← Software Engineering Daily
Software Engineering Daily
SED News: Corporate Spies, Postgres, and the Weird Life of Devs Right Now
00:43:39
Welcome back to SED News, a podcast series from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the latest stories in software engineering, Silicon Valley, and wider tech world. In this episode,
Loading summary
Transcript67 lines
- [00:13]
Gregor
Hello and welcome to another SED News. This is a different format of the SE Daily podcast where we basically just take a spin back through the last kind of few weeks of tech news, obviously especially software news. We look at things like the main headlines, we look at hacker news and we just kind of dive into one topic in the middle there as well, which we'll get into, which is kind of the state of being a developer today. So I've got Sean Falconer with me as usual.
- [00:39]
Sean Falconer
Hey. Hey, Gregor. Great to be back on this. I'm glad our pilot episode went well enough that we're back to start an official season here.
- [00:46]
Gregor
Yeah, exactly. Exciting. So thank you to listeners for listening to it enough. That means that this gets continued. So thanks so much for that and obviously any feedback, please always find the respective socials at the end and you can ping us and let us know what you think. So yeah. How are you, Sean? How's been the last two to three weeks?
- [01:05]
Sean Falconer
It's been good. Been at Snowflake Summit this week. I know we're going to be talking about some Snowflake stuff later. Databricks is moving in basically tomorrow to take over the exact same location in San Francisco. So I'll be there next week. I actually have three talks next week and a whole bunch of different meetings and stuff like that. So it's going to be a pretty intense week. But I'm excited to talk about all the stuff going on there. I mean it was at Snowflake launched like 100 products. It's getting to be like an AWS Reinvent where it's impossible to even keep up with all the things that they're doing.
- [01:33]
Gregor
Yeah, awesome. Yeah, I'm back in Singapore. I was the last episode I did from Scotland. It's been a very hot May in Singapore even for Singapore. So yeah, very hot and even dry and yeah, I'm just crunching through a lot of code stuff right now. But as we'll probably get into crunching through code is a lot of piloting a space rocket right now in terms of cursor. You're just going to sit there and make sure it's not doing anything funny, but letting it do the hard work. So we'll get into that. But anyway, let's get on to the mainstream headlines. So we're going to be looking at a couple of things. We're going to be looking at deal and rippling and what's going on over there and we're also going to be looking at databricks and Snowflake So we might kick off with Dylan Rippling. Yeah, it's been a funny one going on there. Have you been following along with any of this, Sean?
- [02:21]
Sean Falconer
I hadn't. And then of course I knew that you were interested in talking about this, so I kind of looked it up and I was like, oh my gosh, let me get the popcorn. This is something that you see in movies and stuff like that, so maybe you can help provide some background and context for that. But I do have some thoughts on it.
- [02:37]
Gregor
Yeah. So this came up on my radar about two weeks ago when effectively an employee that is supposedly a rippling employee. And let's just backtrack for a second. Who are rippling and deal in the first place? They are these HR automation platforms. Rippling, I would say maybe has the sort of slight more cache, if you like to give it that the CEO was the ex zenefits CEO. There was a whole bunch of drama there. And we can always vaguely talk about why this also plays into it. But yeah, rippling. If you're in the U.S. you probably know a bit about rippling. But if you're not, then it's sort of you. You get to just white glove, have someone onboard all your employees, whether it's through the IT system or for payroll. They'll even deliver a laptop to your employee preloaded with all the necessary security and software, et cetera. So very cool platform and sort of service deals, kind of the same thing, but I would say they're maybe a little bit more kind of on the in theory. So the steady as you goes kind of thing with compliance and so on so forth. Okay, so the deal here is, just to use a pun, is that there was a rippling employee. However it turned out this rippling employee had been kind of spying on his own company, effectively paid by deal to do this. And this came out as this person in Ireland, I believe it was. And it's been reported that this person sort of was confronted in the office and literally threw his phone down the toilet. So proper spy novel stuff.
- [04:05]
Sean Falconer
Was there any smoke bombs or anything like that?
- [04:07]
Gregor
Yeah, exactly. I mean, and I'll be honest, quite frankly, it didn't sound like there was a lot of money involved here. We're talking like, I don't know, it was like $55,000 a month or something. So it seems like quite a big risk to take for what's ended up happening. But what's now happened is that so deal under fire for this, corporate espionage, et cetera, feels like an HR violation, right? Yeah. I mean, at the very least. Yeah. And then we've got deal countersuing, but they're kind of doing it on the. Well, Rippling. You've got people pretending to be customers, but they're clearly just there to be spies. And I think this is where it all kind of unravels a little bit for the deal side. Because I think, Sean, it's fair to say that this is just pretending to be a customer. That's been part of the playbook in tech since forever, right?
- [04:52]
Sean Falconer
Yeah. I mean, I think that even if you look at some of the stuff that was going on in the heyday of the Uber Lyft rideshare wars, there was a lot of. I think, or at least I heard, like, I'm sure you can find out some confirmation. But from what I remember anyway, there were situations where people were paid or received something to essentially go into, say, a Lyft car and then try to convert that driver to be a driver for Uber and so forth. So there's a lot of this kind of like shady business that tends to happen in tech sometimes. But I've never heard of a situation like this. I'm sure it happens. Actually, there was podcast I listened to a couple years ago on the Jordan Harbinger show that I think the title was Struggling Actor to Corporate Spy. And it was about this guy's journey who was an actor or trying to be an actor in la basically. And he took this gig, this job where the job was essentially to try to infiltrate different corporations and essentially do this kind of corporate espionage. And they would hire these actors to do that because they're actors. And he took it because he just needed the money and stuff like that. And he turned out that he was really good at it. It was really, really fascinating podcast I recommend taking a listen to. But it kind of reminded me of that. It's this thing that you maybe hear about from time to time, just a rumor of a rumor, but I've never seen anything in the news quite like this.
- [06:08]
Gregor
Yeah, likewise, I'm even aware of sort of people that have pretended to be customers on products I've worked on and so on and so forth, but nothing like this. Where I think in the case of the Rippling employee that was doing this for deal, in theory, it was something to do with Slack channels, was kind of what gave the whole gig game away that they'd sort of. They set up within Rippling. They set up a honeypot Slack channel and then that sort of got that person in there. And yeah, it all Just sounds a bit ridiculous. And yeah, this doesn't look great for Rippling. I would say especially. Well, I say especially it doesn't look great for them either because yeah, the CEO was the X Zenefits CEO. There was a ton of stuff that went on there and two sides to every story.
- [06:49]
Sean Falconer
That place was scandal central.
- [06:51]
Gregor
Right, right, exactly, Scandal central. And yeah, Parker Conrad, that's the CEO of Replining now, he's come out in public before this landed to tell his side of that story. And sure, there are always two sides of every story. And why see Jessica Livingston very much back him and sort of believe he was kind of set up a little bit by investors to sort of take the fall for a lot of what was going on at Zenefits. But at the same time here we are again, another massive drama company where he's the CEO. So yeah, it just doesn't look great. And yes, it's had some funny sort of side effects that apparently, I don't know which company it was but apparently a new security startup launched and they actually spoofed this spy story in their marketing. So it's sort of flowing through the zeitgeist at this point. So yeah, we're going to see what happens. It probably will set some precedent for companies in the future for how far they wish to take it when it comes to this sort of. Is it espionage or is it just sort of the tech world? Well, I guess we'll find out.
- [07:47]
Sean Falconer
Yeah, it feels like one of those things that ends up, I don't know, like disappears behind closed doors. Some sort of deal happens that the companies come to some sort of understanding, money exchanges hands, no one necessarily knows all the details and stuff like that.
- [07:59]
Gregor
Yeah, exactly. So moving on to the next main headline. Yeah, this is all around Databricks Snowflake. You're the man to talk to about this, Sean. So what's going on there?
- [08:10]
Sean Falconer
Yeah, so as I was saying at the start of this like we're in the cusp of the Snowflake Databricks takeover of San Francisco right now with their two major conferences back to back here in San Francisco. But in the last couple of weeks, first databricks announced that they acquired the database company Neon. And then Snowflake, I think it was the first day of Summit, announced that they had acquired crunchy data. Both of these are cloud based, essentially managed postgres. So I don't know which was happening first. I wouldn't be surprised if one company was moving to acquiring one of these companies. The other one got Wind of it and, and maybe that escalated things, but Neon was acquired at a billion dollars rumored anyway. I don't know if it's public yet or all the details on that. And crunchy Data was like 250 million. And then Neon's like about 140 employees. Crunchy around 100 employees. I'm not sure the traction of both companies, but essentially similar moves by both of these huge data players in the data and AI world. And I think there's a couple of ways to interpret it. One is that these companies are interested in owning essentially all potential movements of data. So they've historically focused primarily in the data tier of the business or in the analytical area of the business. So focused on AI workloads and analytics workloads and running a warehouse or data lake and so forth. And this is a movement to more of the transactional database. OL2P Snowflake did launch something a couple of years ago called Unistore, which was supposed to be sort of one query engine that could query both transactional databases and analytical databases. I'd never heard of a lot of people using that. But historically like this hybrid database model had never really taken off as a category. It's kind of hard to market because you essentially are trying to sell to different types of users. You have your analysts and certainly in the databricks world maybe have a data scientist and so forth. And then the people who are building applications are building on sort of traditional application databases. So it's kind of like two different worlds. But my take on it, and I think what a lot of people are writing about in the news is more, this is more about motivation around owning data in relation to AI agents. So agents need both essentially historical data that maybe exists in a lake, or maybe you want to use this historical data to build up a model yourself or to even use in some fine tuning sort of offload mode. But when, when you have the agent sort of operating in a customer facing application, you're probably not necessarily going to be reaching back to these massive columnar stores to pull that data. It doesn't necessarily make sense. You need a smaller representation of that data that is designed essentially for something like row level access or ephemeral spinning up on databases and stuff. Like Neon talks about how almost all their databases are actually provisioned automatically through agents. So agents are actually provisioning these things, using them for short term storage for whatever reason, maybe message passing, short term memory, stuff like that, and then blowing them away. So they need some sort of application to sort of serve that need. And there's this new area also that's cropping up that could also relate to why they want to invest in this is around this idea of a context store. So in sort of traditional ML you have something called a feature store that represents your vectors or your features that you can store and you can have quick access to that from a model and a context store. Is this sort of build off of that idea that for particular agents I want to. It's almost like a caching layer for the context that's relevant to the agent and type of work that's going to perform. So I think it has a lot more than that. I actually wrote an article about the sort of databricks NEON agent connection a couple weeks ago. I got a fair amount of attention, but it's kind of interesting. Like two of basically the same moves within a couple weeks of each other from two of the major data companies.
- [11:55]
Gregor
Yeah, I mean, certainly the timing seems a little bit too coincidental on that front, but I mean, yeah, Postgres has been having its moment certainly over at least the last year. I'm sure you and I used Postgres for a long time, but then suddenly it's kind of come back in a big way. I mean, the version of this that I use and know best is Supabase. And I'm curious, do you have any read on. Was any of this sort of influenced by how successful in theory they're getting as well? I'm aware that they've. I think they just closed their series C if I'm not mistaken, or it could even be D. This is where the letters or just they've gone from B to C, at least within the space of about a year or something. And the reason that they claim that they've grown so fast in just the space of a year is the agent side of things where. And we're going to also get onto this in the main topic in terms of AI coding tools and they're basically just spinning up instances of sipabase. And a lot of the users don't even realize that's kind of where the data's living. Is there any sort of part of that in this as well? When you've talked about agent, is it sort of that side of things or is it more directed, you think, by the user? They kind of know that they're using neon or crunchy data?
- [13:03]
Sean Falconer
I wouldn't be surprised. I mean, I think that if Supabase is getting a lot of traction there, I'm sure the powers would be at These companies are paying attention to that kind of stuff because everybody wants to get into the agent market. And if you're as big as Snowflake and databricks, then you want to own a lot of that market. And I think that one of the things that people are finding out is that the data requirements for AI agents and gen AI applications in general is different than traditional ML where traditional ML is about building models, AI agents and gen AI apps is about building software on top of models. So you essentially while you're interacting with the model, you're going and retrieving essentially the data relevant to the model to craft a prompt to correctly contextualize what you want. So that changes sort of the requirements where a lot of times I don't think you can rely on for many, many different types of applications rely on that data necessarily being available in the warehouse because you're waiting for some ETL pipeline essentially finished to deliver it. But that could be represent like a stale representation in the world by that point. Whereas if I shift that problem sort of left to the operational state and I have an application store that I can essentially have that context available to me, then I don't have to wait for that pipeline to land in the data warehouse or even reverse ETL it out and stuff like that. So I think they're trying to essentially shift up the value chain to own more of the operational state so that they could serve these agent use cases.
- [14:33]
Gregor
Yeah, that makes a ton of sense. Yeah, in terms of that sort of on ramp into these larger data stores. That makes a ton of sense.
- [14:40]
Sean Falconer
Especially when you think of agents potentially spinning up databases for sort of short lived work. Because especially if like the context window has a certain limitation, I might want to dump some of that context into a database temporarily and then retrieve it later in the conversation. Especially when you start to get into these coding agent scenarios where they might need to have churned through a lot of code that could potentially represent too many tokens to send within one inference pass. But they want to cache some representation of it to still have it on hand and then maybe they throw it away at some point. Like are you going to really spin up an entire warehouse, do that kind of work? Probably not.
- [15:18]
Gregor
Yeah, that makes a ton of sense. Yeah, super interesting space. I say like postgres has just sort of come back. I don't want to come back with a vengeance. But it's always been a really great technology and I think often sort of under misunderstood as to the power of it over say just a basic, mysql database or indeed MongoDB kind of had its time. I don't think MongoDB is having its time at the moment. I think a lot of people are becoming less sensitive to how and where they store the data. From a dev perspective, when you've got things like Sippabase and I assume people like Neon kind of taking care of a lot of the bits of postgres that was a bit annoying, things like migrations, when that's all kind of taken care of, then actually the underlying technology feels more powerful than perhaps what MongoDB can ultimately give you. Unless you're always running on MongoDB's atlas. And that is expensive. So it's kind of interesting.
- [16:11]
Sean Falconer
Yeah. And also the relational databases have adapted to support a lot of the things that you liked from the NoSQL databases. Like a MongoDB where you have like JSON representation.
- [16:20]
Gregor
Exactly.
- [16:21]
Sean Falconer
But then you can query against it and actually Oracle, I forget what they call it, they have a new functionality where essentially the JSON NoSQL representation is almost like a view on top of the relational database. So you can have both essentially within one database. So there's been a lot of innovation that's happened in the relational world to adapt to those demands. So then it becomes just a feature, essentially.
- [16:46]
Gregor
Exactly. MongoDB was kind of, hey, we're JSON. You just dump JSON in and look at a database and exactly when that stops being a unique feature, as you've called out. Yeah, their moat kind of shrinks quite dramatically. And it's interesting that MongoDB have basically just decided that their whole business is just around the hosting effectively and just trying to drive people to Atlas. So yeah, interesting space. So thanks for highlighting that one. We'll watch along and just sort of see how those products integrate or potentially don't. That's always the interesting part of acquisitions. This episode of Software Engineering Daily is.
- [17:22]
Sean Falconer
Brought to you by Capital One.
- [17:24]
Gregor
How does Capital One stack? It starts with applied research and leveraging data to build AI models. Their engineering teams use the power of the cloud and platform standardization and automation to embed AI solutions throughout the business. Real Time Data at Scale enables these proprietary AI solutions to help Capital One improve the financial lives of its customers. That's technology at Capital One. Learn more about how Capital One's modern tech stack data ecosystem and application of AI ML are central to the business by visiting capitalone.comtech so moving on to kind of our main discussion topic for today, which is just quite frankly like the state of being a Developer today with the tools that are available. And I think we're talking a lot here about especially cursor, but also the others, things like Windsurf and bolt, new, etc. And certainly the last month, but I mean, last couple of months things have really been on a tear in terms of the advancement of these IDEs. And yeah, I think it's just sort of a good place to take a minute and see why are we even here and how are we kind of feeling about this as developers. So, yeah, I mean, I guess what's been your experience so far, Sean, in terms of any of these tools and sort of how far back does that go?
- [18:45]
Sean Falconer
Yeah, I mean, I primarily use, I do have cursor and I played around with it a bit, but I don't use it sort of day to day. I think if I was coding all the time, I would 100% be using these tools. So for the amount of coding that I do, which is more sort of at this stage of my career, proof of concept, demo, sort of vision stuff, I get away with using Claude or directly or chatgpt and stuff like that to help me write some of those things. And like, the efficiency gains are massive. And this goes beyond coding. I think you're doing yourself a disservice if you're resistant to these tools because they are massively efficient. But my perspective on this has always been that developers, engineers are paid what they're paid essentially to solve problems. And I don't think these tools, at least as of yet, really solve the problem for you. You have to direct them to solve the problem. So you're still doing the problem, but they can help you implement essentially the solution much, much more efficiently. So I think that it gives an opportunity for junior developers to contribute faster and senior people to probably avoid some of the more tedious work by offloading some of that stuff to AI. And then I think when you get into stuff like PR reviews, which are now also seeing levels of automation, there's things around people trying to do stuff with like sres and stuff like that. Those jobs don't necessarily go away, but they help, I think, fix some critical issues, like with PR reviews, I think a lot of people don't enjoy that experience. I remember when I interviewed the CTO of sourceforge, the biang, he said that no one's ever been promoted for giving a great PR review. So it's not necessarily something that everyone enjoys spending their time on. They would rather be coding and contributing in that way. Then I think with SREs I don't think anybody loves getting waking up at 2 in the morning because of page and then sort of starting with a blank page other than the fact you have an alert. So if you can have something, help do some solutioning, gather some material, even figure out do I need to wake this person up or not. That seems hugely valuable to me.
- [20:47]
Gregor
Yeah, definitely. Yeah. I mean I think on my side I guess I'm coding most days and yeah, I mean certainly I was one of the I guess first pretty early to say copilot INSIDE VS code and I think most developers would look back on that and go yeah, that was interesting but there was just a lot of not terribly smart code coming out of that. But that was obviously super early days. Now I started using cursor maybe back in November, December and yeah, I think the tedium was the thing functions that you just kept rewriting and front end work is actually a lot of where I kind of put it to work to begin with because I didn't fully trust the backend logic could be I guess I just didn't want to trust it to that. But on the front end you can kind of see is this what I was trying to achieve and the stakes are just much lower in terms of how bad can this be again? So long as you've kind of set things up in such a way like oh I choose Svelte and Sveltekit. I don't particularly want Cursor to kind of decide for me is this going to be like a react app or something. And then yeah, fast forward to certainly the last month and I'm just kind of a little bit blown away by actually just the sophistication of the sort of solutions it comes up with. But we are still talking sort of a ten shot, if you want to call it like a ten shot process here where I can go from zero to having a fairly meaty feature implemented within one if not like max two days and that's it. It's just kind of overseeing a 10 shot process and there it is. But as you call out Sean, it's about giving it the direction of what you're trying to achieve. And even small things where I say well actually we want this data cached locally and then its approach to local caching, well, you kind of have to tell it do I want this in local storage or do I want this in indexeddb for example. So yeah, there's still I think coming back to the kind of the junior developer point, yeah, there's still a lot for Junior developers to be able to learn here where they still are going to have to learn the approaches that make sense, even if they're not potentially learning, if you want to call it the hard way, the code that actually had to be written to achieve this.
- [22:46]
Sean Falconer
What's your perspective on if everybody can build some of this stuff or build some level of it where they don't necessarily need to understand quite as many of the nitty gritty details, they just need to understand the direction or the outcome enough to be able to direct the IDE or the model to essentially generate something that's going to be correct. How do you feel about that in terms of an impact on overall state of developers in the future? Are we reaching a place where no one's going to understand sort of what's happening undercovers and it's all about prompting in some fashion?
- [23:21]
Gregor
That's a great question. Yeah. I can give what I think and feel at the moment, which is obviously one very small perspective. I am concerned that developers kind of into the future are not going to be able to potentially problem solve quite the same way. Because I guess I'm concerned that coming to it now feels just like I just want this feature without really understanding. Right. But how does this feature, how should it work ultimately? I mean, the local caching thing is, go back to that example, you know, if I had implemented this feature without ever having coded anything in my life, I would have been like, oh, this is great, it does the thing, it pulls the data, presents it on the page, boom, done. And actually the experience is made immeasurably better because of local caching. Now I'm still trying to get my head around at what point will a new sort of new developer coming in, where will they learn these concepts? Is it just through pure curiosity? I do hope it's that where the tedium of coding stuff that was just kind of grunt work, I hope translates if you take that away, I hope that translates into people taking that time and going and being able to kind of really study up on the concepts that they're trying to sort of achieve with and I guess sort of have a larger breadth of knowledge across coding generally than they might have been able to. I think we're kind of probably going to see the end of, oh, I'm front end, I'm back end. I mean a lot of people of course said they're full stack for a long time I'd have often argued and before these tools that full stack was still a bit of a. Yeah, I mean, but you're probably better at one than the other, aren't you, these days with something like Cursor, I believe Full Stack is a very credible thing you can probably see now.
- [25:00]
Sean Falconer
Yeah, I mean, I think they're really incredible at the front end stuff, and I think part of it is there's just a lot of reference material that exists on the Internet to train models on in relation to that. Like, I haven't tried this myself, but I suspect that if you wanted to try to, I don't know, build your own driver or, you know, something that was a little bit closer to the hardware, maybe they're not as successful there because there's just less references available for it. And it's not that they couldn't help at all, but you probably have to do a bit more work as the person to get them to do what you want. Whereas if you want to spin up a form using whatever React frameworks felt like, whatever Vue, they can jam that out pretty quickly for you. And I know a lot of people, like friends of mine that have always thought of themselves as backend developers are now contributing some UI in sort of their own projects and stuff like that, but that would have been too scary for them historically.
- [25:57]
Gregor
That's interesting. Yeah. Again, set up the project with the framework, for example, on the front end. Got svelte, Sveltekit, tailwind. I then add in a component library, Daisy ui. And once you've got all that kind of decided, then Cursor, for example, is pretty good at then just cranking out exactly what you intend. You can still sort of say, hey, make it more elegant, literally. And off we go. It becomes more elegant, I think, on the backend. Yeah, it's a good point. It's definitely where I put more caution when it comes to just letting it kind of do its thing. But again, I think if you set up your project with tenets, you know, for example, as I mentioned previously, using Supabase, I wrote like a little middleware piece that would sort of always understand who the user is and deal with that kind of off piece. Now, Cursor always wants to go off and do like an admin call to Supabase and I'm like, no, no, no, you got to use the helper. And I know in Cursor you've got rules and you can sort of set that up and tell it to always use these things. But. And I think this is the big but. Back to your question, sort of junior developers, I'm not clear and sure at what stage a new Developer will learn. Why shouldn't I be always calling the database with the admin keys, which is unfortunately the default, it seems like. Unless you set it up otherwise.
- [27:10]
Sean Falconer
Yeah, I mean, I think the counterargument is that people have been concerned about that ever since we've been moving to any sort of higher level of abstraction. You know, there's some. Back when people started writing C, you know, there was assembly, developers were shaking their fists at these newfangled kids writing things in C and they'll never understand how to, I don't know, move memory between different areas of the cache manually or something like that. And then from there, you know, C does Java. And then people said the same thing about Python or even moving from using Emacs and Vim to ides like Eclipse and intellij and stuff like that. People have. And then we've had things like IntelliSense or code completion and all these types of tools, and with each iteration people have complained about the same sort of thing. As far as ACDELA hasn't destroyed too many countries and civilizations and people's careers so far. So I think the argument, I guess, is this is just another version of that is just a huge step function in terms of what we've seen previously.
- [28:09]
Gregor
Yeah, absolutely. I mean, to kind of slightly wrap up just this bit of the discussion, there was a good. I mean, I think it's quite opinionated, but it was a good article by one of the guys at Fly IO came out Hacker News a few days ago and I think that it framed it pretty well, which was just sort of saying, look, if code is meant to be a craft for you, unfortunately the world just doesn't kind of operate like that anymore. You need to be a little bit less precious about the code that you're writing, unless it's a craft hobby project and quite frankly just kind of get the features done and obviously. Well, and I think that's where these tools do come into their own because a lot of development unfortunately is tedious and it's that stuff that we often have tried to avoid. And I'm sure quite frankly these tools can help more. I think coming onto the IDE point, generally you mentioned intellisense and yeah, I remember back in the day paying what feels like a lot of money for a JetBrains IDE. And now a lot of people migrated over to VS code for various languages, which obviously was open source or Quotes, open source and free. And now we're coming back to paying for ides and sort of. Yeah, what's Your take on that in terms of could open source come back again?
- [29:20]
Sean Falconer
I actually had a conversation about this this week at the Snowflake Summit. Someone brought this up and I think it's because Windsurf had a booth there. We sort of sparked this conversation. But I don't know in the long run, what is the future of these AI powered IDs as a business? I think there's huge value in them, just like there was with even the initial first wave of IDEs from 20 years ago. There's clearly value and in the early days of that value, people can charge for it, but at some point that becomes a commodity. And I don't know what the mode is for any of these particular IDs. Like, do all of them sort of become similar and one person can. You can switch between them and there's not really like a stickiness to it. And overall, dev tools is a hard market to make money in, period. Because developers don't like paying for those kind of tools. That is just sort of the tools of the trade of doing business. They don't mind paying for like infrastructure and hosting and things like that. But in terms of helping me write my software, people don't generally like paying for a lot of those tools.
- [30:24]
Gregor
Yeah, definitely. I mean, at the moment, Cursor Pro is about US$20, which seems very reasonable, quite frankly. I've had a quote from a good developer friend saying they would happily pay $200, not $20. I really hope they don't put up to $200, but I could see a world where versions of Cursor potentially cost that and businesses will pay for it, quite frankly, if the efficiency gains are there.
- [30:48]
Sean Falconer
Yeah, that's true. I mean, even if you look at something like ChatGPT, people are paying for that. And arguably the prior equivalent of that might have been like a Google search and you paid for it, but you paid for it in terms of like your ad clicks. So it's a different business model and maybe we're entering a new wave of business models where people are willing to pay these for these premium services that are ad free and so forth.
- [31:14]
Gregor
So yeah, that's kind of the state of, I guess, being a developer at the moment. We didn't, I guess, particularly touch on tools like Windsurf and Bolt New. Just a very brief. My take on those are maybe that they're a little bit more in that vibe code category, perhaps more people that wouldn't have maybe normally coded. And this is how they're kind of on ramping to that, but I no doubt we'll see some sort of developments there. I mean, I'm aware that Bolt news technology behind the scenes is pretty cool because they do a lot locally basically, and that's how they're able to run it at cost that makes any sense for anyone. I don't think that's the case with Cursor where obviously you're literally choosing Claude 4 or whichever, and that's all being run by them, which is probably costing a lot of money.
- [31:56]
Sean Falconer
Yeah. I Wonder what the CAC to LTV ratio is with this $20 a month.
- [32:02]
Gregor
Yeah, I'm genuinely a little bit concerned that that's just not going to hold. But I mean, even if they doubled it, I think it's absolutely still worth it. I think. Just. Does it ever reach something like 200? I think that'll be a question mark. Let's move on to our next regular segment which is just taking a little spin across hacker news from the last few weeks. So Sean and I just like to kind of pull out a few things that have kind of popped up as we go about our daily lives. So, yeah, I might kick off with. There was a fun one called Japan's IC cards are weird and wonderful. And this caught my eye because I have traveled in Japan and I used to live in Hong Kong. And as I learned from this article that the technology used by the transport system, these cards, it's actually the same technology between those two places, which is different to how a lot of other countries have gone about their tap and go. And what I found kind of fun and fascinating about this was just that this is a technology I believe developed by Sony, but was not actually used in Japan initially. It was actually used in Hong Kong initially. And Hong Kong has this thing called the Octopus card. And the Octopus card was pretty much the first sort of mass adopted TAP transit card, but could also be used in like 7:11 to pay for things. The key thing to this technology that I wasn't super aware of was just that, you know, it's a slightly different standard of rfid and the key bit to it is speed. And this idea that, you know, these are very congested cities. If the barrier doesn't open within a sort of 10 milliseconds of you tapping that card, then you're going to have lots of queues in subway stations. Obviously I witnessed this firsthand in Hong Kong where people just don't even think about it. They just tap and they know the barrier is going to open instantaneously. So yeah, I hadn't really dived into the technology behind something I've used many times in my life. And this was a nice little article on that.
- [33:59]
Sean Falconer
Yeah. I think it's really interesting how because of the congestion and sort of trying to optimize for human flow, they had to essentially invest in this different way of doing those cards and using nfi. I think that's really interesting because if you're live in the US like I do, public transit only exists in like a handful of cities. In any of those cities it's not great typically. So there's not like a pressure to essentially really try to optimize these types of things. So they just don't. You end up with a version of technology that is inferior to what they're doing elsewhere.
- [34:34]
Gregor
Yeah. And it's funny because I live now in Singapore and they do have their own tap card system that was just for the subway and the buses. I never got that because by the time I moved here, like quite a few other cities, you can just tap your bank card or your phone with Android Pay and Apple Pay. The thing is that is definitely slower. I mean I put my phone next to the thing and there is always a bit of a kind of will it won't it open the barrier? Most times it does, but it is no way. The same reliability where you can just put that card and just walk at the barrier and know it's going to open. It's just not the same thing.
- [35:09]
Sean Falconer
You got to go full stop or you're going to crash into something essentially.
- [35:14]
Gregor
Yeah, yeah. And I mean Singapore is not as congested. So now that I know that it is categorically faster to use these cards that were developed by Sony, I think about every time I go through the barrier now. So yeah. What caught your eye on Hacker News, Sean?
- [35:26]
Sean Falconer
Yeah, so one of the ones I pulled, it was posted a couple days ago was this post about comparing the system prompts across different quad versions. And you can actually look up there's like a GitHub repo that will show you the full quad system prompt.
- [35:39]
Gregor
Yeah, right.
- [35:40]
Sean Falconer
23,000 tokens. It's pretty massive. But I think in this particular update a couple of things that was interesting was it shows how they're really using the system prompt to shape sort of how Claude acts based I think on what they're seeing from user behavior. So essentially in between training cycles with the model, they can release new versions where they use the system prompt to trick the model into doing the things that they want where they can set the tone, set the policy, the personality. There's some interesting things in there where they ask explicitly remove flattery in your responses so we'd be more direct. It's actually very similar to like a lot of the times the things that I put in as my prompt is like, stop writing like a marketing person and be direct and concise and stuff like that. And they use a lot of these kind of behavioral hacks in different versions. So in some of the old versions they had to do things to explicitly instruct Quad on how to do like word counting and how to avoid things like bad poetry. And then they've been able to improve the model through training to solve for those use cases and then they remove those instructions essentially in the prompt from the future versions.
- [36:54]
Gregor
Yeah, I saw whether it was this one or something similar. But yeah, I mean, there's the fairly prolific blogger who keeps popping up, Hacker News, Simon Willison, and he's written a bit about this as well. But yeah, pretty fascinating. I mean, I would say until two, three weeks ago, I wasn't even that aware of the fact that there was this massive prompt that is the model, if you know what I mean. Okay, you've got the data, but you've got this huge prompt that effectively is being run every time that you then add your prompt and so on.
- [37:21]
Sean Falconer
Yeah, it's going to eat up some percentage of the context window, essentially.
- [37:25]
Gregor
Exactly. Yeah. The thing I'm still trying to get my head around is just the temporal aspect of models and they seem, again, I'm talking, I guess, mainly about OpenAI's models at the moment, but finding that they just still struggle big time understanding the time. If I put something in and say the date is June 6, 7am right now, and then you give it some data and the data says today, but the date on it was yesterday. It still says today. Oh, today. Well, yeah, I think that's an interesting one where I'm curious if there's any models out there that are really tuned on the temporal side of things, because I haven't seen that in these.
- [38:03]
Sean Falconer
Yeah, I don't know. That's a good question. I'm not sure. I think some of that stuff is tricky, so it's not surprising.
- [38:09]
Gregor
A lot of mistakes, it's frustrating. But I also quite like the fact that I found something that it doesn't do very well yet and I find that kind of fun on how to try and solve that.
- [38:20]
Sean Falconer
Yeah, I found with certain models, a lot of times if you're asking for certain lists, certain models don't do A very good job of that. If you say, hey, I want 25 things that match the specific characteristic, the first like five, six, seven of them will be good matches. And then it starts to like slowly deteriorate over time. So there is some confusion that tends to happen with the models when they have to do, I think longer output or of course if you're throwing a lot of information at it as well, sometimes can lead to confusion.
- [38:51]
Gregor
Another just brief one that popped up, which is I think just also good as a sort of PSA for people to go and use themselves is have I been owned or pwned, however you want to say it. 2.0. So thank you to Lauren DB for posting that one. This is the service, have I been. I'll just say owned for the sake of argument. Have I been owned? 1.0 has been running for a long time. It's where if you are wanting to find out if your email address or phone number has been found in a hack, you can just pop it in and it's a free service to use for an individual. If you want to kind of run it on like a domain across your company, that tends to cost some money, which makes sense. And there's a very good API, but it hasn't really had any updates in a long, long time, as Troy Hunt, the founder, I Believe says. So 2.0 is quite a big deal. Yeah, certainly the UI has just had a major lift and sort of much more intuitive in terms of looking through what might have happened with your data. Just reading that I hadn't maybe appreciated. There are some hacks where in a good way, if you want to find out that you've turned up in this hack, they will email you the result as opposed to you finding your results publicly. And to be quite frank, the main one they should talk about, of course is Ashley Madison, which was a slightly controversial dating site. And that makes sense. You shouldn't really be able to just go and find anyone's email address and check if they were using that site and obviously got hacked. So yeah, I think it's a great service. And one thing they also talk about, they've dropped username and phone number searching, which is interesting because they just said it's become too cumbersome to kind of be able to run that reliably. So yeah, that's a sort of interesting update. So yeah, go check that out. And obviously if you have never used it before, always a good one, just to go and run your personal and work email through, just to double check if you've turned up anywhere.
- [40:40]
Sean Falconer
One thing they did talk about in the article about the new version of the website is they did a lot of AI use essentially to generate the front end.
- [40:49]
Gregor
Ah, yeah.
- [40:50]
Sean Falconer
Back to what we were talking about earlier.
- [40:52]
Gregor
Yeah, yeah. I mean, that would make sense. Just sort of sidebar. Yeah, I did a pretty fun thing which was new landing page for product I'm working on and I just had cursor look at both the back end and front end repos and I said, generate a landing page based on all the features of this product. And it was absolutely fantastic. So, you know, within one hour I had a landing page and within five hours I had a landing page. I was like happy to publish. So just incredible. So, yeah, it doesn't surprise me that they took that approach, which is pretty cool.
- [41:20]
Sean Falconer
Awesome.
- [41:21]
Gregor
Anything else from your side on Hacker News, Sean?
- [41:24]
Sean Falconer
No, I don't think so.
- [41:25]
Gregor
Cool. Yeah. Well, that was a nice little spin through things as we kind of wrap up and just look ahead in terms of normal programming. Yeah. I'm aware that we've got any on E Laptop episode coming up, but that's with Byron Wang and myself. This was a fascinating episode. I was alerted to Byron from Hacker News. I think it's the. We talk about it in the episode. It's the number one kudos of all time article on Hacker News, except for this other one that he highlights, which was it is technically number one, but it's only because the user had found a hack as to how to hack Hacker News and get it to the top. So Byron's is actually the real number one article of all time. It is a open source laptop and that might not sound particularly credible, but if you listen and potentially watch his video afterwards, just the level of detail and craftsmanship that went into this laptop. And as it sounds, it's all open source. It's a repo as to how to build this laptop. It's just incredible. And the kicker is that he's in high school or he's just finished high school. So. Yeah, so I think just can't recommend that one enough. Moving on. We're going to have, I believe, the challenge of AI model evaluations or evals with Ankur, Goyal and yourself, Sean. So yeah, what's that about?
- [42:47]
Sean Falconer
Yeah, Ankur is one of the. He's the CEO and founder of a company called BrainTrust and they're focused on how do you build evals essentially for gen AI applications and, you know, AI agents and so forth, which is something that a lot of companies end up kind of rolling their own solutions to that today. So there's this new crop of companies coming up, like braintrust, that are focused on solving this problem in a more systematic way.
- [43:11]
Gregor
Yeah, I'm going to definitely listen to that. I want to get a bit more up to speed on sensible ways to eval or use evals. And then we're also going to have back to some of our video game content. So we're going to have wayforward games with Tom Hewlett and Voldy Way, and that's of course, with Joe Nash. So, yeah, tune in for that. I don't think we've had quite as many video game episodes this year, so that's one of the next ones coming up. So, yeah, as always, thank you for tuning in to SED News. This will be hopefully a monthly installment, so just look out for us around the start of each month and catch up on what's been going on. But yeah, anything else you want to call out Sean, before we wrap up?
- [43:50]
Sean Falconer
No, I think we covered it all. So much going on in the world these days, it's hard to cover everything, but. So I'm looking forward to getting back with you next month.
- [43:58]
Gregor
Yeah, absolutely. As Sean says, far too much to catch up on, but we do our best to try and hit the high notes. Thanks again for tuning in and we'll see you next month.