Hannah Clayton-Langton: 0:03

Why does it matter if the person gets the code that they need at a price that they think is fair?

Hugh Williams: 0:07

You can vibe code up a demo to demonstrate any feature or product idea that you have. So turn up with something that works.

Hannah Clayton-Langton: 0:13

For someone who doesn't work in that industry, that stuff really shiny and sexy and appealing.

Hugh Williams: 0:20

world, and welcome to the Tech Overflow podcast. My name is Hugh Williams.

Hannah Clayton-Langton: 0:24

And I'm Hannah Clayton Langton, and we are the podcast that down technology for curious people.

Hugh Williams: 0:30

How do I do Hannah?

Hannah Clayton-Langton: 0:32

You did great. Uh that felt weird. Guys, we decided to do some A-B testing and mix up who does the intro. So if we get much more listens and engagement on this we'll make that a permanent swap.

Hugh Williams: 0:42

Or we'll try another experiment, one word each, or I I'm not easier.

Hannah Clayton-Langton: 0:46

And guys, this is a signal that I am now an official tech and I will be leading this episode as our resident technical

Hugh Williams: 0:53

Yeah. So our topic today, uh Hannah, is transistors, the of the transistor. So um tell us about transistors. When were they first invented?

Hannah Clayton-Langton: 1:00

Okay, correct. I've been outed pretty quickly. Okay, we will do an episode on transistors later on, let's say season seven. be by then. So, no, we're not talking about transistors today, guys. We are talking about big tech.

Hugh Williams: 1:15

Yeah. Obviously, I spent a lot of my career working in big tech. So I'm really uh excited, Hannah, to talk about all the the West Coast tech, maybe a little bit about Taiwan, and really give our smart listeners out there some insight how these companies operate.

Hannah Clayton-Langton: 1:27

Guys, my goal for this episode is to get you to spill as secrets as I can about Silicon Valley. So wish me luck in Endeavour. Um, I reckon we get straight into it because I really mine you for gossip. no episode about big tech would be complete without a to the Magnificent Seven. So those are the seven biggest tech companies in the US, listed, I guess, biggest tech companies in the US. And I'm sure you can do this, but I'm gonna ask you to name seven to kick us off.

Hugh Williams: 1:55

Yeah, so Apple, of course, uh, Microsoft, Amazon, which owns Google, amongst other things, also owns an episode on in season one. Uh Meta, which of course owns Facebook, Instagram, and NVIDIA, which make uh the GPUs that uh we've talked a lot in season one, and Tesla.

Hannah Clayton-Langton: 2:18

Ding ding ding, got them all right. So they make up, I think, about 30% of the SP 500, which is US's largest 500 publicly listed companies. There'll be a few on there that listeners will know that we mentioned just because they're not publicly listed. So like OpenAI, Anthropic, right? They're not.

Hugh Williams: 2:34

Yeah, SpaceX. I mean, there's there's quite a few large companies that, know, may publicly list in sometime in the near future. Uh, but they're the major ones that are publicly listed. And Magnificent Seven's a new moniker, if you like. It hasn't been around that long. We used to use the moniker Fang, which had two A's in I think is Facebook, Amazon, Apple, Netflix, and Google. They were the cool kids on the block probably five years but now we talk about the Magnificent Seven instead.

Hannah Clayton-Langton: 2:59

Interesting. So Netflix dropped out. And I'm surprised that you didn't mention Microsoft. I would have thought they would have been in there.

Hugh Williams: 3:04

They were a really big comeback, really, under under Satya leadership. And the Azure business is a very, very big business. They're cloud business. And we talked about cloud a little bit in season one, in our in our wrap episode. And also, you know, they've been major investors in AI. They're a large shareholder of open AI, famously. And so, you know, they've really made a comeback, and so part of the Magnificent Seven.

Hannah Clayton-Langton: 3:26

Interesting that you mentioned cloud because I did a of research on the revenue streams of the Magnificent Seven. And some of it's quite intuitive and some of it's a bit So yeah, Microsoft, a lot of the profit driven by cloud. Speaking of cloud, I was surprised to learn that I think it's something like 75 or 80% of Amazon's revenue is still coming their retail business, but their profit margin is mainly driven by AWS. So things like cloud, I assume, are a much better play than know, selling bits and bobs online to consumers, but then the retail business becomes the volume play.

Hugh Williams: 3:58

Yeah, yeah, exactly. I mean, low margin, high volume business, the retail And then because of the scale of AWS and the ability that, know, you can really get scale from that infrastructure, the margins are much, much, much higher. And they really are the company that largely sits under most other companies that you're using on on your smartphone on the web.

Hannah Clayton-Langton: 4:18

And Google have got a cloud business, but they're, I think like 90% of the revenue comes from ads, which I think we're to talk a little bit more about Google in an upcoming episode, but that's not a huge surprise given the power that sits their data collection.

Hugh Williams: 4:31

One of the best business models, Hannah, of all time is the Google Ads business.

Hannah Clayton-Langton: 4:35

Well, we actually should do a whole episode on that.

Hugh Williams: 4:38

We will.

Hannah Clayton-Langton: 4:38

And then I was interested to learn that Tesla actually make 10 to 15% of their revenue on like environmental credits, which I assume is just sort of a way for less environmentally companies to offset some of their emissions, like the sort of old school car production companies or something like that.

Hugh Williams: 4:54

Yeah, yeah, I think that's the case. And look, historically, Tesla certainly benefited a lot from you know government credits, government programs, kinds of things. So it's a you know it's a complex company. Obviously, it's building in its end product something that's incredibly environmentally friendly, an that can be used to power all kinds of things. Long conversation about whether the actual production of the car and the batteries is environmentally friendly. I think that's a that's a separate conversation, but certainly they've benefited a lot from you know regulatory and and support. Obviously, a lot of that's been wound back by the Trump

Hannah Clayton-Langton: 5:25

Uh, we won't get into politics overflow on this podcast. Find us in the pub for that conversation. Microsoft's an interesting one because I don't know how widely known their investment in open AI is sort of outside of the world. And also, I mean, less sexy than ChatGPT, but um, they own which I only learned when I was prepping for this episode.

Hugh Williams: 5:43

Yeah, yeah. Looking, you know, they own I think 49% of OpenAI. And yeah, I think they've owned LinkedIn since probably around 2016, Hannah.

Hannah Clayton-Langton: 5:52

That is correct. And they bought it. Can you guess how much for?

Hugh Williams: 5:55

Oh, look, my mind's saying 9 billion, but I bet it's a bit more than that.

Hannah Clayton-Langton: 6:00

It was $26 billion, which I I mean anyway. Off by an order of magnitude, that's me. Well, I would have guessed much lower. Um, anyway, so yeah, so some interesting sort of makeup of revenue of those companies. You can certainly, you know, dig a bit deeper. We won't get into that any further for now. And then, of course, the Magnificent 7, those are all by US-based. We do see a huge amount of big tech innovation come from the coast of the US, and we can talk about why that is maybe a bit later on. But maybe a nod to Taiwan for the semiconductor production. So TSMC, I believe that company's called. And then we've got Byte Dance who own TikTok and are based in China. More on them later. And I think it'd probably fair to call out Samsung in Korea. Do you think we've missed any?

Hugh Williams: 6:43

Yeah, we've probably missed quite a few. I mean, there's a lot of large Chinese companies, Ali Baba, Tencent, you know, there's a long, long list. We should do an episode on Chinese tech. And then, you know, there's there's companies that large as those that are based outside the US that are pretty famous. So, you know, an example might be uh Spotify. Yeah.

Hannah Clayton-Langton: 6:59

Yeah, that's it. I had didn't realise for a long time that they were Swedish. I think that's super cool.

Hugh Williams: 7:03

But on TSMC, I mean, they are the company that really produces the silicon for most of the Magnificent Seven. So, you know, the supply chain from Taiwan is very, very to US tech. And again, that's probably a topic we could dig into season.

Hannah Clayton-Langton: 7:16

Yeah, definitely. The the geopolitics of it suddenly become quite scary. Um, but that's not what we're gonna focus on today. I want to take us back to the west coast of the US because where Hugh you spent a lot of your career. But like, why do you think we got these hubs of huge tech coming out of it? It's Seattle as well as California. I was gonna say maybe it was the weather, but I think the in Seattle's a bit crap. But um, yeah, like why do you think those hubs ended up there? Is it just because it's where Bill Gates was from?

Hugh Williams: 7:42

You know, the Microsoft story is really the Seattle story, it's probably not super well known. You can read about it in um Bill Gates' latest book, which is called Source Code. You know, Microsoft's early years were really in New Mexico, and then Bill and Paul Allen decided to actually move the headquarters back to Seattle, which is where they both were from. So it was almost an Albuquerque, New Mexico business for a while there it became the center of tech in the US.

Hannah Clayton-Langton: 8:09

Well, uh Amazon is Seattle too, is that right?

Hugh Williams: 8:12

Yeah, that's right. That's right. And and you know, I think it's a beneficiary of the fact that Microsoft was there and really turned Seattle into a into a tech destination.

Hannah Clayton-Langton: 8:19

Because once you get a critical mass of good engineers, I is mostly what are in demand, then you want to co-locate can try and steal that good talent, right?

Hugh Williams: 8:28

Yeah, absolutely. And you know, if you work in any of these companies, you'll find that there's a significant number of people who've there for their whole life, but most of the other people come from one of these other large tech companies. So there's lots of people at Google who are from Microsoft, lots of people at Microsoft who are from Google, know, that these folks just move around.

Hannah Clayton-Langton: 8:44

Okay, so Seattle, that sort of makes sense. And then we travel down the coast to California. Why do you think that built up?

Hugh Williams: 8:51

Yeah, we fly over Oregon and get to and get to California.

Hannah Clayton-Langton: 8:55

Funny that, not a huge hub of tech, globally, Oregon.

Hugh Williams: 8:58

Yeah. And if you've ever lived in California or have been to you know that it's really two states. So they call it Northern California or NORCAL and Southern or SoCal. And you know, they're really different places. Um, arguably it could be two states, you kind of rule a line across the middle. And LA is perhaps famous for the film industry and all those kinds of things, the music industry. It's a very, very different culture to the culture you find in the Bay Area, which is the area just below San which is, you know, famously known, I suppose, outside Bay Area as the Silicon Valley. So you'll find the people inside the so-called Silicon Valley just call it the Bay Area, and uh the rest of the world it the Silicon Valley. But I think the history really is that we had Stanford obviously one of the you know, world-class university. It's always been very, very good at computer science, and it's always produced top shelf graduates. Larry and and Sergei, who founded Google, are, you know, folks. So lots of lots of famous people have come out of Stanford and gone on to found companies, but it's historically very strong school for computer science. Uh, defense was also based sort of in that region. So there's lots of defense industry there. Climate's great. Back in the day, there was plenty of land, lots of fruit And so, you know, you put together the universities with the defense investment, with a wonderful climate, plenty of land. And the end result is it became really the center of tech in the world.

Hannah Clayton-Langton: 10:17

Okay, so it literally comes down to accessibility of smart I know from having worked with robotics through my current job that there's like a big hub around Boston for similar reasons. You've got like Harvard and Tufts and Boston College and some of the really good unis. So it sort of makes sense that that's where the employers to. And what years were you in? You were like early Silicon Valley, right? Is that fair?

Hugh Williams: 10:39

No, no, no, no, not fair at all. No, no, Silicon, no, I'm not fairly. Maybe we can take that out.

Hannah Clayton-Langton: 10:43

We'll let's go.

Hugh Williams: 10:44

No, I'm definitely the uh senior member of the team here, but I'm not quite that senior.

Hannah Clayton-Langton: 10:48

Okay, so what years were you in Silicon Valley, aka the Bay

Hugh Williams: 10:52

Yeah, so um we moved to the Bay Area in 2009, and I was until 2017. So just a small part of the history of uh of the so-called Valley.

Hannah Clayton-Langton: 11:04

But that was a really big so maybe just since you've mentioned timelines, just to place sort of what was going on in the of tech, because I I found this quite interesting as it came of my research. if we think about the history of what tech meant, right? Because back in the day, so in the 1980s, let's say it was all about personal computing, the internet wasn't really a thing or not something that the everyday person was using. And then the 90s was all about the internet boom. I I literally remember the first time we crowded around my desk, um, actually also in the US, and dialed up to the with that very distinctive sound. If you know, you know. 2000 to 2010 was all about social media. And then we moved into apps and the app economy and app for And now when we talk about tech, we're really talking about cloud, generative AI, platform tech. So through that time period, tech as an industry meant things depending on what was going on. So you were there during the sort of social media, mobile, app economy phase of things.

Hugh Williams: 11:59

Yeah, that's it. And probably the birth of cloud computing, really, as it something that became commoditized and available to other around the world. And we've spoken a little bit about it in earlier episodes, Hannah, where we've talked about sort of how Microsoft its own cloud for its own purposes, and in its case for Bing, and Google did the same for its Google search, and Amazon the same for its store. And then obviously they went on and sold those things to people, and that's really now what powers the internet. But certainly I was there for the the mobile revolution, maybe some part of the web revolution and definitely the cloud

Hannah Clayton-Langton: 12:29

And does that change the type of people like computer that you need? Do you need different skills or is it all covered in a science degree?

Hugh Williams: 12:38

Yeah, really good question, Hannah. I mean, if you zoom out a lot, right, I think at the beginning of computing, it was all about hardware. And you know, software was a small part. You know, certainly over time, what's happened is hardware's become, you know, it's still interesting, but the the real has gone into software. And look, I think a good computer science degree gives you problem solving skills that you can use to adapt to any new technology. So that's one of the wonderful things about doing is you learn how to be a problem solver. Um, you learn how to decompose a problem down into and solve those problems. You know, we talked a little bit about that way back in first episode of season one. And so, you know, at least on paper, I guess uh somebody a computer science degree ought to be able to adapt to changes in technology. But I say on a more practical level, the kinds of skills are valuable has has changed quite a lot. I mean, there was certainly a phase when maybe we'll back to the start of the web where being a web developer, could build web pages and make those interactive was kind of the the hot skill. And then being an app developer became a very valuable You know, if you could write iPhone apps or Android apps, was a valuable skill. Again, that's a little bit more commoditized now, with things like Claude Code, where you can generate large of code. And these are often very simple apps to build. Then we sort of went through a phase of where the sort of infrastructure people who could stitch together AWS and Azure and Google's cloud to really build scalable systems were valuable. Those folks are still quite valuable. But what I think what we've really seen over the last few is the emergence of the data scientists. So these are people who can use data to create products, and they're often people who are very skilled at machine learning and AI. And obviously that is the uh topic de jour, if you like, of uh of computer science at the moment.

Hannah Clayton-Langton: 14:16

Yeah, I wonder how that will develop. If you think about it, like if someone works for 40, 45 years in their career, that's spanning a lot of different eras tech. And so I guess you either have to be, you know, super to the thing that you do, even if it becomes out of fashion sort of the main, or you have to be pretty agile, right? And like, would people retrain?

Hugh Williams: 14:35

Yeah, absolutely. I mean, the programming languages that I learned at are largely not used anymore. So certainly, you know, through my career, I've had to adapt to different programming languages, different ways of software, um, you know, pretty much everything's changed. But again, if you've if you've got those fundamental science characteristics, you should ought to be able to, you know, adapt to change over time. And that's what I always say to people when we're hiring, we should be hiring for fundamental sort of competencies, if like. Is a person a good problem solver? Are they smart? Are they driven? They got a computer science degree, not hiring for who has a specific skill because you know, skills come and go very, very quickly in uh in the tech industry.

Hannah Clayton-Langton: 15:10

these highly skilled problem solvers that you're drawing top universities on the west coast of the US, they're paid a lot of money, right? Like if you're working in tech, if you're an engineer, there's sort of two paths you can go down. Maybe this is my outside interview, and you can go for like lifestyle, work remotely from a beach, get paid pretty good considering that you're sort of in control and have the or you can go after like a cold, hard cash and land a job in Silicon Valley and make a lot of money.

Hugh Williams: 15:35

Yeah, that's it. I mean, I think there's lots of things you can do in tech, certainly if you want to be amongst the best of the best and be paid the largest amount possible, then you know, the Silicon Valley is the is the way to go.

Hannah Clayton-Langton: 15:45

And it's not just like monetary compensation, like Netflix have unlimited holiday. And I know that Google um support female employees freezing eggs, which is actually a really awesome benefit that I have a couple of friends that have taken them up on it. Free food. I remember I once worked at YouTube early on in my career. I wasn't working for YouTube, but we did an event with and it was like going into the Google offices and seeing that they do actually have the nap pods and the massage room and free food that you can just take from the canteen. Like for someone who doesn't work in that industry, that was like really shiny and sexy and appealing.

Hugh Williams: 16:19

Yeah, and look at all of it's true. Certainly when I worked at Google, I worked at the Mountain View campus, so the main campus of Google. I think it probably had around 50 different restaurants. Wow. Um, not all of them open for all meals, but you know, they breakfast, lunch, and dinner. Pretty much select any cuisine you want any time of the So I used to hit the gym. They they probably had, I don't know, more than 25 gyms. They'd sort of done a faux athletics track with the grass and things. They had big tractor tires there that you could flip that you could hit things with, put out sort of the cones and have running drills, you know, a bit sort of boot camp kind of style. I used to enjoy that. And when I finished the class, go and have a shower and uh the free towels, of course, uh that come with the uh the And then I'd head over to one of the smoothie stations and uh get them to make me up a really, really good protein smoothie with all the additives that that I wanted. Usually for lunch, you know, I'd pick one of the healthier quite like one of the Japanese restaurants they had, used go there. And then I didn't usually stick around for dinner, I'd jump on my bike and pedal home. But certainly, you know, the culture is designed to get you in there early so you get a free breakfast, feed you at and then get you to stay late, have dinner, stick around, do a little bit more work. So, you know, the culture is designed to get you to work hard by providing you with the uh the perks to help you do that.

Hannah Clayton-Langton: 17:34

Okay, I would be such a sucker to that culture. Like, if you give me a good gym on, I'll be there on the Like that is very smart. I'll take us for a minute a little bit further away But my brother worked for bite dance in China for a while. Oh, wow. And um I asked him for some of the sort of insights into how it was working there because they worked him pretty hard. I think he was there for two or three years. And he said similar things. So it was like core working hours were 10 till seven, I think. But free breakfast was from nine and free dinner was from seven.

Hugh Williams: 18:04

So it's like nine nine six is they call it him.

Hannah Clayton-Langton: 18:06

Yes, yes, that's it. Sorry, I should have opened with that. Beijing tech is the nine nine six, so you work nine till nine six days a week. Yeah, yeah. Um, actually, sorry, just on the six days a week thing. He said that when he moved to work at Byte Dance, they were changing from working six day weeks every week to working a week and then a five-day week the following week. And they did something really cheeky where they were like, we were actually paid double for Saturday, so you're gonna you know, more than one-sixth of your pay cut on the you are only doing five days. And he said that some people really didn't like that just actually wanted to work super hard. He said there was a ton of young people who worked there until they burnt out. And then he said they got subsidized rent, but only as long as it was within 20 minutes of the office or something. So he didn't go for that one. He actually said that it inflated the rents in the local area and so it wasn't really worth it. But it was that whole design of like, it sounds really someone like me who wants a convenient gym will be like bought in. But it's basically designed to keep you on site and working for as much of the day as possible, right?

Hugh Williams: 19:06

Yeah, absolutely. And going back to the Google story, I mean, they had much had every service you could possibly think of, and were free. So they had like a bike repair store. You could, you could, you know, if you had an issue with your bike, you could take your bike there and they'd repair it for you while you're at work, laundry, all these kinds of things. Dry cleaning? Uh yeah, yeah, certainly dry cleaning. Um, I can't remember whether it was free or not, but they had, you know, dry cleaning where they'd come and pick it up and drop it back. Um, and you know, probably subsidised at the very, But certainly, you know, every service you needed to live your life was available on the campus again to get to stay on the campus. The only thing they didn't have was beds. So you couldn't actually sleep overnight there.

Hannah Clayton-Langton: 19:41

Okay. And did they have like child care and or pet care? Like sometimes you see that like doggy day care is uh in London, like dog-friendly offices is a big pull for certain people.

Hugh Williams: 19:50

Yeah, so certainly, you know, all of those things are of. So if you sort of zoom out a little bit and think about of the broader benefits package for somebody working at I mean, certainly they want you and your family to be So the health benefits are fantastic, you know, and a lot things like, you know, looking after your pet, childcare, kinds of things are all pretty heavily supported. And obviously, because it's one of the most wealthy places the world, there's an enormous number of workers who come that area to provide those kinds of services. So it's definitely the center of the universe when it comes to sort of being looked after, both within the company and you know, broadly as a family that lives there.

Hannah Clayton-Langton: 20:24

you get the same perks if you're like a receptionist or like a finance manager? Do you get the same perks as the engineers?

Hugh Williams: 20:30

Yes and no. I think um there's different colored badges. And so you know, the employees get a get a badge that's colour and the contractors get a badge that's a and you you get virtually no perks if you are a contractor. And you would find, for example, that pretty much all the are going to be contractors, contracted through a And so they're wonderful people, they work hard, you know, share the ethos, but they don't get any of the benefits really that the employees get.

Hannah Clayton-Langton: 20:55

I had heard that Google, because Google got big offices in that they mainly hire people at least to start on And I had understood that that was because it's easier to sort of end the relationship with the employee if it's not gone and then they can just make you permanent if it does. But I hadn't considered that's probably also a benefits

Hugh Williams: 21:12

Yeah, look, it probably is. And and look, you know, California has um what we call deployment. And that basically means that they can get rid of you or you can quit and you can do that fairly quickly. Obviously, places like the UK and Australia, it's a lot difficult to get rid of employees. Uh, and you know, sometimes, particularly in the UK, an employee to leave. So, you know, some of the senior executives in UK tech have to give crazy notice periods that, you know, like 12 right? Yeah, just completely blow my mind. Where, you know, the I think the longest I've probably ever seen in the US West Coast is probably three weeks.

Hannah Clayton-Langton: 21:43

Oh, wow. Okay. Wow. Even UK, the shortest you'll get is one month. And back to these different colored badges because I'm kind of shook by this. Okay, so does that create like a two tier Diddy engineers who I presume are the people on the permanent contracts, like, does that make them sort of like first class? Citizens and then the other ones like maybe less so.

Hugh Williams: 22:03

Yeah, I think uncomfortably so. I think uncomfortably so.

Hannah Clayton-Langton: 22:06

Okay, so we've kind of got a two-tier system. And so would your like in-house lawyers be contractors or they be full-time?

Hugh Williams: 22:12

No, they'd be they'd be full-time. They though things like patent lawyers, you know, the folks who um who write up the patent applications and things would be external legal firms. So when it comes to sort of some of the specialist legal you know, they use these well-known external firms, but all the professional staff who are paid well are

Hannah Clayton-Langton: 22:31

Okay. And it's obviously paired with like caning the working hours, right? Like I imagine if you are a very highly paid engineer at one of the big tech firms, the expectations on you are pretty high. And what you've said about our well employment means that that can all be ended pretty quickly by an employer if they don't like they're getting the value from you.

Hugh Williams: 22:48

Yeah, these are these are performance cultures for sure. Um, and I think most of these companies are by any measure class at setting, you know, KPIs or performance of the people that work there. They by and large have pretty strong review cultures. So, you know, you sit down and you talk about your They have very strong bonus cultures where they'll pay or not pay bonuses based on people's performance. And so certainly these are cultures where, you know, people are encouraged to work hard towards very specific goals. And, you know, if you don't hit those goals, it might not you bonus. And uh, you know, probably not far behind that is you be shown the door.

Hannah Clayton-Langton: 23:24

Okay, and talking about bonuses, like what percent of base would they then be striving for as their bonus?

Hugh Williams: 23:31

Yeah, so look at it depends on level. If you're a recent graduate and you you join these you know, your bonus target might be anything from say to 10 or 0 to 20% of your of your base salary, which, you sounds pretty good to most people. Once you get up into the senior executive ranks, you know, probably in the range of zero to a hundred percent, maybe to two hundred percent of your base salary. And so, you know, you start to think of the bonus as the part of your cash compensation, though a very of your cash compensation because it doesn't just depend on your personal performance, but it also depends on performance. And obviously, you're somebody who might have some on that, but you don't completely control that.

Hannah Clayton-Langton: 24:08

Okay, but that kind of makes sense at an executive level the bonus targets would be that high, right? And that's not specific to tech necessarily. But what about like a senior engineer? Like they need to be invested in what they're building, way that we do that is by giving them shares. That's another part of comp we've not really mentioned shares or bonus. Like it do you find that that that mid-range gets pretty well looked after in that sense as well to get them bought into what they're doing?

Hugh Williams: 24:33

Yeah, absolutely. And you know, salaries go up very, very quickly in in US tech from uh junior salaries where, you know, you're an engineer and you're perhaps starting your first role at a place a TikTok, you might be getting a base salary of, say, US, which sounds good by any international standards. And then once you're in the door, if you're somebody who hits those targets, keeps getting bonuses, I mean, you could certainly over a period of years be, you know, getting paid up around a million dollars to be an individual you know, somebody who's sitting there writing software every day.

Hannah Clayton-Langton: 25:04

Yeah, guys, I picked the wrong career path. Well, who knows where podcasting will take me, but feel I went to an all-girls school and it would we were sort of pushed if you were into science that you'd do medicine. And if not, don't bother with science. And there was a big gap when it came to things like computer engineering, maybe it would have been called. And I think my school missed a trick.

Hugh Williams: 25:22

Yeah, I think most schools miss a trick, Hannah. I mean, we should talk about our charity code for schools some point and what we're trying to do here in Australia to change that trajectory, particularly for girls. But uh, yeah, lots of schools don't understand how tech is and uh how much you know one engineer can change the world. I mean, you really can work on a product that affects of people, and and there's really very few industries that's the case. And so, you know, it's a it's a pretty interesting career to get into, and because of that, leverage that impact, you can you can make lots of money for yourself too.

Hannah Clayton-Langton: 25:50

Well, think about Jonathan Medine, right? We had him in episode five-ish of season one, and he just one night coding, invented the swipe right, and that's changed the face of modern dating. So it's definitely not an over-exaggeration to talk about that impact. And I have many a time considered retraining. Think about it all the time this episode too. Giving me some more pause for thought on that as well. And I think just while we're on the topic of the sort of split, which we we don't need to get into in too much detail. But one thing I have heard is that the female engineers that do exist, because they're sort of famously, um, it's more of a male skewed industry, but they can demand some pretty big salaries because the big companies have quotas or they want more female engineering presence. And so if you're a strong female engineer, you can sort of go in and demand your price and they'll be really fighting for

Hugh Williams: 26:36

You know, certainly all the organizations that I've worked and this concludes in recent times, they're probably at 90% male and you know, maybe around 10% female, and that's know, clearly that's not representative of, you know, how the world is. And so I think more diversity would be fabulous in tech, certainly uh, you know, you have to encourage women to get tech, and then uh those women who get into tech and who are great at tech, you know, everybody wants them quite

Hannah Clayton-Langton: 26:59

Yeah, fair enough. Okay, girl power. So back to shares. Does that not dilute the shareholding of a company if they're just giving loads of free shares out to all their employees, is it not quite as simple as that?

Hugh Williams: 27:12

It does create dilution in the in the shares, but probably to a significant extent unless you're really talking about who are getting, you know, big parts of of the company. But it's a very, very important part of the compensation anybody in the US. And there's really three components to the comp in West Coast Tech, Hannah. And, you know, even young engineers are pretty savvy about So, you know, first of all, there's your base salary. That's the cash you get every bi-weekly, as they'd say, in US. The bonus. We talked a little bit about that. Young engineers will be interested in what's the target and what do I have to do to get it? Do you ever pay more than the target bonus? Those kinds of things. And then there's the RSUs, the restricted stock units, if you like, of the company. And most engineers will build a little spreadsheet and say, good, better, best. They'll put in some possible stock prices, share prices might be reached. They'll build out the vesting schedule of those shares and figure out how much they could be potentially worth. And that's certainly a really big factor in the process of engineers is you know, do they believe in the prospects of the company and will they make a lot of money of their shares?

Hannah Clayton-Langton: 28:11

And and RSUs, or at least my experience with them, was that vest over a certain number of years. So it's like, oh, great, we've given you this huge slug of but you've got to stay here four more years to get them all.

Hugh Williams: 28:21

Yeah, absolutely. It's a little bit more complex than that, too. So let's take a fictional example. So imagine you uh you join a company and they give you RSUs as a as an award when you join. So they say, here you go, you can have 10,000 shares. What'll typically happen is that they'll vest out over a period. There's often sort of a cliff before you get the first part. So it might be say, hey, you have to be here six months you're gonna get any, and then you'll get six months' worth. And then maybe they'll vest every month after that until reach the four years and you've got all 10,000. But then what'll happen every year usually in these companies is they'll give you another share award. So they'll say, Hey, Hannah, you've been fantastic. We're gonna give you 14,000 shares this year. And again, they'll vest out over four years. And so now you've got two lots of vesting going on. You've got the awards you got on the first day you joined, and then you've got some award that you got on the 365th day, anniversary of a joining. And then guess what happens next year? We'll give you another pile. And so you've got all these things vesting on different different numbers of shares.

Hannah Clayton-Langton: 29:22

Different share price, like share price fluctuations, right? Because if there was a you always want shares on a down year if you believe in the company, because that's where you're going to make most of your money.

Hugh Williams: 29:31

Absolutely. So, yeah, often what they'll do is, as you say, is well, we want to give Hannah a a certain dollar value of shares. And so they'll divide that by the current share price to the whether it's 10,000 shares or 12,000 shares. And so you're factoring in, you know, the future prospects the company, the number of shares you might get, but you've got this very complex equation going on in your head. You know, they call it the golden handcuffs, because you leave, you lose all of those shares that are yet to

Hannah Clayton-Langton: 29:56

And arguably the best share play is to go for like a super early phase startup that you just believe in, right? Like I had a an old colleague once who he, that was his thing. Like we were on a grad scheme together, and then he was My next move, I'm gonna go early phase, be the single digit number, and then I'm gonna make a ton of money once that goes big. But basically, if you're really good at spotting, you know, next unicorn, that could, you know, make you could make your by the time you're 30. But I imagine that there's more people who don't than do who that approach.

Hugh Williams: 30:25

Absolutely. And different, you know, it's just about different levels of risk appetite, right? So there's certain people who are happy to go for that hero or zero company where, you know, it's either gonna be worth nothing at all, or maybe you'll make a fortune. And there's a certain set of people, and I probably fall into that category of who are happy to work for big tech. You get a generous base salary, you get a predictable bonus, you get some RSUs or stock units that you know are going be worth, you know, roughly in this kind of range, something special happened. And something special has happened over these last few years as share prices of the Magnificent 7 have run up

Hannah Clayton-Langton: 30:56

All of this must amount to quite a distinct culture in Silicon Valley, and I'm sure in other sort of tech hubs that exist in the world. But like it sounds like these people might be a little bit, don't know, like maybe arrogant, which isn't a word I would associate with like engineering, you know, sort of but it's kind of crazy that they would be making all this money and be in this bubble where it's normal to get all this sort of compensation and it's quite distinct from the real world that most of us live in.

Hugh Williams: 31:26

Yeah, yeah, yeah. And I recommend the the TV show Silicon Valley if you kind want to see a caricature version of this. It's uh it's pretty funny. But yeah, certainly, I mean, you know, when I was a kid, I just kind of some nerdy geek. And then when you move to Silicon Valley, you know, you're of a population of people like you, and you know, you feel a little bit like a rock star given the money that you're paid and where you live and all the things that you can do that kind of money.

Hannah Clayton-Langton: 31:49

Okay, so this episode is now sounding like a pretty strong for people becoming software engineers. about the disruption of something like Claude Code? Like suddenly you've got a much cheaper way of generating that output. Even if you don't remove all of the engineers, you remove 50% of them, 70% of them, then it's much cheaper to use that. And then your big ticket salaries and compensation and packages might just disappear.

Hugh Williams: 32:13

Look, I think that's partly true and partly not true. And I think it's a little bit unclear exactly where this is all headed. But if we if we wound the clock back, say six months, I had the very strong view that you know, things like clawed code were kind of generating, you know, code that could be used in prototypes to demonstrate a concept, but it really wasn't beyond that. So everybody's quote unquote vibe coding up these apps saying, hey, software engineering isn't too hard. And I'm like, try getting that running at scale where you have 99,000 queries a second.

Hannah Clayton-Langton: 32:42

Okay. And then six months ago, you you're thinking, eh, like good prototyping. Yeah.

Hugh Williams: 32:47

And good for prototyping in a super cool way. Like we spoke about product management back in season think it was our second episode. I think even six months ago, you know, my advice to young managers is don't turn up with slides, don't turn up with don't turn up with PowerPoints, turn up with a demo. Like you can, even if you're not a really proficient you can vibe code up a demo to demonstrate any feature or product idea that you have. So turn up with something that works.

Hannah Clayton-Langton: 33:11

I love that. That's really cool.

Hugh Williams: 33:12

Yeah, yeah. And I think we should expect that of product managers It's like go build it. If you think it's real, build it and show me the demo. There's even a course now uh at CMU, Carnegie Mellon called Vibe Founding.

Hannah Clayton-Langton: 33:23

What and what does that mean?

Hugh Williams: 33:24

So the idea is, you know, you have a startup idea, and within a week or two of running in this class, you actually come out with a product that's actually launched and running and a business model.

Hannah Clayton-Langton: 33:33

I love that. That sounds way more interesting than the medieval French that I studied in university. That sounds great. And so I think you're building to telling me that since ago, your attitude changed on that, right? Like I heard in the round that one of the latest Claude models has really changed the game in terms of the quality of the that the LLMs are giving.

Hugh Williams: 33:52

Yeah, it's changed so much and in a way that I just did predict. So I'm starting to think, Hannah, that coding by hand may be a thing of the past. We may not need to do that anymore. That's big. Yeah, and certainly I'm struggling to find cases where like clawed code can't do the work. I even heard from a friend the other day, maybe this is down the down the mill, but that Microsoft is now mandated every software engineer needs to use clawed code who works Microsoft.

Hannah Clayton-Langton: 34:21

Well, I mean, if it's that good and it enhances productivity, that makes sense. But then is this sort of darker undertone as that means you fewer engineers, right?

Hugh Williams: 34:30

Yeah, well, the question is what's software engineering, And I think I like analogies. We use a lot of those throughout the show. But what I would say is it's a little bit like power tools the carpenter. The average carpenter's got a nail gun, you know, they've an electric saw, these kinds of things. They plug batteries into things, things are just a lot faster and a lot easier, and they can do a more professional job. And I would say things like Claude Code are a little bit power tools for the carpenter. But I'd say that software engineering is even broader than It's more like building software.

Hannah Clayton-Langton: 34:56

Yes, we did. Yeah, we talked a little about this, like the architecture, plans.

Hugh Williams: 35:00

Yeah. So I think do you need software engineers? Absolutely, you do. But will they be coding as much? Probably not. And so then I guess the question becomes do we need as many software engineers given they spent so much time coding? So I think I think it's yet to play out. I think probably the answer is that the best software are going to be paid even more and uh going to be very, very valuable. But I think that band that's not so great today, I think know, could be in a little bit of trouble.

Hannah Clayton-Langton: 35:24

And doesn't what you described potentially blow the line product management and engineering even more?

Hugh Williams: 35:31

Yeah, absolutely. And I think if I was giving advice to a young person I'd say become a product manager who understands data science and vibe code like crazy.

Hannah Clayton-Langton: 35:39

Yeah. Before LLMs entered the scene, there was a lot of companies were like offshoring engineering capability to low-cost I think like India is the main one that I know of. I actually have a friend, actually, he's a listener who is a engineer and he works with a team in India and he has teams in the UK, and he says he gives directs different types of the teams because the Indian engineers have like less but they can just churn stuff out really quickly, which is helpful. But do you see that being disrupted by the LLMs?

Hugh Williams: 36:10

I think massively so. These folks who work, you know, in these remote geographies given really specific tasks really are mostly just coding.

Hannah Clayton-Langton: 36:17

Yeah.

Hugh Williams: 36:17

Right. So they're not really doing the whole software engineering They're just asked to fix this piece of code, write this whatever else it is. And that can pretty easily be done by tools like clawed today. I think that's dramatically going to change.

Hannah Clayton-Langton: 36:31

Yeah. Just to be clear, it's not because they can't do that software engineering piece. It's just that the way tech companies have set up their offshore arms is that they give very specific like to-do lists to people who aren't as embedded in the product. And so, yeah, it sounds like that's that's the thing that end up pretty disrupted. Or in I mean, I guess you could say it's enhanced, right? You'll get a lot more productivity, but it just means that will be fewer jobs to generate the same amount of output.

Hugh Williams: 36:54

Yeah, or there's more companies created, more happening in and those people are deployed into those, into those new and new spaces.

Hannah Clayton-Langton: 37:03

So we'll we'll see. Tell you what though, you hear these stories where I think, I think I know some people, this has actually been true. People have more than one job. So if you're in one of these sort of remote engineering there's like a good history of it's probably not just but it's probably an easy one to sort of fake that they'll more than one job and they'll just be like pretty and sort of be able to fudge doing two different jobs at time. And uh yeah, I guess once you have this enhanced productivity expectation, it might be harder to fudge that through.

Hugh Williams: 37:32

Yeah, absolutely. And I'm I'm sure there's already people uh lying in hammocks across the world with lots of agents running, doing all coding for them and sending bills to people.

Hannah Clayton-Langton: 37:40

Yeah, I mean, I think it's kind of fair enough if you can get away with it. Maybe that's a bit morally gray, but like at work, my line is kind of like if I can't tell that you've used Chat GPT or similar, then I actually don't really mind. It's just that when the output is it, what is it, the M-dash that you is a real give. Like if you can tell someone's use it, then they've not well enough. But if you can build code and bill people for it in a way you know, you're getting great return on your time in the I think that's fair enough until, you know, why does it matter if the person gets the code that they need at a price that they think is fair?

Hugh Williams: 38:09

Yeah, absolutely. And I think, look, LLMs are great for two things. You know, one is to sort of stimulate the thinking in the place before you actually do the thinking and then get on with the task. Or, you know, if you've done all the thinking, you've it through, and you just want to, you know, correct the write that as a paragraph, turn those bullets into a whatever it is, then, you know, power to you.

Hannah Clayton-Langton: 38:28

Yeah, power to you. Okay. And I feel like, is it fair to say that the cadence of change in Silicon Valley or big tech in general is just getting and quicker as we go because the world just moves faster

Hugh Williams: 38:40

Yeah, I think so. I mean, I think uh, you know, AI is super disruptive, LLMs super disruptive. And so there's certainly been unprecedented change in the few years after what I think was a period of lull. But if you look back far enough, you know, we had mobile, the smartphone, that was a pretty big revolution. We had the personal computer was a pretty big So cloud computing was arguably as big a revolution, though a little bit slower on the boil. But certainly we've always had periods of revolution by periods of stability, but we're certainly going through of those periods of revolution right now.

Hannah Clayton-Langton: 39:09

Interesting. So don't retrain as a software engineer just yet. Get into data science. Um, okay, so let's just take a big step back out to round this episode, which is why does big tech matter? you're not interested in being a part of this industry, then it just sounds like a bunch of young people making more money than they have sense to deal with. But um, there's some pretty significant geopolitical impacts days from big tech, right? So the obvious one is if Taiwan's invaded by China, that we mentioned up front, you know, that could cause some pretty significant disruption to tech supply chains, which will everyone's life, by the way, guys, because everything is by tech now. But also just things like the latest US administration's to, well, basically everything. But I've heard some sort of European tech leaders casting some doubt over whether they should be using the big cloud providers out in the US because they just don't know what's to happen.

Hugh Williams: 40:00

A lot of conversations right now about sovereign AI So, you know, a lot of countries thinking, hey, we should our own AI capability that's totally walled within our so that we control this infrastructure, we control what it do, we can make sure that the laws that we have are applied, we can make sure that our data stays in our country. So certainly lots of discussions about that right now. And I think governments and institutions are getting more more uncomfortable with the idea that their data could be anywhere in the world and you know, stored even in the US.

Hannah Clayton-Langton: 40:31

Yeah, I think I saw France the other day were the latest to announce like a for them what was a significant investment in AI. Although I think the context in which it came up, someone saying, yeah, it sort of pales in comparison to what these US tech companies are making. And I guess that's where it becomes difficult to establish If you're a country that wants to play in this pond, right, I'm sure everyone does for reasons we've mentioned, if you're not well established with the capability or the investment in it, you're starting basically on the back foot.

Hugh Williams: 41:01

You need the intellectual capital, you need the the actual to really invest, you need to go and find people and get to stay, have the right regulatory environments, all these of things, the data center infrastructure. So, you know, very, very hard to replicate something like Coast tech, you know, anywhere in the world. And and indeed, you know, if you're going back to the Seven means a good way to round out the show, the market cap of each one of those is more than the GDP of, you know, most nations on Earth.

Hannah Clayton-Langton: 41:28

Yeah, it's pretty crazy. Like they make up 30% of the SP 500, which on a global scale you know, outsized again. And anyone that's investing in like an index fund, you know, if you've chucking your pension or some of your savings into tracker or something like that, you're going to be investing these companies. So you kind of can't get away from them.

Hugh Williams: 41:46

Absolutely.

Hannah Clayton-Langton: 41:47

All right, guys. Well, apologies if any of you listened to that on your morning commute and you're wondering if you've made the right

Hugh Williams: 41:54

But thank you for listening. And we love, we love all of our listeners out there who to the Tech Overflow podcast. You can find us on socials. We are on LinkedIn, we're on X, we're on Instagram, we're also on TikTok.

Hannah Clayton-Langton: 42:08

We are on TikTok, guys. Time to get an account.

Hugh Williams: 42:10

And YouTube Shorts. So you can find us all over the web and if you want the old school version, techoverflowpodcast.com. And we're of course available on all of the podcast

Hannah Clayton-Langton: 42:19

And if you like what you've heard today, do recommend the to your friends and family. Give us a like, subscribe, and leave us a review. We love to hear from you.

Hugh Williams: 42:28

Yeah, absolutely. Go to Apple Podcasts, write a review if you really want to thanks for the podcast.

Hannah Clayton-Langton: 42:33

And guys, you heard it here first. It's time to retrain as a data scientist. So I better go and look that up now.

Hugh Williams: 42:37

Yeah, awesome. I'll help you, Hannah.

Hannah Clayton-Langton: 42:39

Awesome. Let's go and do that. Thanks, guys. See you next week.

Hugh Williams: 42:41

See you soon. Bye.