B (2:37)

Yeah, so that Was pretty cool.

A (2:38)

Yeah. So my understanding is if Starlink supplies Internet to an airline, apparently the contract says they're not allowed to charge consumers for Starlink, so it basically has to be free, which is great. And yeah, just the other bit is just you simply. At least I was on Qatar Airways and you just connect to the WI Fi and that's it. There's no logins, there's no signups or anything. It's just you literally just hit, hey, connect to plane WI Fi and off you go.

B (3:06)

Least amount of friction possible.

A (3:07)

Exactly, no friction. And I did genuinely get a bunch of work done. Certainly I had two eight hour flights and the first eight hour flight I could actually just sit on the laptop and do a whole ton of stuff. So absolute game changer. Definitely would suggest anyone looks out for flights with that in the future if you plan to want to get some work done, basically. And yeah, I believe some people highlighted this to me at work. But yeah, there's been a bit of an acquisition on your side, Sean, is that right?

B (3:34)

Yeah, I mean the big news back at the beginning of December was Confluent is being acquired by IBM. Now there's of course a lot of things that have to go on for a deal of that size and magnitude to go through, but it's kind of shaken up my world a little bit over the last month and a half or so, but it's been exciting times and we'll see where things go. But at some point, probably this year, I'll be getting paychecks from IBM.

A (3:56)

Wow. Yeah, that is a bit of a change on my side. I work for Supabase now. I think some people know that already. And yeah, I was at the Supabase off site. So Supabase is a predominantly remote company, but they get everybody together once a year. So this was about 200 people in the same place, at least half of which hadn't ever met each other. So always a fun one a week with just getting to know a ton of people and definitely worth the effort on everyone's part when you're growing that fast. And almost half the company hasn't met the other face to face. So really eases a lot of communication I think as well.

B (4:33)

Yeah, absolutely.

A (4:34)

So going on to the headlines, we've got quite a lot to cover. We're going to be covering a little bit from almost pre holiday as well, just so that we haven't missed some of the bigger things that happened and make sure that we dive into them a little bit. One of the more recent Things we'll start with the. Maybe more recent ones. Yeah. Tesla has killed Autopilot. So this was their driver assistance system. It was never meant to be self driving. That was not allowed to be said. Exactly. But yeah, I mean, given in the wake of Waymo especially coming into the fold, this is kind of interesting where something that Tesla kept pushing as like their big differentiator. Yeah. Just killed it. And it's been in the vehicle since 2014, I believe. So yeah, that's quite an interesting. And just sort of riffing off of that. Ironically, very recently, I think a couple of weeks ago, someone actually basically had a Tesla drive themself from LA to New York completely unassisted by a human, including all highways and charging stops. So it clearly works. But there's something here where Tesla's just decided this is not where they're going to go.

B (5:45)

Don't they have another self driving mode that's not the assisted version but it's full self driving mode.

A (5:51)

Oh, I see. So they're going to be kind of just like deprecating, right?

B (5:55)

Yeah, I think what they're doing, they had essentially their assisted and then they also had a full self driving mode. And I believe they're essentially in the software terms like deprecating the assisted Mode and going 100% into full self driving mode, which I think probably makes sense. Not that I'm an expert in self driving cars, but I think presumably they see that's kind of where the future is going and they want to put most of the resources behind that and have the people who are driving Teslas start to move towards enabling their vehicles for that mode.

A (6:28)

Nice. Okay. Yeah, that makes more sense. Yeah. There was another couple of things on the mobility front just that Waymo is being investigated at the moment for some infractions. I think of Waymo cars driving past school buses on the wrong side or something like that. Again, I don't think this has any real bearing on are self driving vehicles going to stick around? I think the answer is yes. I think something at this stage would have to go incredibly wrong for that to not hold up. I think only more cities want to have these vehicles on the roads. I believe in Singapore they're going to be trialing it pretty soon and I really look forward to hopefully having self driving cars here.

B (7:08)

Yeah, I mean it's pretty amazing when you kind of just you know, pause for a moment and like think about the fact that we have like, like a, like a robot car like driving around, picking people up, you know, dropping them off and stuff. It's, it's kind of like flying. You know, when you fly you kind of just, it becomes like this normal thing. But it's pretty amazing the fact that you can go in this like, you know, metal vehicle and fly through the air and stuff. Now in a lot of it actually is, you know, autopilot at this point too. Of course there's a pilot there to do a lot of the take over necessary and all this sort of stuff. But it's like these technologies like my kids, when they're adults, self driving cars are probably not going to be anything special. It'll just be the normal thing that they grew up around.

A (7:50)

Yeah, no, you're totally right. Yeah. It is kind of strange actually that we're able to just talk about it so nonchalantly about self driving cars and yeah, you're right about the flying. There was a quote that I read recently about flying which was sort of not that long ago, probably like 70 years ago, which is really not that long ago apparently there was a quote where a pilot would say a good land is one where the people are able to get out the plane alive and a great landing is where you can actually reuse the plane. So given that we're now at the stage where we're able to reuse the plane on thousands of flights per day, that's just insane. So moving on Apple, they're going to be actually using Gemini. Reportedly it's going to be that a Gemini powered Siri will land in February. So this is kind of interesting because as I think most people have caught on, Apple's AI foray has not maybe gone to plan or maybe it's going exactly to plan, which was just to kind of sit back and do nothing for a while. Although Siri was supposed to be that I think to some degree and clearly has, or I think in many people's eyes has failed. Because what Siri promised was actually more like what things like ChatGPT ended up becoming. And so people could see the stark difference between the quality. But yeah, what's your take on them actually reaching for Gemini at this point?

B (9:10)

I think it's interesting. I think Apple certainly has never had a strong presence when it comes to AI. I think when you were back in Assistants, when you had Google Assistant, you had Alexa, you had Siri, Apple's I think was by far the least useful and most frustrating one to use. So I think it makes sense for them to perhaps not try to own sort of the model part of it and team up with another company. Apple's good at user experience, they're good at hardware design. So maybe a better move for them is to kind of focus on the form factor around AI. Whereas a company like Google is really good at performance, they're good at AI and maybe is not as good at historically at sort of hardware design. So can you bring sort of these two giants together to create something interesting?

A (10:01)

Yeah, absolutely. I think this is a good move for them. Really. It's just. Could Apple sort of let their ego not get in the way and actually partner with somebody else? I believe they let go or sort of shuffled on a couple of people on their side, the sort of senior AI people. I believe the person that was behind Siri in the first place, I think he has gone on to sort of retirement or something else. So yeah, there's clearly a big kind of shift around on their strategy, which is just to partner now and just get moving with the level of AI that most consumers would expect at this point.

B (10:38)

Yeah, it's kind of interesting though, what you were saying in terms of, I think all those, whether it was Google Assistant or Alexa or Siri, they were sort of this promise of AI that you would interact with all the time and have a conversation with. And I think part of it was maybe the technology just wasn't there and they ended up being sort of glorified like timer settings and you know, give me the weather and set a reminder, like really, really basic stuff. And, and maybe part of it too was because they were audio based or maybe the, maybe the killer app for audio just was never sort of broke through. But I think like ChatGPT and that interface eventually is sort of what the original like vision and goal of those products were. It's just that ChatGPT had a couple of things probably going for it. One was of course like a much more powerful like AI model. And then they didn't try to go audio first. They actually went with a typing interface. And maybe that form factor is something that just for whatever reason seemed to work better for people having conversations and so forth versus actually having an audio based conversation.

A (11:44)

Yeah, that's a really good point because I think especially with films like her where that was almost 20 years ago at this point and you've got Joaquin Phoenix being this person who has this voice assistant AI thing, which is basically like a human. And so I think that was maybe everybody's framing of like, oh, this is what the future will be when it comes to AI and sort of Apple likes to try and wow people. And that's maybe where they were going with this. But yeah, you're completely right. Then chatgpt maybe. And then people had this kind of bad perception of chatbots because we had been told that this customer service is an AI chatbot, but actually it was just a bunch of if statements, a double thing there where chatgpt clearly thought, well, yeah, voice is not the thing. And actually if we can show just how well above anything that a human has seen so far on the chat front, then maybe that's the way forward. So just sort of tracking back. It was John Giannandrea. Apparently it was Apple's AI chief who's just headed out. Yeah. So let's see. So apparently February, we should be able to see some of these updates coming into Siri, and that was reported by Bloomberg and picked up also by TechCrunch. So check out those for any more details on that. Moving on. This was something that did kind of touch the news before the holidays, but it's kind of an interesting one. And we'll lead a little bit into more of the main topic today, which is just around the hiring environment and what a developer might expect today in 2026 to be sort of thinking about when it comes to landing a job or moving jobs in 2026. But yeah, this was Wall Street Journal reporting that OpenAI is ending a vesting cliff for employees. So for those not fully understanding of roughly how equity works, when you join a company, there are various means of equity, restricted stock units, or what are called ESOPs as well. But generally speaking, if you join a company and they offer you equity, there is what's called a vesting cliff. And that is where there is a longer period at the start of your tenure where that stock is not really allowed to be yours until after a certain point in time. And usually that's one year. So it's saying, hey, if you manage to stick it past one year, you now have the right to apply to get this stock in your name. There's lots of other complications there, but that's a basic way of putting it. What OpenAI are saying is you're not going to have to wait one year. You're going to be able to join the company. And I think it's almost like monthly or at worst, quarterly, you're going to have these chunks of equity vest, which is just a hugely different way of doing things compared to virtually any other tech company out there. So, yeah, what did you think of this, Sean? I mean, you're right amongst the companies in the Valley, and this felt like quite a sort of shakeup to how they all operate.

B (14:43)

I would assume that OpenAI's approach to this is that they feel like it's going to give them some competitive advantage to attracting top tier talent. And there's such a competition around hiring the top tier AI talent right now. Just like we've covered before with the big alleged bonuses that Meta was giving out for various AI leaders and stuff like that, this is sort of the latest move that OpenAI is making to try to hire the best talent, make it really attractive. And if you can start vesting from day one, I guess it reduces some of the fear that you might have with joining a company where maybe you're like, well, what if I really don't like it? And then I'm stuck there for a year until. Or I walk away with nothing for the investment time. So I get it. Maybe that helps them close more candidates. But it does certainly change, I think, the nature of how people potentially think about their jobs.

A (15:42)

Right.

B (15:43)

When you join a startup, I think part of the fun part of joining a startup is trying to be part of something bigger than yourself. You're joining for the mission. Obviously, everybody wants to be rewarded for the time that they're putting in and see some financial payout, but it's certainly an early stage. The chances of that payout actually happening are pretty slim. So you're buying into like, hey, I really believe in the mission. Even if this fails, I really want to try to make this happen. And then there's also, of course, you learn a lot during that process and this kind of changes the nature a little bit. I think it's almost like you're not getting a bunch of people who necessarily are there for the mission, but you're getting mercenaries that are there because they care primarily about the financial outcome. I just wonder how that changes the psychology or does it create certain biases even towards the type of employee that you're going to attract?

A (16:43)

Yeah, for sure. I'm kind of on the fence here. Apparently the applications chief, Fiji Simo, had said that this was to encourage new employees to take risks without fear of being let go before accessing that equity. Which is what you also touched on, Sean. Yeah, that sort of makes sense. But I guess as someone who has built a company in the past, I think I would just feel very uneasy about bringing people into the company and within one month they suddenly have share of the company and they could, in theory then walk away if they want and they walk off with that equity. Very different scales here. And I think the speed at which OpenAI has to develop world beating products, I guess a year is just maybe not realistic anymore. Someone maybe can come in and make a huge impact in say six months and actually that's good enough. And if they can't hold onto them, so be it. But yeah, it's a very sort of interesting way to differentiate and potentially rather than dangling bonuses that people like Meta were doing and well that didn't at least play out quite so well. A bit of a mess over there in terms of AI hiring and strategy. Well this is a different way to do it. But then that said, it's not like this costs them 0. OpenAI is projected to spend 6 billion on stock based compensation this year and that's like nearly 50% of entire projected revenue. So I mean that's just like it still costs them a lot of money to run this.

B (18:09)

Yeah, I mean they're basically spending 50 cents for every dollar that they earn just to keep the people building the product. But and we're going to talk a little bit about the code red scenario and the pressure they're getting from the hyperscalers in particular at Google. In this hyper competitive world of AI, people are just full steam ahead, full pressing on the gas all the time and you're competing against some of the most well resourced companies in the world that are also trying to own the same space. It just seems to be a place where for some period of time people are just going to have to burn a lot of money to try to own that space and do as much land grab as possible. It's like in the early days in the ride sharing wars between Uber and Lyft, there was such a both companies were spending a lot of money in the red massively to try to land grab across the world, all these different spaces and really roll out globally. And it'd probably take a long time for them to rebalance the earnings there. But it's like if you can dominate that space and of course there's going to be return on that investment eventually.

A (19:15)

Absolutely.

C (19:17)

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A (21:51)

So yeah, I look forward to seeing how this plays out. I had a friend that worked at Meta a while back and they also had a more, to my understanding, slightly more generous stock scheme than most. I think it was something to do with it was maybe six month cliff and then then it was monthly, something like that. Interestingly, that person didn't stick around that long at Meta and I think did quite okay out of the shares vested, but then again they probably contributed a lot. But yeah, it's sort of like do you value ICs who come in and do a huge amount but then maybe get restless more quickly or do you value people that are in it for the mission and plan to stick around or you're trying to get them to Stick around for a longer period of time. I think that remains to be seen. As you called out, Sean, even though you can have vested stock, the likelihood that you're actually able to benefit from this is a pretty low percentage in the grand scheme of things. So again, for anyone not sort of familiar, you have to have what's called a liquidity event, which basically just means some way that these vested shares can be bought by someone. Is that one of the investors is that the company themselves buy you back? Is that. The most commonly understood one is ipo, which is these days, not unlikely, but it's more unlikely than it used to be. And some companies are very unusual, but are very friendly in this way where they allow some portion of your vested stock to be bought back during any funding round, for example. So when you go from series C to D, actually they set aside some money and they say, hey, if you've got some vested stock, then let's just say 25% of whatever is vested will allow you to cash that in. But that's an incredibly friendly approach and does not happen a lot.

B (23:44)

Yeah, I mean, databricks is doing that, but databricks seems to be at least on a path where they're never going to go public. So they need some way of creating essentially a liquidity event for their own employees. And then of course, there's secondary markets too.

A (23:57)

Yeah, true. But yeah, as I've also seen, some of these sort of friendly policies actually explicitly say you cannot use secondary markets. So it's like, hey, join a friendly policy, but you can't actually use a secondary market to do that as well. So, yeah, the high level here is for anyone thinking of joining a company and we're going to get onto this maybe slightly more in the main topic, but anyone joining a company and equity is part of it, do think very hard about what do you think the prospects of this company being and do you trust the management to make good on what they say they'll achieve and how they plan to make liquidity happen? Because often you can be negotiated down on salary quite big time if you're made to believe that the equity is more valuable than it really is. And Shopify famously now allow all employees, they're a public company, so it's a little bit different. But they famously allow employees every year to basically apparently use a literal slider to choose equity and cash and you can just choose how much of your compensation each year. And part of the reason they did that was because they had a crazy spike in the share price. They Found that over a couple of years where people joined, unfortunately the equity they were offered, the price they were offered, what's called the strike price was just crazy high. So there was almost no point in receiving equity. So I think that's very smart where they just say, look, actually if you look at the numbers and don't think the equity right now makes any sense, don't take any, that's fine. But going back to something you touched on, Sean, and was going to be our kind of next final news topic, actually. No, sorry, penultimate news topic. But what happened before the holidays that OpenAI code red. So this was where OpenAI basically said that they sort of understood Google is actually beating them on basically the approach to producing models. And this is boiling down to a TPU versus a GPU and having developed what are called TPUs. And we'll get into that in a second. Meanwhile, most other producers use GPUs, like Nvidia is the most famous producer of those. And I think the sort of turning point was Gemini 3. Is that right? Yeah, I think so, yeah. So this is maybe also linked to this vesting piece with OpenAI. They sort of went, oh, shoot, we have to find a way to get people in the door now and not have them worry about this one year thing. We just need them producing now. But yeah, let's just talk a little bit about this whole GPU versus TPU thing. It's obviously been covered quite a bit before the holidays, but I think it's still pertinent to sort of understand where these two sites are coming from.

B (26:39)

Yeah, I mean, I think that this is kind of the latest in some of the unfair advantages I would say that like Google has over a company like OpenAI when it comes to model development and then also distributing that model to a number of people. Like one, they have a lot of data that companies like OpenAI don't have access to because they have a lot of products where people are generating that data or because of Google search. They also have deals where they're able to index data that typically is behind paywalls and things like that that other companies don't have those deals for that they just carved out over 20 years of being the main search company in the world. So that's one big advantage. They also have thousands of products in the B2C space that reach billions of customers. So when they come out with a new model, they have so many different surface areas where they can touch users. They're much wider reach than a company like OpenAI has currently. And then with the GPU TPU thing, it's kind of like another thing that they have now where most people are building and running models and GPUs. I think if you've been paying attention to the market at all or what's going on with Nvidia, you probably have some sense of the importance of GPUs. But they were originally designed for gaming and graphics, and they're really great at parallel processing. But because they were designed for graphics and gaming, they also have to do other things like render textures and physics and lighting. So they have kind of like, in the world of AI, this architectural baggage that doesn't really help when it comes to running AI processing. So they end up spending energy on other tasks that are independent of the pure AI math that they actually need. Whereas with tpu, which is a tensor processing unit, it's actually a chip built specifically for doing AI math. So what Google did was they stripped away all that baggage, and then they designed it to do one thing only and do it really well, which is massive matrix multiplication, which is essentially the core thing that you need to do for deep learning. They originally did this back in 2013 because they had realized that if every Android user just used voice Search for 3 minutes a day back then Google would have to double their data centers as a result of that. It wasn't like they envisioned this world or anything like that, but they just had this, like, this problem. And they used sort of the fact that they have a lot of really smart engineers and a lot of resources, and they're just like, hey, like, I know how we'll solve this problem. We'll design our own chip where we can run this much more efficiently and reduce the cost essentially of scaling these data centers. Because one of the challenges with AI right now is a lot of times your training models or you're running inference is the people running they had to buy those GPUs from Nvidia. And Nvidia has like 75% gross margin on their chips. Whereas if Google's building their own TPUs, they avoid that markup entirely, where everybody else in the market is essentially paying Nvidia for the chips. So that's a pretty massive advantage that they have. And they've also restructured their company very much because of the existential threat that AI was causing the company a couple of years ago. And now they just have the whole company's kind of steering in that direction of owning the AI space. And I think as a result, the combination of all those things led to this code red situation. OpenAI for sure.

A (29:53)

And I guess it's sort of interesting that maybe OpenAI they just sort of underestimated the power of this approach and maybe for good reason, because Gemini 1 and 2 were impressive, but nobody was apart from, I think Gemini 1. It was like large token window was kind of its biggest advantage. So people would use it for tasks where that was really the crux of what they needed to get done before other technologies came along to help chunk things up. But Gemini 3 is actually where people say, you know what, this is actually producing way better across a bunch of factors. One of them was actually more on the image front. All these infographics floating around before the holidays were all Gemini 3, basically. Again, Toby Lutke, the Shopify CEO, posted a pretty great one that he said, this is Gemini 3. But I'm using this because I want to show he took one of his talks I think he'd given to the company and he really wanted to capture that in an infographic. And Yeah, I think Gemini 3 did a great job at that. So very interesting.

B (31:03)

Yeah, I mean the graphics stuff has come a long way. I encourage you to play around with nanobanana if you haven't exactly that was it.

A (31:11)

Nano Banana.

B (31:11)

Yeah, yeah, yeah, yeah. It's amazing because I think a lot of where at least when I've played around with some of the image generation stuff from the models is, you know, you can get there but it takes a bunch of prompting and they tend to spell things wrong a lot. So it takes a bunch of work to get what you need. And then after the latest model came out from Google, it's just one shot and you have something pretty amazing. It's just really, really obvious jump in terms of the step function of capabilities for sure.

A (31:39)

The only downside was in my opinion LinkedIn just became an absolute garbage of all these Nano Banana images. They were impressive, but it seemed like nobody could post a thing without this being part of the post. And yeah, had to kind of shut off LinkedIn for a but yeah, very impressive. There hasn't really been a lot reported since this Code Red and then it sort of all died down a bit over the holidays. So yeah, I think this is one to sort of keep on watch and I'm sure we'll be revisiting where these two are at on this front probably later in the year. And then finally, just a final sort of headline news point. This was a company called Manus being acquired by Meta. Now I had heard of Manus since I live In Singapore. We're going to get onto why that's significant in a second. But a lot of the world hadn't really heard of Manus. I'm curious, had you heard of Manus before the acquisition, Sean?

B (32:29)

No, I hadn't. I saw that you had surfaced this and I did a little bit of digging in, but I hadn't heard of the company previously.

A (32:37)

That was sort of my impression was that a lot of the world, and especially the US market actually hadn't heard of them. And so when this was announced, I mean, at 2 billion, so nothing for Meta. That's maybe a rounding error at this point, but it's still not a bad exit for a company that was maybe struggling to find exactly its product market fit, in my opinion. What does Manus do? It's very much consumer facing AI, but they focused more on kind of production of an end product. So especially things like presentation decks or a full website that can just get spun up and hosted, that kind of thing. As opposed to chatbot helping you understand something. It's really tell me what you want produced for work purposes. Basically it was kind of their angle and that does require more of an agentic approach. Various processes going on, putting that thing together. Very expensive though. And I think that was part of the problem. A, they were running out of money. B, consumers. I went to a conference last year. I did mention this on one of the SED news where someone actually stood up and asked very publicly to the CTO of manuscript. I don't understand. I spend so much money on Manus and it just runs out every week and I've got to keep applying more credits in. Do you plan to address this? So there's a bit of tension there. Clearly users say, okay, the outputs are maybe helpful, but I really don't understand your billing model and I think I spend too much money with you guys. But they seem to be fundraising. That was the sort of murmurs over here. And just to point out what is Singapore Connection, people refer to them as a Chinese startup, which is true. They started in China, but they did move to Singapore in 2024. And the big reason really for that was de risking and trying to move that image away from being that they're part of the Chinese ecosystem and they wanted to be part of the world ecosystem, which seems to have played out in this Meta acquisition because I think it would have been unlikely that Meta went to try and acquire them if they were still based in China.

B (34:44)

Yeah, I mean that is a challenge for sure. And I think I read that all ties to China either been severed or being severed. It's interesting. You said that they were running out of money and they're fundraising. I guess that would be the case because they were spending a lot on token costs. But I had read that they were doing $100 million in revenue. So they certainly were customers and people paying for it.

A (35:04)

Exactly. People paying for it. I think it was the sort of. I'm curious to know how much this was actually costing them to run this thing. Do they have as good relationships, say with Open or rather Nvidia or data centers that OpenAI say have to run these things at a cost that is bearable? I'm not entirely sure.

B (35:24)

The thing that I struggle a little bit with is how does Manas in particular fit into whatever Meta's overall AI strategy is? I struggle to see the alignment and even where Meta is going with AI is just not very clear to me. Maybe there is some grand unified plan, but it's lost on me.

A (35:44)

Yes, there were a few jokes flying around about this at the time. It was something like one of the jokes was asking Alexander Wang, who's their chief AI? And it was sort of like, message from Mark Zuckerberg to Alex, like, hey, can you get us a Manus? Can you buy Manus for us? As in a subscription? And then Andrew Wang replies, done. How much? Like 2 billion. Oh, I just bought the company instead of buying a subscription. And yeah, I think that's kind of a lot of people's thoughts here is where is this fitting in and why? And the only real logical explanation at the moment is just the lack of consumer facing AI that Meta seems to have produced. Okay, they are behind llama models, but they require developers to kind of really be the ones taking those to a consumer in whichever way they want to do that. But I wouldn't say people. They've tried to integrate Meta AI into WhatsApp and for a few weeks people kept sort of, you could say, like I and someone would ask a question in a WhatsApp group, for example, and some clever person would say, I answer this question. But that just gets very boring very quickly. The whole point of a group chat is to have conversation and see what the funny answer someone gives is. It's not to have some know it all AI in the group chat correcting everybody. So that didn't work, at least in my opinion.

B (37:06)

Yeah, I guess the big question is if Meta is to stay in their wheelhouse of social network connecting people. And you can debate the merits of the value of this connection but it's always historically been about people connecting in some way. What is the role of AI in that world where it's historically been about people being able to connect over, hey, you and I, we love Pokemon. Let's talk about that or whatever. Where does AI fit into that beyond being some form of recommendation system or a way to surface other types of connections?

A (37:42)

Yeah, and one sort of maybe more macro thing here is, I was listening to, I think it was Tim Ferriss podcast he had Bill Gurley on, who's a very well known investor. He got into things like Uber early and he's been visiting China a few times, which I think is very smart because you really have to go there and understand what's going on. But he did highlight the fact that actually the approach of the Chinese government these days is to say to startups like do not get too big, we need you to all compete with each other. And yeah, there should be no tall poppies basically. And I think that sort of is what's happened here, that Manus saw that and was like, well, there's no way we can break out if we stay in China, so we're going to move to Singapore. And I've seen this with quite a few startups at least in the last couple of years. I'm curious to see if some kind of regulatory thing comes up in China that stops this from being possible. If you form it in China, then that's it. You can't move it somewhere. I don't know. But we definitely saw a lot of these moves around 2024. I'm curious to see where this net's out now because this is a bit of a high profile loss, I would say, for the Chinese startup ecosystem. So as we move on, our main topic today will maybe be a little bit shorter than usual. We had a lot to cover off in the news, but it was really just looking ahead to the job market this year. I think last year was a lot of wait and see because people were quite unsure and anxious perhaps about this sort of phrase, AI taking your job and this kind of thing. And we did see quite a few layoffs through 2025. TechCrunch put together a very comprehensive list of who had been laying off and why. I guess the standout for me though on the layoffs, you can put together a report of layoffs, but actually I don't feel the numbers were that crazy. Each month we were talking maybe five digit thousand layoffs per month, but that doesn't feel crazy. And actually a lot of the People laying off. Either these were just companies that just weren't quite hitting product market fit or even like Hewlett Packard had said, we're going to cut 4,000 to 6,000 jobs by 2028. I mean, I think something like Hewlett Packard surely has room for kind of thinning down, especially with AI being able to do things that probably somebody had to sit and manually and maybe even enjoyed manually doing. But maybe as we kind of look more at the developer standpoint, I mean, Sean, you did the episode with Stack Overflow that came out towards the end of last year, the Stack Overflow Survey. That's a little bit interesting just to sort of. Because they get the stats kind of on who's moving where or what kind of technology is being adopted and how does the job market look for someone at that snap Snapshot in time. And yeah, was there anything else that kind of came out there that might help us see where 2026 might land?

B (40:40)

1 thing I wanted to say before we jump into the Stack Overflow Survey too is that I think if you look at the overall metrics for tech employment, they're actually growing. Perhaps the skills or the nature of the jobs are changing a little bit. And the roles that tend to contribute to strategic growth, whether that's like AI ML skills or data skills or something like that, those are definitely in demand. But there are some roles I think that are deemed non strategic that are perhaps being cut. And I think the other thing is that not all the layoffs are necessarily tied to displacement by AI. Some of the layoffs are due to realigning resources around certain efficiency initiatives. Or even if you look at Google from a couple years ago, they had their first fairly large scale layoffs. But at least from my friends that have been there, a lot of them have actually been hired back into new roles. A lot of it was kind of reshuffling of the deck and stuff like that as they needed to react to the market change. So there's definitely some of that going on and I think that sometimes the headlines are a little bit sensational when it comes to this. But regarding the Stack Overflow Survey, I think one of the things that was interesting from there, and I know it's kind of potentially like a macro issue around how we think about the impact on AI and developers and what it might mean to be a developer in the future. So if you look at the history of using some of these AI tools for programming, we started out with Copilots. We're kind of just like a superpowered code completion and the general industry action. And also if you go back and look at some of the stack overflow surveys from a couple of years ago, was that they were kind of good for junior devs, but not necessarily super helpful for senior engineers. And senior engineers were like, I don't really need this. I know the language inside and out or whatever, and I can just program this faster myself. But then I think in the last year there's been a change in that sentiment, and it's also reflected in the survey is that with some of these coding agents, there seems to be the shift about who gets the most value out of them. To use them effectively, you kind of need to know how things fit together architecturally. So we're seeing that really strong engineers are becoming even stronger engineers by leveraging some of these essentially really helpful agent interns that they can now depend on. But I think there's some fear that if you're junior and you don't get as much value out of these tools, and if you're always insulated from the details because of the AI, how do you ever get to a place where you're senior? So what's that do for. It's great that we're leveling up the senior engineers, but if we never, ever build the future of the seniors for the next generation of coders, what happens in the future? And I think part of this might be that we need to just think about how this shifts the educational focus for engineering. There's things that we've historically valued with engineers in the workplace or even from an education standpoint that maybe now are less valuable. Really deep knowledge of a particular language maybe is not as valuable now as having a deeper knowledge of how things should be architected, for example. And maybe there needs to be more emphasis into that from computer science education, and you need to be working, get used to working at a higher level of abstraction sort of immediately, and that could be something that needs to change. But there's still going to be sort of this. Even if the answer is education, there's still going to be potentially this risk of a generation of coders who are sort of young in their career and maybe they're not able to take advantage. But I guess the counter argument I've heard to that is that, well, the people who are younger are also more open to using the tools and are able to level up their skills on the tools faster so they can pick up the work and start contributing immediately. So I don't know the answer, but I think this is kind of just the things I'm seeing in the survey and some of the conversation that's going on right now in the market.

A (44:27)

Yeah, I think my take on this is almost not a lot should change really at that fundamental education level. Spending four years in CS is probably and full disclaimer. I did not do a CS degree so I was self taught probably could have benefited from a CS degree but just didn't happen to do one and ended up just having to learn slightly the harder way some of the fundamentals. But those fundamentals have always stood me really well I think even though now, especially today I don't code daily as a job, I don't think either of us do exactly. We both dabble probably in code to prove things or just for pure enjoyment as well. But there are many, many many more people in Supabase far more talented than I am at coding and I'm more useful to the company as more of that high level, able to look at how something is architected or looking at what the risks are. Basically like de risking projects. But I have to understand coding as well and be able to converse with engineers about coding. And equally I actually speak to a lot of the engineers and it's at least it's no more than 5050 when it comes to who are actually using any AI tools. And I would say it's those that are working on the really low level stuff are not using them. And I think that's fair in terms of using them maybe more for a sanity check or especially some security checks. I've seen some really interesting progress from us using some AI based security tooling that can really pick out some pretty nuanced security flaws. But equally having something generate a bunch of low level code that is going to probably sit in the code base for years and years and years, the likelihood that that's best generated first by AI is unlikely. The place it's still doing very well like AI does very well is SQL. So anyone who's just basically putting together complex database statements that seems to be where it does very well. But yeah, I mean back to sort of more of the job side of things, I think again a CS degree is not as useless as I think as people are making out. And I do think open source is a big driver for or should be a driver because that's actually where you can get real hands on experience without already having joined a company. And many big libraries open source projects are basically rejecting pull requests if they have any inkling that it's majority AI generated. And for Good reason. I think they're just getting swamped with what look like AI pull requests. And so there's sort of a way to filter out actual engineers applying their brain to this problem as opposed to just thinking that they can out prompt somebody else. So I think the super high level here is that it is not as doomsday as maybe the news makes out and there is a lot of opportunity for engineers.

B (47:21)

Yeah, I mean, I think it's still very early days. I think we're still figuring out a lot of stuff and things are moving incredibly fast as well. So things might seem a certain way right now, but it could be in six months. Things change dramatically as well. But ultimately it comes down to, I think people who have solid fundamentals and a breadth of knowledge tend to have a place in tech. In the work world, there's kind of always sort of value behind people who can wear many hats and kind of flex across a bunch of different roles and understand a bunch of sort of the core fundamentals of how technology works. Yeah.

A (47:56)

So we're going to leave it there today that we may touch on this a little bit more later in the year as well, just as we see how sort of hiring is going. And I think this is just an ongoing topic. How are engineers faring with AI? I mean, we're still only really in maybe the start of year three of coding with AI proper. So we've only seen two years of this so far. And this is still going to be a very pivotal year, I think, for how this plays out. As always, we like to just wrap up with a fun thing of looking at hacker news. I think this is an interesting one this week where Sean, you and I both landed on the same suggestion. Do you want to introduce it?

B (48:34)

Yeah, sure. Doom has been ported to an earbud. Doomsbuds.com I think when I saw that I was like, this is the kind of ridiculous stuff that we always like to talk about and highlight on these episodes. Just people doing fun stuff in engineering, whether it makes sense or not. Sometimes it's like these super over engineered pet projects that people have and it's just fun to talk about. And it's fun to see how people apply their sort of creativity and innovation to different projects. And this one fits that bowl for sure to be able to run essentially Doom through an earbud. So I wasn't surprised also that you grabbed it too, because it's the kind of thing that you and I both seem to gravitate towards.

A (49:14)

Absolutely, yeah. I had been swayed by Another one a couple weeks ago, that was another one of these disposable vape things. But then we've already covered that and this was just. I think that one going even deeper. This definitely was like, wow. And they say it only works on what's called the pinebuds Pro, which is earbuds that have open source firmware, basically. But again, I just looked at the specs of these earbuds and I was like, okay, well, I mean, these days they've got dual core 300 MHz processors, they've got four megabytes of flash memory, three microphones. Yeah, I mean, earbuds are pretty advanced these days. And doom is this sort of recurring theme, right. Of where can you run doom? We actually had an episode out, I think, at the end of last year, which was running Doom in typescript types. Like, not even just in typescript, but typescript types. So if that piques your interest, go check that episode out. That was with one of the. Our other presenters. But, yeah, I love this Doom on an earbud. And it's sort of like. I'm not sure if it's actually still up at the moment, but it was sort of. You were able to jump into Twitch or something and get on a queue and then control Doom being hosted on this earbud. But, yeah, it's doombuds.com if you're interested. And we thank Aaron S. The user on Hacker News for posting that. Yeah, unfortunately, that's all we've got time for today, but do join us again next month. We'll be hitting all the news highlights and probably a bit more of hacker news than we did today. So, yeah, hope to see you there.

B (50:50)

Thanks, everyone. Cheers.