SED News: Corporate Spies, Postgres, and the Weird Life of Devs Right Now

0:12Hello and welcome to another SED news. This is a different format of the SED 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. 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.

0:46Yeah, exactly. Exciting. So thank Thank you to the listeners for listening to it enough. That means that this gets to continue. 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? 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.

1:15I 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 a hundred 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. 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.

2:09And we're also going to be looking at Databricks and Snowflake. So we might kick off with Dillon Rippling. Yeah, it's been a funny one going on there. Have you been following along with any of this, Sean? 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, like, 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. Yeah, so this came up on my radar about two weeks ago, when effectively an employee that is supposedly a Rippling employee.

2:43And 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 a sort of slight more cachet, if you like, to give it that. The CEO was the ex-Zenefits CEO. There's a whole bunch of drama there, and we can always vaguely talk about why this also plays into it. But yeah, you know, Rippling, if you're in the US, you probably know a bit about Rippling. But if you're not, then it's sort of you get to just white glove, have someone onboard all your employees, whether it's through the IT system or through payroll.

3:17They'll even like deliver a laptop to your employee, like preloaded with all the necessary security and software, etc. So very cool platform and sort of service. deals kind of the same thing but i would say there may be a little bit more kind of on the in theory so the steady as you go 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.

4:01So proper spy novel stuff. Were there any smoke bombs or anything like that? 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$5 ,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 dealers under fire for this like corporate espionage etc and feels like an hr violation right yeah i mean at the very least yeah and then we've got deal counter suing 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 all kind of unravels a little bit for the deal side because i think sean it's fair to say that this is just the pretending to be a customer That's been part of the playbook in tech since forever, right?

4:52Yeah, I mean, I think that even if you look at some of the stuff that was going on and sort of the heyday of the Uber, Lyft, rideshare wars, there was a lot of, I think, or at least I heard, 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.

5:24Like I actually there was a podcast I listened to a couple of 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 L.A. 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.

5:55It was a 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. 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 four deal in theory, it was something to do with Slack channels was kind of what gave the whole game away that they'd sort of, they set up within Rippling, they set up a honeypot Slack channel, but then that sort of got that person in there.

6:32And 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 ex-Zenefits CEO. There was a ton of stuff that went on there and two sides to every story. That place was Scandal Central. Right, right, exactly. Scandal Central. And yeah, Parker Conrad, that's the CEO of Revelling Now, he's come out in public before this landed, you know, to tell his side of that story. And, you know, sure, there are always two sides of every story. and YC, 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.

7:14But 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?

7:45Well, I guess we'll find out. 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. 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? Yeah. So as I was saying at the start of this, 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.

8:21But 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 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 acquire one of these companies. The other one got wind of it 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.

8:56And then Neon's like about 140 employees. Crunchy around 100 employees. I'm not sure of 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.

9:35Snowflake 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 like 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 like analysts and certainly in the database world, maybe you have a data scientist and so forth. and then the people who are building applications are building on sort of traditional application database and stuff.

10:07So 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 like AI agents. So agents need both essentially historical data that maybe exists in the 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 you have the agent sort of operating in a customer facing application, you're probably not necessarily going to be reaching back to these like massive columnar stores to pull that data.

10:43It 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 of 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.

11:19So 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 to do that. I actually wrote an article about the sort of Databricks neon agent connection a couple of 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 of weeks of each other from two of the major data companies.

11:55Yeah. 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 Superbase. 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 like 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 get also get onto this in the main topic in terms of ai coding tools and they're basically just spinning up instances of super base and a lot of the users don't even realize that's kind of where the data is living is there any sort of part of that in this as well just when you talked about agent is it sort of that side of things?

12:58Or is it more directed, you think, by the user, they kind of know that they're using Neon or Crunchy data? I wouldn't be surprised. I mean, I think that if Superbase is getting a lot of traction there, I'm sure the powers that be that 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.

13:34AI 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 to essentially finish to deliver it. But that could represent like a stale representation of the world by that point.

14:08Whereas 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 like reverse detail it out and stuff like that. So I think it's, 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. Yeah, 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. So especially when you see the thing of like agents potentially spinning up databases, for sort of short-lived work.

14:46Because 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, you know, 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 to do that kind of work?

15:16Probably not. Yeah, that makes a ton of sense. Yeah, super interesting space. I say like Postgres has just sort of come back. I don't know if it comes 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 Superbase. 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.

15:56Like when that's all kind of taken care of, then actually the underlying technology feels more powerful than perhaps what like MongoDB can ultimately give you. Unless you're always running on MongoDB's Atlas and that is expensive. So it's kind of interesting. 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 JSON representation. Exactly. 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.

16:34So 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 exactly mongodb was kind of hey we're json you just dump json in and look at the database and exactly when that stops being a unique feature as you've called out yeah their moat kind of shrinks quite dramatically and as sort of 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.

17:08So 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. 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 We're talking a lot here about especially Cursor, but also the others, things like Winsurf and Bolt.new, etc. And certainly the last month, but I mean, the last couple of months, things have really been on a tear in terms of the advancement of these IDEs.

17:45And 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? 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 ChatTPT and stuff like that to help me write some of those things.

18:30And 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.

19:11And 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 B.A. 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.

19:45And then I think with SREs, I don't think anybody loves getting waken up at two in the morning because of the 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, like, do I need to wake this person up or not? That seems hugely valuable to me. Yeah, definitely. Yeah, I mean, I think on my side, I guess, yeah, I'm coding most days. And yeah, I mean, certainly I was one of the, I guess, first pretty early to, you know, say copilot inside VS Code. And I think most developers would look back on that and go, yeah, that was interesting.

20:20But there was just a lot of not terribly smart code coming out of that. But, you know, that was obviously super early days. Now, I started using cursor maybe back in November, December. And yeah, I think the TDM was the thing, like 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 back end logic could be, I guess I just 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 there's just stakes are just much lower in terms of how bad can this be?

20:51again so long as you've kind of set things up in it in such a way like oh i choose svelte and svelte kit i don't particularly want cursor to kind of decide for me is this going to be like a react app or something yeah 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 of the sort of solutions it comes up with but we're still talking a sort of a 10 shot if you want to call it like a 10 shot process here where i can go from zero to having a fairly meaty feature like implemented within within one, if not like max two days.

21:24And 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, you know, small things where I say, well, actually we want this data cached locally. And then it's 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 IndexDB, you know, 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.

22:03What'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 kind of 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. But how do you feel about that in terms of an impact on overall state of developers in the future? Like, are they really, are we reaching a place where they, no one's going to understand sort of the what's happening under covers and it's all about, you know, prompting in some fashion?

22:39That's a great question. Yeah. I mean, 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'd have been like, oh, this is great.

23:12it does the thing it pulls the data presents 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 you know where the tedium of coding stuff that was just kind of grunt work i hope translates if you you know 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.

23:51And 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, you know, 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 yeah 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 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.

24:44And 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 frame or it's felt, whatever view, 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 back-end developers are now you know contributing some ui in sort of their own projects and stuff like that but that would have been too scary for them historically that's interesting yeah you know again set up the project with the framework you know for example on the front end got svelte svelte kit tailwind i then add in a component library daisy ui and once you got all that kind of decided then cursor for example is pretty good at then just cranking out exactly what you intend.