then they can very quickly ship stuff that doesn't quite work.
Speaker 2: But organizations are really bad at tracking what actually drives revenue,
Speaker 2: So the moment you get the flashy product out, people
Speaker 2: think you're some sort of superhero.
Speaker 3: Yeah. And if it's broken, yeah, absolutely so.
Speaker 2: I've been I probably shouldn't say this, but I will
Speaker 2: and just leave the details out. I've been leaked a
Speaker 2: couple of confidential documents from i would say small to
Speaker 2: medium businesses on how JENNYI has worked in their chetbots.
Speaker 2: I can't name the companies because I'm not supposed to.
Speaker 2: The documents like, it's not impressive. Even the ones that
Speaker 2: sort of work. You get really weird statistics like interacting
Speaker 2: with the chatbot predicts tickets being escalated to human support teams,
Speaker 2: like way worse than usually.
Speaker 3: But they're still rolled about, right, that's good.
Speaker 1: So the one thing that they say, this is going
Speaker 1: to be able to do customer service, very cool.
Speaker 3: I definitely can't do it now.
Speaker 1: Great Jesus.
Speaker 5: Do you get the sense they're rolling it out even
Speaker 5: though they're not saying an immediate like positive effect, because
Speaker 5: the kind of effect on their potential valuation by throwing
Speaker 5: AI in is higher than whatever they lose by having
Speaker 5: a less efficient actual solution.
Speaker 3: I think it's threefold.
Speaker 2: So the first one is it's speculative, which means even
Speaker 2: if I if I was dishonest and I thought it
Speaker 2: was bad for the company, I might want AI on
Speaker 2: my CV specifically, it doesn't actually have anything to do
Speaker 2: with the company, right, it's just for me. The second
Speaker 2: one is, yeah, there's obviously it's very easy to get funding.
Speaker 2: Someone reached out to me a CEO of a company
Speaker 2: that does LM work, and this person admitted to me
Speaker 2: their product doesn't work, so they don't accept funding because
Speaker 2: they're trying to get it to work and people are
Speaker 2: still flinging money at them. This thing that, like self
Speaker 2: admittedly doesn't function.
Speaker 3: That's very cool. Yeah, it's great. It's great that the
Speaker 3: industry is in that position.
Speaker 5: And the last one is good for them.
Speaker 3: The last one is, you know, the chatbot piece.
Speaker 2: I don't work in that domain, but I kind of
Speaker 2: wonder is it cheaper to just provide bad customer service,
Speaker 2: lay off all your supports offf Like, when I'm trying
Speaker 2: to cancel my mobile plan, do they actually care that
Speaker 2: I got frustrated and put the call down?
Speaker 3: That sounds good for.
Speaker 5: Them, right, Well, yeah, I mean that's one of the
Speaker 5: things that's so insane about this is that this could
Speaker 5: work out for them. At least in I still don't
Speaker 5: think that when you're looking kind the kind of like
Speaker 5: the dollar amount of valuations that like open Ai is seeing,
Speaker 5: I don't think that letting companies that don't give a
Speaker 5: shit about customer service economize more is going to be
Speaker 5: the size of industry that they're hoping for. You're certainly
Speaker 5: not going to It's not trillions of dollars in value, right,
Speaker 5: that could be a profitable business and just making everything
Speaker 5: a little bit worse for everybody like that, that could
Speaker 5: be a very good business to be it. Yeah, just Google, No,
Speaker 5: I mean yeah, I mean yeah, that's Google's done well
Speaker 5: off of that.
Speaker 1: It's just just making things gradually, iteratively worse.
Speaker 2: Well, I will say that I get a lot of
Speaker 2: email from people who left Google, and you know, some
Speaker 2: of them. It's a huge company, so they do some
Speaker 2: useful stuff, but a lot of people were like, I
Speaker 2: left because it sucks there now.
Speaker 3: So that's that's definitely a thing.
Speaker 1: So you said the data science field was large but
Speaker 1: largely fraudulent. What exactly does that? Does it mean that
Speaker 1: most of data science is just grifting or is it
Speaker 1: just something a little more deep.
Speaker 2: It's a little deeper than that. So as a as
Speaker 2: a technical discipline, machine learning is very very serious, right.
Speaker 2: You do see it used and genuinely helpful things. It's
Speaker 2: probably being used right now as we're recording this. It's
Speaker 2: somewhere in the supply chain, and you'll hear more old
Speaker 2: cool practitioners. They get very annoyed at the words AI
Speaker 2: and machine learning. They say things like, it's just statistics,
Speaker 2: you know it, Ellen are obviously doing something. It would
Speaker 2: be wrong to just say they're classical statistics and not
Speaker 2: impressive in any way. But when I say it's grifting,
Speaker 2: I mean this whole artificial intelligence thing. The people deciding
Speaker 2: on the size of the data science market are not technicians,
Speaker 2: so when you say AI, they're thinking Skynet, generative AI,
Speaker 2: general intelligence. Like they really have no idea what they're
Speaker 2: hiring for. But they'll do things like say we need
Speaker 2: to hire twenty data scientists tomorrow, right, like that's.
Speaker 1: Right, without really knowing what they do with them, no.
Speaker 2: Idea what they do with them. And it's really hard
Speaker 2: to solve problems with data science, right. It is entirely
Speaker 2: possible to have a problem that is fundamentally intractable, no
Speaker 2: matter how discipline your team is because the data doesn't exist,
Speaker 2: or the problem's just too hard mathematically.
Speaker 3: That happens all the time.
Speaker 1: It almost feels like the problem with the tech industry
Speaker 1: is that nobody knows what they're doing. You have people
Speaker 1: that know stuff, how to do things, and then they
Speaker 1: get a job at Google in a pile of people
Speaker 1: that can do stuff run by someone who goes all right, dickheads,
Speaker 1: put the AI in it now, and then stuff comes out.
Speaker 1: It almost like the problem you mentioned earlier of just
Speaker 1: they're not being enough good people also appears to be
Speaker 1: there are no good managers.
Speaker 5: I wonder kind of pivoting or not pivoting, But building
Speaker 5: on that, I wonder how much of it is that
Speaker 5: the guys who are really good at keeping the hype
Speaker 5: going are also just better socially than the kind of
Speaker 5: people who are really good at coding and are really
Speaker 5: good at the actual like science, Like if some of
Speaker 5: the being bulldozed effect is that the people who really
Speaker 5: know their shit just are not used to the kind
Speaker 5: of energy that a hype man is capable of deploying
Speaker 5: against them.
Speaker 2: Yeah, so this has come up. I've thought about this
Speaker 2: a lot. So that's a kind of component of engineering.
Speaker 2: I work on a lot not hyping myself up, but
Speaker 2: actually being able to hold conversations. But that's not quite
Speaker 2: the attribute I see in the managers who do this
Speaker 2: kind of thing, because what you're describing is like a
Speaker 2: pure conman. And at least and not to be mean
Speaker 2: to people who aren't comment but I'm leaking, like at
Speaker 2: least there's some skill in that. But what we're talking
Speaker 2: about is they.
Speaker 5: Just like this is where Steve Jobs comes in, right,
Speaker 5: there's a version of this that requires talent.
Speaker 2: Right right, Like it may not be talented, I respect
Speaker 2: like morally, but I'm like that it's an actual skill set.
Speaker 2: But we're talking about people who have really just learned
Speaker 2: how to like mimic the trappings of success and responsibility.
Speaker 2: You know, they're real big on suits, they're real big
Speaker 2: on talking very slowly with long pauses, but like they
Speaker 2: don't have novel thoughts.
Speaker 3: Their brain has just had.
Speaker 2: Like Forbes magazine flashed onto it like there's nothing else there.
Speaker 3: So maybe talking about social skill and bulldozing, I'm.
Speaker 6: Not talking about the war, right, and you know, we're
Speaker 6: not talking about people who are doing this very savvy
Speaker 6: political piece where they finesse things, and you know, it's
Speaker 6: very machiavellian. We're talking about people who just turn up
Speaker 6: and if you point out they don't know what they're
Speaker 6: talking about.
Speaker 2: They're a fucking dick to you. And they do this
Speaker 2: until you leave them alone, and that's their whole career.
Speaker 2: The industry is just full of that. They're not even smart.
Speaker 2: I have seen an executive at a restaurant order the
Speaker 2: wrong dish, have their family eat the whole thing, then
Speaker 2: tell the weight stuff that like, hey, you brought us
Speaker 2: the wrong thing, and when a kid piped out, they
Speaker 2: shushed the kid.
Speaker 3: You know.
Speaker 2: It's it's not like a talent that they have cultivated
Speaker 2: in the menagerial space. It's like personality disorder that just
Speaker 2: leads into everything.
Speaker 1: In ruins in a reality.
Speaker 3: How I want.
Speaker 5: It's some of it is because like I talk about
Speaker 5: jobs a lot, and I think you have to because
Speaker 5: a lot of these guys, if not all of them,
Speaker 5: at some level wish they were him, right with the
Speaker 5: exception of the not you know, the medical issue, but
Speaker 5: like they's he's like mythologized to a significant degree. Especially
Speaker 5: I'm recording from San Francisco right now. I mean He's
Speaker 5: almost like a saint down here, and I feel like
Speaker 5: the act of copying him, you get these people who
Speaker 5: are like carbon copies of just the personality disorder without
Speaker 5: any of the actual insight. And I think that's like
Speaker 5: further exacerbated because they're all like, yeah, read the Art
Speaker 5: of War, read like one of three Malcolm Gladwell books,
Speaker 5: Read The Four Hour Body, and do not read anything else.
Speaker 5: There's no humanities, there's nothing like because all you need
Speaker 5: to learn how to do is be the most optimized
Speaker 5: asshole you can be.
Speaker 2: I like, how you just pick the If I had
Speaker 2: hit Man budget, like that would be my list as
Speaker 2: a data sideist. Malcolm Glenwell, Like I might need him
Speaker 2: more than anyone on the planet.
Speaker 5: Oh, I'm right there with you, buddy. He's he's been advertise,
Speaker 5: I got our shows and oh man, I don't love it.
Speaker 4: I don't love it.
Speaker 1: So with that in mind, Nick, what do you think
Speaker 1: of Sam Oltman.
Speaker 2: I don't really know a whole bunch about him because
Speaker 2: out here in Melbourne, I don't really play around in
Speaker 2: the fang super huge space.
Speaker 3: Right.
Speaker 2: Our clients are relatively small. I work at like medium
Speaker 2: sized businesses, tiny compared to the size of Google and
Speaker 2: open AI. All I will say is, if he said
Speaker 2: what you just said about physics, like, he needs to
Speaker 2: come out with the greatest innovation I've ever seen in
Speaker 2: the next two years, or he will be one of
Speaker 2: the most insane people I've ever heard of, right, Like,
Speaker 2: that's he really has to deliver on that statement, or
Speaker 2: he's obviously full of shit.
Speaker 1: It just it blows me away that he's even able
Speaker 1: to say it without someone just being like, what the
Speaker 1: fuck you talking about? Sam Oltman? Sam Oltman, did you
Speaker 1: hit your head somewhere on the way here? Because it's
Speaker 1: not even the first insane thing he said. He has
Speaker 1: said so many times. I was super smart. It's going
Speaker 1: to be a super smart friend that knows everything about you?
Speaker 1: The fuck are you talking? What does any of this mean?
Speaker 1: And my own frustration I've shared about the media is
Speaker 1: that no one ever seems to say the appropriate thing,
Speaker 1: which is wait, what was that? Excuse me, mate? What?
Speaker 1: But it almost feels with everything you're talking about, and
Speaker 1: in your excellent blog that also feels like the problem
Speaker 1: You've just got these guys who just say things raise
Speaker 1: money go up in organizations and don't actually do anything like,
Speaker 1: Samulman did not make gpt someone else did that. Mirror
Speaker 1: Morati did not do it. Cto of open Ai didn't
Speaker 1: do it either.
Speaker 4: It's just so strong. It feels like we're living in.
Speaker 1: An alternate reality at times, and it's freaking me out.
Speaker 1: I wan to be honest, it's I'm putting on the
Speaker 1: clown makeup, the joker makeup almost every day now.
Speaker 2: Was Miramuradi the one who couldn't answer that question on
Speaker 2: whether they used YouTube to try, Yes, I mean.
Speaker 5: Yes, yes, she sure couldn't. And I found at least
Speaker 5: I watched the video with captions while we were doing
Speaker 5: this with sam Altman, and the exact statement was basically,
Speaker 5: someday you'll be able to ask chat gpt U discover
Speaker 5: physics for me. It'll do it, discover all the physics
Speaker 5: something like that. I've got the link in there, but
Speaker 5: like just just a nonsense statement, like at least at
Speaker 5: least go to make it. You could make like star
Speaker 5: Trek claims, right, like that's the rational end of this.
Speaker 5: I don't know that it'll actually be that good, but
Speaker 5: be like, one day I'll have a computer and you
Speaker 5: can tell it to do all these things and it'll
Speaker 5: it'll organize your life and answer questions, it'll run complex systems,
Speaker 5: and it'll let us explore space. That's nonsense too, probably at
Speaker 5: least in any kind of near term, but it's at
Speaker 5: least a thing that theoretically could happen, as opposed to
Speaker 5: just telling a robot to discover physics for you.
Speaker 1: And he says, computer solve all of physics for me,
Speaker 1: which is so funny.
Speaker 5: Right, And it's not what anyone Also, it's just not
Speaker 5: I don't know, I don't need to go into.
Speaker 1: The physics works. You don't solve physics.
Speaker 5: You don't solve physics. And it's not what's appealing about
Speaker 5: the Star Trek dream of a computer that works the
Speaker 5: way the ones on those ships do, right, Like it's
Speaker 5: the the enticing thing is the idea of like technology
Speaker 5: that is hopeful and still needs humans at the center
Speaker 5: of it. And I don't know, he doesn't seem to
Speaker 5: know how to like promise anything but the elimination of
Speaker 5: human creativity interest action, which I guess is part of
Speaker 5: what I find disturbing about him.
Speaker 2: It also, you know, that's obviously something that is said
Speaker 2: to drive stock prices at various companies, right, it is
Speaker 2: like no one believes that, Like, it can't be the case.
Speaker 2: Even the people investing don't believe that, because if you
Speaker 2: could get a computer to solve physics, stock prices wouldn't
Speaker 2: matter anywhere, right, So that can't be why you're investing.
Speaker 1: I just don't know that statement. I haven't really thought
Speaker 1: about too much before right now, but I can't get
Speaker 1: over the oder of soul physics. Like it's a statement
Speaker 1: said by someone who doesn't know what they're talking about
Speaker 1: for other people who don't know what they're talking about
Speaker 1: to go, damn, this boy's smart.
Speaker 5: It kind of makes me suspect ed that he thinks
Speaker 5: about like writing a novel that way too well. The
Speaker 5: author could just solve you know, Wuthering Heights, right, he
Speaker 5: could have the chet GPT do it.
Speaker 4: She could have Jeff PT.
Speaker 1: He would have survived. In my book, yeah, those kids
Speaker 1: would have been safe. In The Brothers Karmels.
Speaker 5: Of Jed GPT accidentally pulled too much from dev into it,
Speaker 5: and the Gatsby ends with some Captain Kirk and Spock
Speaker 5: im preg fanfic.
Speaker 3: The most curs ever heard.
Speaker 1: But that's the thing. It doesn't feel like anything's being
Speaker 1: done about this shit? What was it the end of
Speaker 1: twenty twenty two GPT popped up and now like what
Speaker 1: was like a year and a half into it, I'm like, oh, great,
Speaker 1: I can get a pregnant picture of Garfield with an
Speaker 1: AK forty seven. Great. Now what And you actually kind
Speaker 1: of made not an identical point. I don't think the
Speaker 1: Garfield npreg stuff was in there. I have to look again.
Speaker 1: But you made a similar point where it's like, as
Speaker 1: a company, you probably don't need AI or you're already
Speaker 1: using it.
Speaker 2: Yeah, yeah, I mean it's just baked into the software
Speaker 2: you use.
Speaker 3: Right.
Speaker 2: So we did a little bit of work for a
Speaker 2: managed security provider down here in Melbourne. They have AI
Speaker 2: in their supply chain, but they don't need data scientists
Speaker 2: and specialists doing it here. Right. They've got some vendor
Speaker 2: way upstream, very small company that hires a couple of PhDs.
Speaker 2: They write some algorithms which are not llm's, just like
Speaker 2: all school statistical computing to detect when someone's like trying
Speaker 2: to get into your network.
Speaker 3: You just buy the product from them, right, you.
Speaker 2: Just sit there And it's the same way we get
Speaker 2: benefits out of Zoom and YouTube and Twitter or whatever
Speaker 2: the heck, right, like there's just some stuff baked in
Speaker 2: the back, like you know, have to stress about it.
Speaker 2: It is insane how many companies that have no business
Speaker 2: playing in the space are doing this stuff instead of
Speaker 2: figuring out things like, you know, staff retention averages one year,
Speaker 2: how do we get it up to seven? They don't
Speaker 2: worry about that because they're just fixated on this A
Speaker 2: I think, I'm I need to calm down because I
Speaker 2: bus say I'm going to strangle the next person to
Speaker 2: mention it, but it might come across as more of
Speaker 2: a legal threat.
Speaker 1: Calming down is not how better offline works. My Aura
Speaker 1: ring tells me, I'm working out during the show, so
Speaker 1: I don't have it on today, sadly. But you mentioned
Speaker 1: that they should be doing other things, and you actually
Speaker 1: mentioned in the piece as well, the companies aren't like
Speaker 1: checking their backups to make sure they work. What should
Speaker 1: organizations actually be doing instead of AI.
Speaker 2: Just turn their brains on for like twenty seconds, you know,
Speaker 2: like it's not hard. They're just so hyper fixated on this.
Speaker 2: It's not AI. If it's not lllm's or JENAI. It
Speaker 2: was like older AI. I mean, it's not that it's blockchain,
Speaker 2: it's not that it's quantum. I went to a talk
Speaker 2: at a big conference called I would really put them
Speaker 2: on last year. It went to something Digital Queensland. Last
Speaker 2: year it was dystopian.
Speaker 3: It was just.
Speaker 2: Entirely filled with like non technicians. The stage is just
Speaker 2: filled by people lying to them and half the products
Speaker 2: are about quantum. And that whole talk, they never explained
Speaker 2: what quantum was, right. They were just like, quantum is
Speaker 2: going to revolutionize everything, and I'm in the audience being
Speaker 2: what the hell does that even mean? Right, what do
Speaker 2: you mean quantum? But yeah, what they should be doing,
Speaker 2: it's just like really basic fundamental stuff, right, It's not
Speaker 2: even interesting, which is why no one wants to do it,
Speaker 2: because you can't like rocket ship your way to CEO
Speaker 2: by doing this stuff. But like you need to figure
Speaker 2: out how to like get your teams out of more meetings.
Speaker 2: You need to actually spend time with people on the
Speaker 2: ground and ask them what needs changing in the business.
Speaker 2: You don't need AI to figure all that stuff out.
Speaker 2: Just ask a guy who's been there for a while.
Speaker 2: It's all pretty common sense, and AI is really pulling
Speaker 2: away from that. We talk a lot about the investment
Speaker 2: in AIS a waste of money, but there's probably like
Speaker 2: just as much unrealized opportunity cost in people just wasting
Speaker 2: my time meetings about it, right, like we could just
Speaker 2: be doing something else.
Speaker 3: I just got back from a trip to Fiji.
Speaker 2: And I was volunteered for a tiny bit with my
Speaker 2: girlfriend and animal's Fiji so they can treat a dog
Speaker 2: for about thirty Australian dollars. Can you imagine how many
Speaker 2: dead dogs Open Aye has produced?
Speaker 4: Like you could just oh my god, you could just.
Speaker 2: Away them, right, it's gonna be hundreds of tons like that.
Speaker 3: That's not the way way.
Speaker 1: Way be a little more specific. How did Open Eye
Speaker 1: kill the dogs?
Speaker 3: Well, because we could have just spent the money on
Speaker 3: the dogs, right, Like you just say, you do the math, right?
Speaker 4: This many dogs worth of potential?
Speaker 1: Yeah? Life putting that in the document of if I
Speaker 1: ever get the Sam Oltman interview, Yeah, Sam, talk to
Speaker 1: someone who said thirty bugs I can help a dog?
Speaker 1: How many dogs would you kill to bring KGI to life?
Speaker 4: Atally?
Speaker 5: That's a great one of those things because people there's
Speaker 5: that talk about how much power does it? Used to
Speaker 5: ask a question of chant gpt. How much water are
Speaker 5: we basically pouring on the ground every time we use
Speaker 5: these models? And it's you could say the same things
Speaker 5: about every useless thing humans do, but like we mostly don't,
Speaker 5: right Like. I can say that about like warhammer models,
Speaker 5: but at the end of the day, you get a
Speaker 5: warhammer model, right Like, that's why people keep buying that
Speaker 5: shit as opposed to like at the end of the day,
Speaker 5: I think a lot of the the ultimate result of
Speaker 5: a shitload of what's going on in ai AI right
Speaker 5: now is that briefly a lot of people, hopefully briefly,
Speaker 5: a shitload of people lose their jobs and customer service
Speaker 5: gets wildly worse, maybe forever, right Like, That's.
Speaker 4: That's what we're giving it up for. I would rather
Speaker 4: have little models.
Speaker 3: Yeah.
Speaker 2: Also, no one's turning up in the public service and
Speaker 2: going I need ten million dollars to hire someone to
Speaker 2: paint ultramarines.
Speaker 3: Right like that right? Not right?
Speaker 4: They should be maybe in the UK that.
Speaker 3: Would be a better use. At least someone's having fun.
Speaker 1: You kind of hinted at this in the piece, but
Speaker 1: where does this actually go? Because it feels like we're
Speaker 1: hitting a wall with what lllms can do, and there's
Speaker 1: all of this hype, but there's not that much stuff
Speaker 1: that's come out of it. What happens. You named a
Speaker 1: few scenarios, the first being like magic, like just it
Speaker 1: gets better in two years.
Speaker 2: But otherwise, Yeah, I think realistically the hype just dies
Speaker 2: down and a lot of people are very very embarrassed
Speaker 2: by their overinvestment in the space. You'd hope that's the case.
Speaker 2: It's very possible they'll just kind of get away with
Speaker 2: it and drift their way into something else, especially you know,
Speaker 2: if all their CEO friends did the same thing, I
Speaker 2: don't know who holds them accountable, especially if they're the
Speaker 2: board was you know, it's a bit like arguing with
Speaker 2: people who are like late stage Trump supporters, and it's
Speaker 2: not that they necessarily agree with things he's saying at
Speaker 2: this point.
Speaker 3: I hope that's not too political for this podcast.
Speaker 2: Like yeah, it's just that they've said so many embarrassing
Speaker 2: things that it's like too late to back out now
Speaker 2: that you can't even if you write theory, you're like, Okay,
Speaker 2: you know what he just said something insane. You can't
Speaker 2: admit that you've been saying insane things for four years,
Speaker 2: you know, so you're kind of locked in. Yeah, I
Speaker 2: think the magic scenario is possible. You know, Open Eye
Speaker 2: has tons of money and a lot of PhDs, but
Speaker 2: you know they've got they've got people there who know
Speaker 2: more about the field than I do. Maybe they've got
Speaker 2: something in the wings that's incredible, but I mean we
Speaker 2: would there's no need to speculate on that, right, They'll
Speaker 2: just show us.
Speaker 3: If they've got something, Yes, do it, Yeah, just do it.
Speaker 3: We don't need to speculate.
Speaker 2: And if they do it, I don't even know if
Speaker 2: investing makes sense because I don't know if like in
Speaker 2: that universe, stock markets make sense, right, because they're really
Speaker 2: talking about a level of innovation that would do away
Speaker 2: with all human labor, So it's all doesn't make sense
Speaker 2: to put money into them. Then it's all very very strange.
Speaker 2: What I'm hoping for, to quote my co director ash Leally,
Speaker 2: the people who did this are going to be the
Speaker 2: ex body spray of CEOs, Like we'll just be done with.
Speaker 3: We'll just remember the investment.
Speaker 2: We'll have all the snippets of them getting on their
Speaker 2: ted X stages and then hopefully we'll never work with
Speaker 2: them ever.
Speaker 3: Again, Yeah, Boob.
Speaker 1: Will like, well, it feels like they'll find another grift.
Speaker 1: But I think that's really the question. So it's not quantum,
Speaker 1: it's not blog chain, it's not AI. What the hell
Speaker 1: is next? Like? What now? Where does all of this
Speaker 1: money and hype go? This is the thing that I
Speaker 1: feel crazy about. A number of things drive me crazy.
Speaker 1: It's just where does it go from here? What is
Speaker 1: the next thing that people even can invest in organizations?
Speaker 3: Yeah?
Speaker 2: Well, I mean you know, quantum and blockchain were not
Speaker 2: very predictable, nor were not the elms. There would there
Speaker 2: be something, yeah, nerdifiable, And I suspect it's very possible
Speaker 2: the bubble will not be allowed to pop until there
Speaker 2: is a new thing because I think the people making
Speaker 2: this investment also control when.
Speaker 5: Yeah, the end, it's a load bearing bubble, right, like yeah,
Speaker 5: when this things fall down.
Speaker 1: But when you say they won't allow it to what
Speaker 1: do you mean?
Speaker 2: I just have no idea how long the kind of
Speaker 2: investor class involved in this can just keep pumping money
Speaker 2: into it, right, I have no idea if they're on
Speaker 2: their last legs. I don't have a background in international finance.
Speaker 2: I don't know where the money's coming from it's coming
Speaker 2: from somewhere. I don't understand because I know they're not
Speaker 2: making profits right so right, So I don't know if
Speaker 2: they could keep this going for twenty years if they
Speaker 2: need to, or if we're six months from some sort
Speaker 2: of massive collapse. Like you'd have to at an economist
Speaker 2: in here to comment on that. But I do know
Speaker 2: it's very likely it will collapse at some point. It's
Speaker 2: why at Hermit we don't do AI consulting. We could
Speaker 2: get a lot of work doing it. I just don't
Speaker 2: think it's you know, we're thinking in a five to
Speaker 2: ten year time span. I don't think it's sustainable to
Speaker 2: be in that game.
Speaker 1: It all feels very nihilistic. It all feels just likes
Speaker 1: grifting each other at this point. Like Microsoft is now
Speaker 1: the largest customer of Oracle because Oracle is now building
Speaker 1: data centers for Microsoft to build AI. Yeah. My experience,
Speaker 1: by which I mean reading a great deal of blogs
Speaker 1: and earnings is it doesn't seem like anyone's making any
Speaker 1: money from this, and that seems to be your experience too, right.
Speaker 2: I haven't seen any medium sized company that's stabbled in
Speaker 2: AI make any money off of it. Most of our
Speaker 2: clients fortunately aren't too deep into it, but they bring
Speaker 2: us on and ask things like, hey, you know, we
Speaker 2: just bought this Microsoft product. Can we get it to
Speaker 2: do the thing it's supposed to do? And the answers
Speaker 2: almost always know, like there's just no. We mostly help
Speaker 2: people get out of the AI game, right. They bring
Speaker 2: us in to help them finish the project, and we
Speaker 2: mostly point out that they should just cancel the project,
Speaker 2: and then we go do boring stuff like fix their
Speaker 2: databases because that's what they should have done five years ago.
Speaker 1: And that's kind of what you've been suggesting in the
Speaker 1: piece as well, that the real problem is organizational failure
Speaker 1: almost like like I mentioned earlier though unchecked backups. Yeah, yeah,
Speaker 1: what are other things that people are just not doing?
Speaker 1: Like what is the actual thing being ignored?
Speaker 2: Well, the thing is, it's like a constellation of things, right.
Speaker 2: It would be like asking a writer what is the
Speaker 2: one thing that writer's ignoring. It's about like developing your
Speaker 2: judgment across like the entire field holistically, but that's really
Speaker 2: hard and takes a lifetime. So people just fixate on
Speaker 2: the latest thing and they build their whole career off
Speaker 2: of that. It takes like thirty seconds of skin being
Speaker 2: someone's cv to tell when they're full of shit, Like
Speaker 2: it's really really obvious, who's serious?
Speaker 1: And how do you do it?
Speaker 2: Tell me again? Even that's a judgment piece, right, But
Speaker 2: you know, here's a good example. Most organizations I know
Speaker 2: are really into I don't know if this resonates for
Speaker 2: non technical people, but there's this thing agile. Everyone's just
Speaker 2: obsessed with being maximally agile all the time.
Speaker 1: Please please define that. I know what it is, but
Speaker 1: I'm looking forward to hearing.
Speaker 2: It's it's meant to be a set of like it's
Speaker 2: literally like a four or five sentence thing which says
Speaker 2: you value things like people over processes. Right, it's it's
Speaker 2: literally five pages. And we've built this entire manic industry
Speaker 2: of like books and specialists and this all built around
Speaker 2: these five sentences which just say things like, you know,
Speaker 2: let people work and pay attention to the human And
Speaker 2: when you talk to these consultants, you find out they
Speaker 2: haven't even read those original five sentences.
Speaker 3: Right, that's very very common. I hope it's five sentences.
Speaker 5: It might be that it's again, it's like that copy
Speaker 5: of a copy right at this point, like the we've
Speaker 5: gone to Kinko so many times you can't even really
Speaker 5: tell what's supposed to be written on the sheet. But
Speaker 5: they all know it's deeply important to run a good.
Speaker 2: Business like Camino. But all the clones have eight heads,
Speaker 2: you know, like they'd be right.
Speaker 5: They no longer look like that very handsome stunt man.
Speaker 4: Yeah, it almost.
Speaker 1: Feels like the whole DevOps thing that happened. Remember the
Speaker 1: DevOps boom where I was like, yeah, DevOps is important,
Speaker 1: and then when I had clients, I was like, what's
Speaker 1: stevops meaning? To be like wor It's like the developers
Speaker 1: talk to the business people like why do you need
Speaker 1: software for that? And they would kind of freeze.
Speaker 2: That's that's not over. It's just that it's been overshadowed
Speaker 2: by the AI thing. But so you're agile. We have
Speaker 2: this whole industry of people who turn up and tell
Speaker 2: you how to run meetings every day, and it's like,
Speaker 2: to talk to people, what the hell are you talking
Speaker 2: about DevOps? People still say that constantly, and it's really
Speaker 2: just code for like automate your things sensibly, right, there's
Speaker 2: something useful in there, and the moment someone realized it
Speaker 2: was useful. We just got another gigantic industry around it.
Speaker 2: That's where most that's what most of my blog is
Speaker 2: actually about. The aipiece was just like I've never even
Speaker 2: written about it before because it was so obviously kind
Speaker 2: of bullshit. It didn't warrant it until someone really annoyed
Speaker 2: me last week.
Speaker 1: Yeah, what actually caused you to write that? Was there
Speaker 1: just a guy?
Speaker 2: I think, I, you know, it's been building up for
Speaker 2: like four years. And then finally I think I put
Speaker 2: a picture in there of that scale AI survey. Yes,
Speaker 2: and I just saw that line that was like, was
Speaker 2: it eight percent of companies have not seen gains from
Speaker 2: gen AI?
Speaker 3: And then I chose violence.
Speaker 1: You know, this is done some really inventive threats as well.
Speaker 1: I was very happy to see you say it was
Speaker 1: you need to you need to replace your sweaters with
Speaker 1: full plate to survive my onslaught.
Speaker 4: I I appreciate that.
Speaker 5: I can't think one of the problems we're having, and
Speaker 5: this isn't just a problem in the tech space, but
Speaker 5: you've got a bunch of people who get by on
Speaker 5: not being challenged, or the fact that if you are
Speaker 5: going to have a debate with someone, the act of
Speaker 5: like arguing with them about something lends some sort of
Speaker 5: credibility to their position. When there are certain people that
Speaker 5: what they're saying is just such horseshit, potentially dangerous horseshit
Speaker 5: that what you need to say is if you say
Speaker 5: that again, I'm going to pile driver you right like,
Speaker 5: I'm gonna give you a fucking stone cold stunner if
Speaker 5: you keep doing that shit.
Speaker 4: And I do appreciate that tone.
Speaker 2: Yeah, And you know it's we talked about that bulldozing.
Speaker 2: A lot of it is just the fact that you
Speaker 2: know they're basically just committing a low level psychological violence
Speaker 2: on a societal level.
Speaker 3: Right.
Speaker 2: They may get you into an office and then they
Speaker 2: will talk at you for like a hundred hours, like
Speaker 2: they will not drop the point. They will just talk
Speaker 2: about AI twenty four to seven. And if you're a
Speaker 2: little bit pessimistic of question your credentials, say you're not
Speaker 2: forward looking, blah blah blah blah blah, no idea, and
Speaker 2: they'll just do this until you go, I just need
Speaker 2: to paycheck, all right, invest in whatever you want.
Speaker 3: I give up, just do it.
Speaker 1: Just do it. And this is a common is this
Speaker 1: like a what kind of person does this?
Speaker 2: Is this?
Speaker 1: Like I see is this an executive level person, the
Speaker 1: product manager, what's the art or like a consultant.
Speaker 2: I think it happens at like in every position. I've
Speaker 2: seen programmers do that. I've seen artists do that. I've
Speaker 2: seen executives do that. I have I can't respond to
Speaker 2: my emails anymore because so many people have written in
Speaker 2: with stories that I can't navigate that inbox, right, And Yeah, I.
Speaker 3: Just see it everywhere I go.
Speaker 2: And then occasionally I see like these really small functional
Speaker 2: places where they don't have these issues stops usually anywhere
Speaker 2: between like five to one hundred people, and it's really
Speaker 2: hard to get in there because they don't scale up
Speaker 2: because they.
Speaker 1: Really don't help to hire more people.
Speaker 3: Yeah.
Speaker 2: Yeah, they get to one hundred and they're like, well,
Speaker 2: we're all really well paid and happy, and the more
Speaker 2: people we add, the higher the odds are we just
Speaker 2: get someone like that.
Speaker 3: So we're just going to stop hiring.
Speaker 1: In my experience, people like that, And I'll run a
Speaker 1: tech p off from my day job, and I do
Speaker 1: occasionally run into people at this, and I've learned that
Speaker 1: there's just a really easy way of saying it is
Speaker 1: I'm not done talking, like they really hate that. When
Speaker 1: I run into this kind of sociopathogic, you say I'm
Speaker 1: not done talking, and they get really mad because they're like, wait,
Speaker 1: I can't just attack. I've told peg to fuck off.
Speaker 3: I don't care.
Speaker 1: The thing is, these people, perhaps they only need to
Speaker 1: be pile drive, but they need to be yelled at.
Speaker 1: Samultman can't apparently walk around San Francisco anymore. And I
Speaker 1: think he'd want you to believe it's because he's famous,
Speaker 1: but I like to believe it's because people fucking scream
Speaker 1: at him. I hope that that happens.
Speaker 3: I'd probably do.
Speaker 4: I'll tell you if I run into him today.
Speaker 1: Yeah, please do give him my number.
Speaker 2: I should probably clarify I don't know that much about
Speaker 2: Sam Altman, so I don't want to. I'm gonna I'm
Speaker 2: going to read about him, and then I'll kick you
Speaker 2: an email to see if I feel better or not
Speaker 2: about slamming. It's great, it's cool, dude, He's a real
Speaker 2: he's a real charm. It's got your best interest at heart.
Speaker 2: You should listen to them.
Speaker 1: But always has so okay, I think good question to
Speaker 1: wrap up on is assume you are God really easy
Speaker 1: one here? Yeah, yeah, how would you actually fix the
Speaker 1: current culture in tech? You've kind of hinted at it.
Speaker 1: It's like organizational stuff. What would you see done with
Speaker 1: like a Google or a fake like what the bigger companies?
Speaker 1: What is the problem then?
Speaker 2: Yeah, So I think it's some inherent issue to do
Speaker 2: with scale, because fundamentally we're talking about the fact that
Speaker 2: there's a class of person who will either believe people
Speaker 2: in day to day interactions or they find ways to
Speaker 2: attach themselves to people who are very very credulous or
Speaker 2: don't have the technical skill to push back on what
Speaker 2: they're saying. I suspect that's a lot of why journalists
Speaker 2: don't push back on, you know, people saying insane things,
Speaker 2: because there's of course a fear in the back of
Speaker 2: your mind that they're going to come out with like, yeah,
Speaker 2: but you're not a technician. That was a stupid question.
Speaker 2: You've just been embarrassed on your own show, right, Like,
Speaker 2: that's that's very, very possible. I think a lot of
Speaker 2: those issues are so systemic that I view it from
Speaker 2: like a small scale disruption standpoint. So I started Hermetech
Speaker 2: with just a couple of my friends. Right, They're just
Speaker 2: guys I met who behave very honestly in the space.
Speaker 2: Some of them are AI guys, but they just do
Speaker 2: like actual serious work that gets published in places. Yeah,
Speaker 2: and we're just taking all the business from places that
Speaker 2: actually need results. Right, So most of the people rolling
Speaker 2: out Opening Eye stuff are not interested in working with
Speaker 2: us because they're just doing some weird Ponzi scheme where
Speaker 2: they convert the investor money into status and they use
Speaker 2: the status to.
Speaker 3: Get a higher paying job.
Speaker 2: Like, they don't need us because they don't actually need results,
Speaker 2: They just need to grift. I'm just going to let
Speaker 2: that market explode. That's not my problem. I think it
Speaker 2: would be dangerous to do anything to it. It's just
Speaker 2: going to blow up on its own. I'm just going
Speaker 2: to hang out in the corner with some sane people
Speaker 2: and just find people who actually need stuff to work.
Speaker 7: Right.
Speaker 2: I'm going to go in and just make sure all
Speaker 2: the database backups get tested, and then I feel like
Speaker 2: that's going to be a bajillion dollar industry.
Speaker 3: Right, Like for the rest makes things work, Yeah, just
Speaker 3: make things work.
Speaker 2: That's how people have made money for like the history
Speaker 2: of time. Just don't be insane about it.
Speaker 1: Nick, thank you so much for joining us. Where can
Speaker 1: people find you?
Speaker 4: Yeah?
Speaker 3: Thank you?
Speaker 2: Yep, so I bought a lunic dot blog so they
Speaker 2: can find my personal website, and there is hermitdash tech
Speaker 2: dot com and that's where they can get us for consulting.
Speaker 3: If you need someone to not lie to you, that's
Speaker 3: that's us.
Speaker 1: And of course I would never like to you. My
Speaker 1: name's Ed Zititron. I run this podcast. You I need
Speaker 1: to hear from me. But of course Robert Evans joined
Speaker 1: us today as well. Where can they find you?
Speaker 3: Robert?
Speaker 4: Thank you? Thank you.
Speaker 1: Ed.
Speaker 5: You can find me occasionally on your show Better Offline
Speaker 5: and on my own show Behind the Bastards.
Speaker 1: So yeah, thank you for listening to Better Offline. The
Speaker 1: editor and composer of the Better Offline theme song is Matasowski.
Speaker 1: You can check out more of his music and audio
Speaker 1: projects at Matasowski dot com, M A.
Speaker 4: T T O S O W s ki dot com.
Speaker 1: You can email me at easy at Better Offline dot com,
Speaker 1: or visit Better Offline dot com to find more podcast
Speaker 1: links and of course my newsletter. I also really recommend
Speaker 1: you go to chat dot where's youreaed dot at to
Speaker 1: visit the discord and go.
Speaker 7: To our slash Better Offline to check out our reddit.
Speaker 7: Thank you so much for listening. Better Offline is a
Speaker 7: production of cool Zone Media. For more from cool Zone Media,
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Speaker 4: The Welsh Spanish School