Railway: The Agent-Native Cloud — Jake Cooper

Conductor of Railway. Conductor of Railway. Choo choo.

Choo choo. Do you actually have that, like, anywhere on, like, your Well, we, like, we roughly call, like, people into well, I don't have a business card. We're not we're not that big yet.

At some point, I will. I got handed a nice business card from the super micro folks, I was like, damn. That's actually, like, pretty official.

They're coming back. Cards. Yeah.

They're they're cool. They're hip. They're jiggy.

But yeah, the the whole conductor thing, like, call some of our volunteer moderators, conductors, you know? Yeah. So it's a good one.

It's a good one. Like, we're trying to figure out what we want to call each other internally, and there's like varying levels of thought. Some people are like, oh, it's super cringe.

Like, just don't like, you don't need a name for, like, you know, people internally. And some people are like, oh, yeah, we want to call each other, like, this thing or whatever. I was like, we still don't have a really good one.

You know? We've got like we've got like new rail crutes. We've got like trainiacs.

We've got like nothing's like really I like trainiac trainiacs. Yeah.

Okay. So, well, for those who don't know, what is railway? Let's give people a crisp definition up front.

Yeah. Railway is the easiest way to ship anything. You just go to the canvas or you talk with Claude and you say, deploy Postgres instance, deploy my GitHub repository, run this code, etcetera.

Right? And you'll just be up and away to the races. Right?

Yeah. You do a nice animation on the landing page. Oh, well, thank you.

Yeah. None of my work, by the way. They they don't let me touch any of the design stuff anymore.

But, yeah, we wanna make it trivially easy for not just to, like, deploy things, but for you to almost, evolve applications over time. Like, we believe that most of the tooling right now is kind of, like, stacked up. Like, you're stacking Entropy on top of Entropy on top of Entropy.

Right? So you have like Docker and Cube and then like Ansible scripts and all of these other things. Right?

And if we can kind of like version all of your software for you and keep track of all of the changes, then we can make it actually trivial for you to clone environments, you know, fork into a parallel universe, get copies of like production data, get copies of like any of your services, make those changes, validate those changes, collapse it in without kind of having to just like reproduce everything across a, you know, a staging environment or all of those other things. Right? So Yeah.

Amazing.

What prepared you for Railway? It's almost like a curiosity to just, like, ever go deeper. Right?

And so, like, you know, started out on, like, front end stuff, you know, like working on the, like, Wolfram, like, web mathematica and, like, porting it over there. And then, you know, briefly moving to Bloomberg and then moving towards Uber and, like, distributed systems and kind of, like, taking all the jump bikes kind of systems and and moving them over to a distributed system built on top of Cadence, like the pre temporal. Yeah.

Pre temporal. Which, by way, I'm happy to talk about pros and cons. Yeah, I think like it's like- do the Totally.

Throwaway And so like, it's just been a continual step of like, I want this experience, whether it is like walking up to like a bike and just unlocking it and like having it be like frictionless to like work or whatever. And then like necessitating the like depth required to go in and make that happen. Right?

Like a lot of the work that I do and a lot of the team does is like, it's all in service of that experience. Right? And like, we fundamentally don't care like how deep we have to go, whatever.

Like, we will swim to the bottom of the swimming pool to go and get the experience. Right? And I think that's what a lot of, you know, kind of the trajectory was.

Right? And so it's not like I have a physics PhD or whatever. I did like an ECS degree, you know, it's just, it's always been about just trying to figure out that next step of like, how do we get there?

Right? And that's like what's led to, you know, starting Railway for that experience and then like moving all the way to bare metal data centers. Right?

Like, you know, was adding patches to the kernel this week, right, just to like get the experience there because I'm like, I see it and, like, how much better it can be. Right? You added patches to the Linux kernel this week?

Yeah. Well, not upstream. That's a flex.

Our our Railpack? No. This is different.

This is the op OS on top of Railpack. Yeah. No.

This is, like, this is the actual kernel, like, patches. But it's it's always literally just what do we have to do to get that experience and just like figure it out. Right?

Like anything is figureoutable. Right? Like, you'll just figure it out, you know?

Would you send the patch upstream or is it just because like it doesn't fit for the Maybe. It's like we have to we have to work out the experience for us internally. It has to do a lot with the, like, storage layer that we're building for some of the agentic stuff.

So maybe it'll be useful to to people upstream, but it's deeply useful for us internally. Yeah. Mean, you mentioned open source before, so I'm just kinda curious about how you think about starting from open source and then coding agents let you do a lot more from forks of it.

I think the it's funny because like, I think GitHub's original sin is that it's like almost a series of broken pointers. It's like you have essentially this thing, and then you clone it, and then, okay, great. Like, I've just lost that whole upstream.

Right? How do we make it trivial for people to modify really, really small pieces of it? Right?

And you like, you think of of Git almost in this like discreet sense of like, I've either made a change and I've merged upstream or I haven't. Right? What would it look like if it was like percentage based or a little bit more nondeterministic or anything else like that?

More of like a stream of changes that you kind of like traversed as a user, more as kind of like a a percentage of this is rolled out in general, and it's been rolled all the way up. Right? You know, we have the open source like Kickback program and allowing you to deploy those templates because we almost wanna make it trivial for people to like go and version these shards over time.

It solves like a really, really large problem in terms of authentication authorization, security. Like, you know, NPM has that thing where you can almost define, hey, don't take any new packages or whatever. Like, the ideal end state is actually like, you should roll out progressively to the users who have the minimum impact zone for any of these things and just continually roll up.

Right? Like JP Morgan or something else like that should probably be the last one on the patch line for that. Right?

For all of our sakes. Right? Like, because we have all of our, you know, money, our lively, all of those other things.

It's okay if like Johnny Vibe Coder gets like a broken patch or something else like that, because ultimately there's so much entropy in the system that do have to roll like rubber has to be rode at some point. Like, you have to test at varying levels. Right?

So, yeah, a little diversion from wherever we started, but, you know.

or number of Daily sign ups, I think. Daily sign ups? Yeah.

and Yeah. Like, a slow grind. Slow grind?

Yeah. And now now, obviously, you're on a rocket ship. You say, don't doubt your vibe and don't quit.

But, like, maybe if you wanna pick out, like, certain points that were, like, sort of key inflections of the company that that might be fun. Oh, yeah. Yeah.

Yeah. Well, I mean, at the start, it's basically like, how do you get your first 100 users, like, or high water? Right?

And so, like, starting in you know, we had a website and we had a support link, and the support link was the Discord channel, and you just showed up there, and I had notifications on. I had two monitors. I had the monitor I was working on, and then I had the other monitor.

And if anybody came in, I was like, oh, hey. How's it going? Like, know, it's like and it was, like, super rare or whatever.

So trying to get those initial, like, first 100 users to, like, actually kinda come back to it. And that's, I think, where you can kinda, see the really, like, in between January 2021 and 2022, like probably the middle, like, there kind of, right? And that's like the start.

And then you ultimately end up building a consultancy factory of like users wanted all of these things in general. And so you kind of have to go back to the board a little bit and be like, well, what is the actual product offering that I want to build on top of these? And I think like incidentally, it's funny, like, I think VCs really want like charts that like always look like this or whatever.

Right? But I think in reality, you actually don't want charts that look like that. Most companies, I think, or at least for us, there's been periods of like expansion of like, oh, okay, we're going go and add these features to like go in and test these use cases.

And then there's been periods of like compaction where we're saying like, okay, how do we have, if the experience we have is really, really good, do how we make it significantly better? Right? Like maybe we're even stripping out features that don't like fit our ICP anymore.

Like, how do we go in and do that? And I think throughout this whole chart, you can see a lot of those things. Like the boom in the like 2022 to 2023 is like we had a free tier and like everybody under the sun was like using it and and all these other things.

A lot of Reddit bots and stuff. Yeah. Right.

And and like, I think there's a there's a thing that's really, really tough to like teach people or tell people about is like when you build an open product on the internet where anybody can sign up, the internet is a horrible place that has like so many things like- Oh yeah, people told you about my PC. Yeah, like we got PC and Triad. And crypto nessus.

Crypto miners, you got like all these other things, right? And so you kind of go through these periods of like, well, how do I reach as many people as possible? And then like, how do I fit in exactly the use case for the people who are really, really gonna matter and who are gonna be really, really excited about specifically this thing.

Right? And we go back and forth internally. And then there's like a, what is that?

A two year period of like making the actual business work in general. Right? So like free tier era, losing, what, I think half $1,000,000 a month.

And like, you know, we're making On like a 20,000,000 bank account. Yeah. Yeah.

On like a 20,000,000 bank account with like, I don't know, like maybe $50,000 a month in revenue or something else like that. Horrible business. I don't know why I animated my best.

But anyways, you have to kind of go through and be like, cool. Like, we have an experience that people love in general, but like the business has to work. Right?

And I think there's there's like, I guess, two schools of thoughts. You you can continually run the horrible business all the way up in in general and and have bad margins, or you can actually go in and go back and kind of make it work. Right?

And for us, you know, we've always really wanted to have like a super lean team. Right? So we're 35 people right now.

You know, it's very, very small. We have like what, 3,000,000?

Because we're adding like a 100,000 users a week right now. Right? So it's like, it's growing really fast.

Right? But we've always wanted to have a really, really lean team. We don't wanna just add headcount for the sake of headcount, just throw bodies at these problems.

We wanna build systems. Right? And it's really, really hard to build systems when you're kind of in that expansion phase because you're just adding stuff to system in general because people are asking for it or things are breaking in general.

Right? We basically were like, all right, like, you know, we're gonna we're gonna cut it for now. Like, we're just we can't support this, like, these free users that, like, we want.

Like, we wanna reach as many people as possible because we believe that, you know, software is this really, really important thing where if you can kind of, like, create something, it's become really difficult to create things in a physical world. So it's really important to make it really easy for people to build things in a virtual world so that people have access to creation. Right?

And so we wanna reach as many people as possible, but there's kind of like legs on that journey. So we basically had to kind of close off the the free free kind of users for a little while, rebuild the business, make sure that it worked in general. Right?

And then I think you can kind of like see the building of that in general. Right? And then I think you you see kind of some divots in those charts.

Right? Like, if you actually follow between, I think, 2025 and 2026, it's either summer or winter. That's basically it.

Right? Like, where either people go on holidays with their family or they go on holiday. Oh, it affects that much.

Yeah. Yeah. Well, because it's like, it's kind of B2C.

It's kind of B2B in general. Right? And so you have a lot of these users where, like, they're shipping constantly and then, you know, they'll kind of like stop or whatever.

Right? And so maybe for summer, like maybe like our activation curve is like, now we see a lot of people like activating the weekday, right? Because we have a lot more like business users in general.

So that gets a lot less sheer, so to speak. Right? And it kind of like smooths out over time, you know?

Yeah.

I think like we've, so we've prioritized almost like AgenTic as, like, a top of funnel thing. And probably over the last six, six months, we've probably deeply prioritized, like, AgenTic as a as a mechanism to go and build and and deploy things, just because we we believe fundamentally, like, the the curve is so sheer, and, like, that is the way that people are gonna go and build and deploy software. And it it almost, like, fundamentally doesn't matter if it's if, like, this is .

com or not because we're all on the Internet now anyways. Right? And so if agents are gonna go and deploy a bunch of things and we hit an inference wall at some point, then, like, at some point, we will go in and fix those problems.

But, like, that will be kind of the dominant species over the next, like, ten years is is we've moved from Assembly to C to C plus plus to JavaScript to now, like, Words. Right? And you're gonna need be able to close that loop.

Right? But that's where it goes. You know?

So When you say this is .com, do you mean, like, buying the domain? Or No.

No. No. No.

I I mean, like, actually, just, like, you know, they had a bunch of run up in the .com era for companies because they were like, the Internet is really, really important. And then you hit kind of like bottlenecks, fundamental laws of physics, math didn't work, all of those other things.

And and everybody kind of like, you know, went back down to the earth. Right? But at the end of the day, didn't matter because the internet is like so, so impactful for our lives that if you operate on a long enough time horizon that you should be, like, you should just build these things anyways because you you can see where that's going.

Right? And that's where I fundamentally believe a lot of the agent stuff is. Right?

And we can talk about it a little bit of it later, but you're gonna get to a point where you're running thousands of these agents, like, in parallel. Right? Like, one, what's the inference cost for that?

What's the compute cost? How are you gonna make that efficient? All of those other things.

But, two, do you go and coordinate all this stuff? Like, we had it we have we have issues coordinating humans in in in general. Right?

We don't even have good tooling for that. And now we're starting to to figure out, it's like, oh, like, how do get agents to coordinate? How do you go in and get them to be able to, like, safely version changes or or, like, for them to know when to, like, put their hand up to get somebody to intervene.

Right? Otherwise, it just becomes like an interrupt factory that's, like, crazy, you know? Well, so maybe we'll go right on the technical side of things.

Yeah, yeah. What are the core, like, infrastructure or architectural beliefs of RealWait that allow you to do what you do? Yeah.

I think the the primitives matter a lot for us, like a lot, a lot. We need to be able to do network, compute, and storage, and orchestration all kind of around it. You kinda need control over a lot of those things.

Like, we've talked a lot about, like, how we don't really use Kube, like Kubernetes, because we want the higher order of control to be able to, like, go in and place workloads in very, very specific places. Right? And the reason for that is, like, you know, it's kind of the thing we we talked about previously, but, like, you have to be very, very efficient with these agents, like memory reuse, all of those other things, or you're gonna massively, massively blow up your cost structure.

Right? I think also, incidentally, being able to rack and stack your own servers and and build your own metal, it unlocks a level of like performance, one, but like two, cost where you can say, oh, those experiences that you wanna offer where you're running a thousand agents in parallel are not like massively cost prohibitive. Right?

Because like, if you look at just like token use right now or compute use or anything else like that, those things are blowing up massively. Right? Over time, those things are going have to get a lot and lot more efficient.

You can get a lot of almost like back of the napkin balance sheet margin, whatever you want to call it to kind of make those experiences, like, solid by building your own metal, right? And so, kind of to the earlier point of, like, we've always tried to go a little bit deeper every time to make that experience. It's all in the service of offering that differentiated experience to as many people as, like, humanly possible, you know?

Yeah. You have a data center in Singapore. Yeah.

So we have two in every other region now, Singapore. We're adding a second one in Q3. So, yep.

So, like, what's it like? I mean, I've never built a data center. Yeah.

Then we'll have to, like, It's go to one or go to, Equinox and say, hey, I want some Yeah. Yeah. So so yeah.

Mean, I can I can bring Equinix? Equinix. Yeah.

Yeah. Equinox. I mean, you should also Equinox for your body.

Equinix for your software. I mean, you can put a you can put a data center in the steam room and get nice and hot or whatever. But, yeah.

Yeah. You basically just go and you say, hey, listen. I want power, and I want a cage.

And they're like, great. Here. This is what it's gonna be.

And then you rent the cage for a period of time, and then you have to fill the cage with racks, servers, and then hook up Internet to it. Right? That's realistically all the And then you handle everything else.

Right? Yeah. You just handle everything else.

Right? So And, like, what's the math versus, obviously, the clouds? Yeah.

They're good for you. Our our payback period when we go to to Metal, if we rent it in the cloud, our payback period is about three months. It goes crazy.

It's nuts. Yeah. And that's like four years worth of like depreciated hardware.

Right? And so I think it's like, you're gonna see a lot of this almost like compute crunch, so to speak, because a lot the hyperscalers are buying up a lot of stuff. Like, we're working directly with OEMs and, like, resellers and and, like, directly with people who are, like, building these machines, like Super Micro, Dell, all of those other things to go in and get these things things working.

But, you know, upstream, there's, a bunch of supply stuff. You know, we it it was funny because when we raised our last round in between basically deploying the capital for the servers and actually, I think even even now, the amount of money that we've raised is less than the amount of money that we have in the bank plus what the value of the servers are because the servers have actually appreciated in value because RAM has gone up in general. Right?

So it's kind of nuts just in terms of like how valuable hardware and all of this stuff is. Right? And if you look at especially a lot of that, like hyperscalers, like what they deployed, like $80,000,000,000 of, like, capital expenditures, like, this year and and, like, into next, it's gonna be, like, more in in general.

Right? There's a massive, massive scale, like infrastructure build outs. And you can look at that by like, wow, that's crazy.

They're spending, like, way more than the Manhattan Project. But, like, again, if you go back to every person is going to run dozens, hundreds, whatever of agents in parallel, You should spend more than that.

like, we still maintain like cloud presence for like bursting essentially. And so what we can do is, you know, we work with AWS and GCP and a few of those, you know, other clouds, like we can just rent. And then the moment we kind of get space or power or whatever, you almost just like compact those off the cloud, right?

Like we, because we started on the clouds and then we built a system to allow us to migrate to our own metal. And so there's nothing that says you can't just continually do that again, which is exactly what we do right now. Right?

And so we never want to be in a spot where essentially we are, you know, compute constrained. Right? And at the start of the year, like we actually got to a point where we were compute constrained because the one upstream provider that we were actually working with wasn't able to give us quota at the rate that we needed to.

And the hardware was like slower. Right? And so we had to do a bunch of different stuff.

I spent a weekend rebuilding our entire network overlay essentially so that we could straddle five different clouds. Right. Yeah.

Oracle, AWS, ourselves, GCP, and like one other one, right? And we can do more than that now, right? But we got into a spot where like, we were just trying to like pack instances tight because we couldn't get the amount of compute that we needed.

Right? And it was really unfortunate because as a result, like some of we had a few like reliability kind of things, which are now kind of past us, but it was all a result of this kind of like, there's a tweet that I made where like, you know, I've I like gotten in trouble because I was trying to point it out, but I accidentally caught this super bass folks in the crossfire. But like the tweet was about there's it's really, really difficult, and it's gonna become more and more difficult to acquire compute at the rate that these models need to acquire compute.

Right?

And so we can actually deeply subsidize the cloud business if we want to scale at a reasonable rate. And so we have a few different, like, actually very fun from, like, an operations perspective because you have a few different levers on how you can go and scale it. Have, like, the metal which actually, like, makes your margins.

You have the cloud burst, etcetera. You have debt you can use to, like, buy servers in general. So it's a very interesting, like, operational, like, problem to basically say, like, okay, we have this much cash.

Oh, and then you have obviously venture capital that you can raise on top of it. Right? And so you have this much cash.

How much money should we raise? How, like, how quickly can we go and deploy it, etcetera, if we can scale revenue as basically as quickly as we can scale compute, provided we continue to make it trivially easy for people to go and build and deploy in that.

or what? Yeah. It's just secured against our hardware.

Right?

can refinance any of the debt as it goes down. Like, the terms are pretty good from that perspective. I think, the unfortunate thing is like Twitter has no nuance or whatever.

So they're like venture debt bad or whatever. It's like, well, no, like as with all things like- It's not venture debt. Yeah.

Or Yeah. It's data center debt, right? But like, yeah, I think there's specific tools and specific areas where you can be very, very deliberate about not just using one specific tool as a hammer, like venture capital as a hammer for everything.

You just have to kind of, like, go out and explore it and figure out how it kind of, like, works for VC is the most expensive financing you can get. Yeah. Yeah.

I I think, incidentally, I think also people think about VC completely wrong from a raising capital perspective. Like, tell us how this VC is wrong. Yeah.

Well, I I think most people are like, okay. Well, how do I raise as much money as possible from, like, whoever is, like, probably the best that I can get at that point in time? And I think that's, like, kind of close to right.

But I think what you should be doing, or at least what we've tried to go in and do is, like, try and figure out what almost unfair advantage you can buy with that equity because it's the cheapest equity or it's the most expensive kind of equity you're gonna give away at that point in time, assuming your company's gonna get better and better and better. And how do you use that to, like, go in and work with somebody who is stellar and who's going to go in and compliment you? Right?

Like, you know, yeah, like Serious So lucky. Yeah. Right?

Like, you know, great. I've never started a company. Race from Lucky.

He's got good advice. I can text him all the time. He's really fast, etcetera.

Like, awesome. Right? Then you kind of like move on and and you kind of like, you know, worked with, you know, John and Jordan and Jordan at Unusual.

Right? And they were like, yeah, you roughly know what you're doing in building a product. Like, we're just gonna mostly like leave you alone and be totally available for advice.

Amazing. Awesome. Get to series A.

Business is a total, you know, operational tire fire, right, because we just don't know how to scale a business. Right? Go and work with Erica.

And, you know, Jordan's over at Redpoint, so bonus. Like, you know, we get to work with them continually. Right?

And then now moving into, like, you know, raised from TQ and FPV, like, we're moving into the enterprises now. Right? And, like, feeding into there.

Right? So every step of the way, we've kind of moved towards, like, who can we partner at at this specific time? Who's gonna help us unlock that next section of the journey?

Because guess what? I just I don't know enterprise sales. I can roughly like eyeball it and be like, yeah, as an engineer, I think these are the kind of features that we're gonna roughly go in and need, and we have some wonderful people who are gonna help us internally.

But you really wanna work with those people who are like at the boardroom dynamic level are going be like, Oh yeah, we're all aligned, that's obviously what we want to go in and do. And we can spend our time basically saying, How we win this? Versus bickering about strategy.

Right? No, I just had to pull out some beautiful data center charts. I feel like you've done others.

I just couldn't find them. Well, these are good. Mean, like, they all kinda look the same.

Like, they just they're servers in a rack. This is our box. Yeah.

Exactly. This is our box. Right?

This box. It's like, do you wanna see more racks? It's like, oh, yeah.

It's like, you know? What's the what's the Jay Cooper signature edition? Yeah.

It's a We have we actually have we have plans internally. Yeah, so it'll be fun. We've got a few different promos that we're gonna do and like stunts for the year, so those will be fun.

Yeah. You had a tweet about data centers in space just before we wrap up this section.

do you hate so much? Okay. So it's not no data centers in space because actually, think, like, my hot take is, like, I think this is solvable.

I've just never seen anybody solve it, right? Because you need to, like No, no, no. You said you said how are how are you gonna dissipate that much heat in a vacuum?

You're making a physics claim. Yeah. Yeah.

Yeah. Well, because because I haven't seen anybody, like, prove how you're gonna go and dissipate that much heat in a vacuum. Right?

Like, it it doesn't mean that it's not possible. It just means that, like, nobody's kind of put it up there. Pardon?

Astrophage.

Martian thing. Okay. You're very lucky.

Yeah. Yeah. That's fair.

But, yeah. I don't know. I mean, it could work in general.

Right? But I think a lot of people and I I think, incidentally, this is probably what you have to sort of do. It's like they're putting almost the cart before the horse.

It's like, oh yeah, we're gonna put data centers in space. It's like, okay, but how? It's like, well, we have some period of time to basically figure it out.

Right? It's like it's like, you know, in The Martian where they're like, oh, how are gonna like intercept with the Yeah. Restropatriates.

Oh, okay. Right. It's like, how are we gonna do that?

It's like, well, we'll figure it out. We have however long to go in and figure that out, you know? Yeah.

how do you know what's, like, basically not possible and, like, is a grift versus, like, is possible, but, like, sounds completely insane. Right? And you're like, oh, cool.

Like, you know, we're gonna put data centers in space.

I think they want the ability to version things. So, it's not like actually that different. Like there's just almost like slight deviations in terms of how it kind of materializes, right?

So agents want a way to be able to go in and test changes incrementally, right? Like we have feature flags as like engineers or whatever, right? Like, is there any reason why they can't just use feature flags?

Right? I don't think so. Like, I think there's ways that you can just go in and do that.

Right? They want version control. Is there ways we can use Git or not Git?

I think that one is, like, realistically completely up in the air. Right? And I do think that's something ultimately outside Git will emerge in terms of how we're gonna go and version a lot of these things over time.

They need observability. You need to be able to go in and essentially query what happened at what point in time, which steps failed, traces, logs, metrics, all of those other things. They need like network compute and storage.

They need the ability to write files, save files, iterate on files, snapshots file system, all of those other things. Right? And so I think a lot of the stuff that we roughly needed is like very, very kind of in line with a lot of the stuff that agents also need.

Right? And so like the branching and forking stuff, like, it's not different. Like, we're just moving a thousand times quicker than than we used to.

And so some of these things, like, look like you really need, like, something massively, massively different, but it's just you need something massively better than what currently existed. Right? You need orchestration.

You need something massively better than Cube. Right? You need, like, networking.

You need something probably better than Envoy. Right? Like and it just goes all the way down the stack essentially in terms of, well, if the the workload profile doesn't change so much as it gets, like, massively, massively compressed because you need to do thousands of these things, what assumptions change?

Right? Like, ETCD is gonna melt. Right?

Like, you know, you need to replace it with something. Right? And then I think you can go all the way down the stack and basically say, okay.

Well, that part has to change, and that part has to change, and that part has to change. And the interesting thing about the kind of like super exponential curve is that you have to build your systems in such a way where you can rip out those parts at any point in time because a new bottleneck might emerge because, you know, you start getting really, really good at like parallel agents. Agents.

Right? And then that's kind of where the new bottleneck is. Right?

And that breaks a different part of your system. Right? So I think it's very much like similar kind of stuff that kind of like humans have needed.

You just need at a 1000x scale. Right? So like, how do you code review in the age of the agents?

Right? I guess it's more of a question. You tell more agents who don't.

Yeah, right? But then like, who reviews things for like CVEs and like all of those other things? Can get kids.

More agents. Great, okay. And then that's how we hit the inference wall at some point.

Right? And you can continually throw agents and agents and agents at that problem. Right?

But like, you know, I think there's, I think there's a limit to like the amount of agents you can kind of throw at a problem. You started, though You already had a CLI before it was cool, I guess. Has the CLI's always been cool, by the way.

But, yeah.

the CLI changes because the way that we think about this is, like, how do you give Claude or Codex or Chat or, like, whatever, like any of these models almost like a handhold. Mhmm. And, like, a CLI is a single command when you think about it, right?

It's like, okay, well, you're going to do deploy or whatever, right? You're going to get logs, you know, whatever, right? Like things that were prohibitively annoying to humans are not actually prohibitively annoying to agents.

They're really, really nice, right? And so if I wanted to hand you a CLI and I said, hey, guess what? The CLI has 40 arguments and 600 flags.

You'd be like, wow, that's crazy. Like, I'm never gonna use all those things in general. Right?

But you hand it to an agent and you say, hey, that's 40 arguments and 600 flags. You'd be like, oh, yeah, this is excellent. You know?

Like, I I have so many handles that I can go in and kind of like work on with this. Right? And so I think incidentally, if you're going to go in and try and expose things for agents over over that mechanism, you wanna just basically have as many handles as possible where they can get information, query additional dynamic information, and then see how it can close that loop, like, as quickly as possible.

Most of the kind of like problems right now are actually just how do you close loop as quickly as possible? Where does the agent get stuck and how can you go and kind of remove that? That's why incidentally, like telemetry is very, very important because if you can tell where the agent gets stuck from the CLI and you say, hey, listen, like twelve percent of people are actually getting deviated from the happy path because of this thing.

And now I go and add this arg and that drives it down to two percent, you've massively increased the like rate of the loop closing for a lot of people in general, right? So that's kind of the way that we think about not just the CLI, but every point in the dashboard, right? Like it is a user journey from, I hear about Railway.

I go and get something deployed. I get my first green build, whatever moment. I see an endpoint.

I see some logs. I see whatever. And then I go in and iterate, right?

And then I go in and iterate loop is indefinite and infinite until the end of time. Right? It's basically like user wants to deploy a new thing.

User wants to deploy a new Postgres instance. User wants to change their their their code. User wants to iterate all all over time.

Right? And so if you just focus on a lot of those iteration loops and and figuring out what's blocking that loop from closing as quickly as possible, like one of the things we talk about internally is you never ever, ever want to be waiting on compute anymore. You always want to be waiting on intelligence.

Right? And if you're waiting on compute, there's a bottleneck that needs to be destroyed there because at some point that bottleneck will be so, so, so large that some other workflow will kind of emerge to go in and change a lot of that stuff. I think incidentally, we've built a really, really awesome product where you can push code and then you build the code and all those other things.

Right? But that push pull whatever kind of like loop, I just fundamentally believe it's gonna go away. Right?

Like it's you were gonna get to a point where you make a small change in production, that changes version across your entire kind of infrastructure. You're working alongside, you know, copy and write versions of your your database, all of your infrastructure, and then you merge it in and instantaneously, it's it's like live. Right?

Because that's like the holy grail of loops. Right? But that like push pull rebuild thing, right, is a point of friction that we are like removing entirely from our loops.

Yeah. It's incredibly fast. So if anyone hasn't tried it, like Yes.

Yeah. That fast feedback is great.

it's actually just a mechanism to show you changes over time. But I think you're totally right in the sense that like, we have previously used it a lot as an input and its goal moving forward is actually a lot more like an output. What I mean by that is you would go to the canvas and you make some changes and all these other things, whatever, right?

And you see them and, you know, your agents or your infrastructure would evolve over time, right? Now you just have a bunch of agents that like, they have access to CLI and they can go in and make those changes in general. Right?

And so the canvas actually, instead of becoming this like input thing where you're like, oh, cool. Like, how do I go in and make this happen? It's actually just more of an output thing.

It basically says what information- Dashboard. Yeah. What information does the human need at this point in time to make suitable decisions about about, like, control requests of, do I approve this?

Do I not approve this? Right? Like, that's realistically all the Canvas becomes at that point in general.

Right? Also a way and I think this is important, and I think this is lost on a lot of people who are, like, building some of these, like, Canvas experiences. It has to be almost like an anchor for your context.

It has to be like a port in the storm. It has to be like you have to think basically about it as, like, layers and, a file system almost to, like, get to the next spot. Right?

And so you have all your infrastructure and like, this is why the Canvas starts as like, it's just a project. Right? And then you have a drill down chart, right?

Like, it's like, I'm breaking down into these services or this like section that just is like a function or code or anything else like that, because you want to actually be able to represent the entire thing, not just in your head, but in this canvas so that other people can also get that representation so that they can think on the same wavelength as you so that they can move as quickly. Right? I think a lot of orgs, especially as they scale, they get in trouble because all that context lives in somebody's head, basically.

And then it's like, oh, how does this microservice work? It's like, I have no idea. Go ask this specific person.

Right? And then you have entire categories and classes of products that are built around like, how do you do context discovery at all these things? And I think a lot of that stuff just gets melted in terms of if you can have a really, really solid hierarchy and you can infinitely nest services, infinitely nest code, infinitely nest all these things all the way down, that's what allows you to kind of build these kind of like structures up over time, you know?

And I think it's also what's going to allow us to like build, I've written a bit about this, like these like hyper structures, like things that are way, way bigger. And like, you know, you look at the Golden Gate Bridge and you're like, how, how did we build that? Like, you know, we've, there's that whole meme of like, oh, how do we build this?

Like, we lost the technology. We don't know how. We don't know how anymore.

Right? It's like, well, yeah, I mean, to some extent, yes, because a lot of the coordination that we, that built those things like has evolved, right? And like has changed.

And there are new things that we've lost almost like some of the art of like building that structure as we've just like jammed everything into Slack. Right? And we're just like, everything happens through Slack and it's just- But you have anything in Discord, so Yeah.

Well, that's the same point. It doesn't really matter. It's just like message passing and interrupts, message passing and interrupts, message passing and interrupts.

Right? Like- So you're arguing that there should be something better, more structured?

Yeah. Yeah. Okay.

For sure. I think Slack I think and incidentally, I think Discord is awful too. This is the equivalent of my mom test.

Right? Like, what have you done that has your solution to this? So internally, we've built a tool called Central Station that allows us to go in and aggregate all the context from all of our users.

So every piece of feedback, every piece of customer support, every single thing like that gets aggregated into what we call like clusters. If you have an incident brewing or like anything else like that, now we can go and determine how many users are affected, all of those other things, etcetera. And then we can actually break off a discussion based on that.

And I think a lot of that is actually a lot more helpful and more correct in terms of instead of, like, having just these, like, long running channels where you're just like, which channel should I put this thing in? Right? Like, you can dynamically aggregate that information and dynamically route it to the right person based on the context, right, we know we know internally, like, these four people are pretty close on networking.

Right? And so if we see like, okay, we've got a networking thing, you can roughly, like, drill it down to, like, those four people. Right?

And if you're saying like, oh, okay, cool. It's actually with this part, you can just go, like, look at the the commits. Right?

And this is like no longer a manual process internally. Like, this is the whole point of why we built if you go to like a station or help.railway.

com, there's a whole reason we built this thing, right, is because we wanted to figure out how we're going go in and scale with like a massive, massive, massive amount of leverage to go and aggregate all this feedback, you know? This is built in house? Yep.

Okay.

Yeah. Okay. Alright.

Yeah. Oh, if you go to if you go to our I account can just, like, cron this and then just have Well, you your you don't even have to cron it. We expose this as, a PubSubbable thing.

So go to railway.com/stats. Oh, there you go.

Yeah. That's your And so it's, like, all real time metrics for all of this stuff. There's a way to get this as like a JSON too somewhere.

Yeah. You care or anything else like that. We'll look it up.

Yeah. But yeah, yeah, we're we're big on like trying to build everything in in public, talk about a lot of the stuff we're working on. You know, like we've had some issues or whatever in the past and we're like, Hey, cool.

Like, here's how we're fixing these things. Like, we've, you know, we've got both compliments as well as some flack for our incident reports and like always trying to like make them better over time just to like talk with people, right? Yeah.

Yeah. Any, obviously you had a big one recently.

talking through, like, what happens and I guess how do you how do you address it, you know, Yeah. As a So internally as a this one, like, really, really sucked. You know, it was it was like to do with an upstream provider that didn't they didn't do the behavior that they said they were documenting, which is unfortunate given they, like, wrote the RFC on how the behavior should work.

But we rolled those things out, and then central station kind of caught that initially where we had a couple users being like, oh, like, the caches aren't invalidating for some of this stuff. Right? And so turn it off immediately, etcetera.

Right? But when you go and kind of roll out to those, like, that, like, user base of like 3,000,000 people, right? You know, like you have a lot of different disparate behaviors that can kind of come up.

Right? And so try as we will, we tested those things in, you know, staging. We have tests for them, like all of this other stuff, you know, and unfortunately, we like hit a kind of an an edge case there.

Right? And we've incidentally, like, gone and hardened a lot of those systems. And now we can, like, make a lot of that stuff better.

responsible disclosure. We kind of on the side of, we'd rather over disclose and know that you know that something is wrong versus almost like having your provider gaslight you. And so, yeah, you know, we've we've we've kind of we've erred on the side of, like, sharing those things kind of more publicly, even if they go in and impact a small, like, subset of of those users.

Right? And that's kind of just a decision that we've made internally. It's it's under, like, we have four values.

One of them is honor. And so, like, what's the honorable thing to go in and do? It's like, well, you notify people, you know, to the widest degree which they may have been, you know, affected or there was an issue or whatever, and then we kind of confront that head on and be like, why did that happen?

What can we do better in the future? All of those things kind of like that, you know? So Yeah.

Not the whole user base. No. And that's because of, like, incremental rollouts and Yeah, other things progressive like rollouts and stuff like that, right?

companies, it totally is. Right? Like what, there's a whole quote of like meta runs like 10,000 versions of different versions of meta in general.

And like to our earlier point about agents, right? Like, they need the same thing. They need to build a shadow traffic.

We'd have to hook in with like your observability infrastructure in general, right? This is like why we almost have the template loop on the platform is to be able to kind of roll those things out progressively where you say, hey, listen, you know, I can roll this out to like Johnny VibeCoder initially. Right?

Or I can push a shard and you can almost like consume that at your own leisure and be like, oh, okay. I'm gonna update to this specific version. Right?

Or have this kind of like roll out over a period of weeks where you're pushing a new version and then it goes to, you know, 0.1% of people, 1% of people, early dot like, whatever, and then rolls out all the way there. Right?

That's the kind of like nondeterministic version control that that we've kind of like talked about earlier. So, 100%. Right?

And I do believe that, like, that's where most things should go go towards because I think ultimately most companies end up building that stage rollout system in in house. Right? And it's just the same thing built again and again and again again at every single one of these different companies.

So there's a massive opportunity to consolidate a lot of like developer stack. Should have a free tier. Like the model providers give you free tokens if you let them use the data.

Like we'll give you free compute if you're like the number one shark that goes out and you let us plug into your observability. Yeah. Like incidentally, we do that.

Right? And that's why the, you know, we talked about, yeah, we talked about, you know, the impact of that on like 3,000 people or whatever. We start with the kind of lower impact people, like the, you know, larger companies, etcetera, on the platform, right?

Like they're the last ultimately that should receive those kind of rollouts so that they have a version of the platform that's like deeply, deeply stable. Right? I have three services, so I'm sure I get the first rollout.

I think if you don't have the primitives to make iterating in production safe, it becomes very, very difficult, right? And so if you're an observability provider and you're like, oh, here's this fix to this error, right? Like, assume like 80% of those, they're probably actually good.

Like, they're gonna make sense, etcetera, right? But then the last like 20% of that long tail of like kind of complex kind of issues in general, ultimately rolling those changes out, if you just kind of let somebody say like, oh, cool, this looks good, and just like stamps it, there's an opportunity for you to have an issue or an incident or anything else like that. And I think that's why it's really, really important to have those kind of like forked environments in general, and people have staging, etcetera.

But it always ends up like deviating from prod, right? And so you need the primitives and the workflows and the experience like built in our mind as a first party on the platform that you can fork any point at any service at any point in time so that you can almost like, you know, think I consider the canvas almost as like a little, like, sheet of transparency paper, and the agent is kind of like this little guy that you push up, and it's like, should be able to, like, pop up in the canvas, and then it should be like, oh, cool. Like, well, I need to copy that service.

I need to copy that service so I can test these two things. Right? That's my hypothesis as, like, an agent or whatever.

Okay. Cool. I can go in and do that.

Looks good for all the this stuff. Ideally, I get a read only copy of of production. Anything that's PII, etcetera, is kinda, like, marked as, like, a transform when we when we automatically clone that database or go for a copy on the right version of it or read from it, and then it just makes those changes.

It says, does this actually work? Right? Like as close to production as possible.

Right? Because ultimately that's how close you have to be, or you just have a massive amount of drift where, oh, I've changed this thing. And then it just kind of gets out of sorts, right?

The system gets a lot more unstable. I think that that's like what you see with a lot of these kind of almost massive systems that these companies built on top of like Docker for local and then like Kube for production and like this specific thing for whatever, right? It's like all of that complexity ends up getting to a point where it slows down the developers, yes, but it just gets to a point where it's so unstable at scale that it becomes hard for people to go and iterate and make those changes.

Right?

Oh, yeah. Yeah. I mean, I've I've kind of Have you come around on it?

Yeah. Well, I flipped. I'm actually still not a believer on the AISRE because I believe that you need you need the primitives to make those things safe.

And if you just unleash an AI SRE on your production infrastructure, and you don't have like safe primitives for like copying volumes, making sure that this is fine, it's gonna nuke your production database. Like it's not a matter of if, it's a matter of when it's going to nuke that database, right? I'm a big believer in making those kind of like loops safe in general.

I think I was a pretty deep, like almost, I don't want say AI skeptic until, like, 2023 and then 2024. I've kind of, like was like, okay. Like, maybe I can make this thing roughly do it, etcetera.

2025, I was like, okay. Now I can, like, hold this, etcetera. And then, like, over the whole Christmas break, I think you just saw, like, I guess, winter break.

But it's just massive. Like, everybody came back came back and be like, oh my god. It's it's almost impossible to Here's you on the Cloud docs?

Yeah. Cloudbot. Well, But open it's gotten to a point where it's it's almost like it's harder to hold it wrong than it is to hold it right.

You know? And it's like, you know, the there's that scene in like Avengers or whatever where Vision's like, it's terribly well balanced, you know? Like when he picks up Thor's camera or whatever, like, you're like, damn, like this this thing just kind of like self balances and like works quite well from that perspective.

So, I'm I'm a deep believer at this point in terms of that will be the dominant species. Right? Again, you know, Assembly, C, C plus plus JavaScript, Words.

Right? Yeah. It feels like a big jump.

Yeah. Feels like a big jump. And and it is too.

Right? And I think like there's it's not like you abandon, like, CPU based discrete logic in general and just move straight to fuzzy logic. You you need both.

Right? So your skills should call code or applications or like whatever, some sort of like static structure, and you can use the skills to kind of distill what the almost like procedure should be or like how the code should act, right? Yeah.

I'm kind of coming to this thesis, which is you need three points essentially, which is you need a clear spec of what defines the system. You need the code, and then you need the tests, right? And I think when you say this thesis out loud, it's like, well, if you've been in engineering for any amount of time, you're like, well, no shit.

Like, yeah, of course, that's a RFC, like a request for comment. That's tests and that's your code, right? But they all matter a lot, and having them all be actually together so that they can reinforce each other and say, well, the spec and the tests match, but the code doesn't.

Let me reconcile that. Yeah, definitely. Oh, okay.

Now the tests and the spec match, let me go and reconcile this other thing. Right? And you can kind of move through that period of basically saying, well, this is fuzzy, and these two are either discrete in the case of tests, or slightly fuzzy, slightly discrete in the case of code.

Right? And that's kind of your iteration loop. I think that's also incidentally why you're seeing a lot of people be like, software factories, and I wanna write this doc and, like, how to go and reconcile all this other stuff, which I think is a bit of architectural astronomy if you, like, don't actually go in and implement it.

But I do think generally that's kind of that loop is kind of where most things are gonna ultimately end up. Yeah. For listeners, we've been talking about this on the pod for three years, the holy trinity of specs and tests.

Oh, okay.

have a loop that I've kind of set up, which is you put the Railway CLI on top of something that runs on top of Railway. Right? And so you're essentially authenticated as whatever the current box is in general, and you can make any sort of changes to it.

And then you just call Railway deploy and it deploys itself. Right? Like, it's just like, oh, cool.

Need to go and spin up this instance of this environment. I already exist in this environment. Excellent.

I've got access to a Postgres instance now. Right? Like, and this was kind of where we want to go with a lot of the, like, agentic, almost like self replicating, like, infrastructure is like, that's your loop.

Like, you iterate in production. That's your loop. Right?

You're gonna just continue to to make some sort of change and either it will work and you're gonna wanna go in and merge it and say, cool. That's great. Like, put it into our upstream or it will not work, and you can just kind of throw it away, etcetera.

Right? How do you go in and make those throwaway copies, like as trivial as possible to spin up, run super cheap, etcetera? I think the era of like, I have an AWS instance and I'm gonna, you know, get four vCPU and 16 gigs of RAM, it's going to get like completely destroyed, right?

Because it's like, if you do that for agents or anything else like that, you now need a thousand of those machines, right? Like it's so prohibitively cost expensive versus like, you know, we've spent a ton of time trying to figure out how do we go in and make these deploys, whatever you want to call them, you know, Cloud Serverless got the like isolates, everybody's like, call it sandbox, like whatever. Like that atomic unit of deploy, only pay for what you use, spin up instantaneously, closed loop as quickly as possible.

Right? Because if the system can self replicate the system and it can do so safely and say, this is my environment, I'm making these changes, etcetera, it can come back with, hey, does this look good? Like, this is a new state of infrastructure given this prompt.

I think I've solved this problem. Right? And then you can go back to the agent and say, Actually, it looks a little bit different, goes and does the loop again, and you're like, Cool, excellent.

Apply.

No. I mean, it's getting better every day and, you know, I'm on X or Twitter or whatever you want to call it. And like, you can always, you know, yell at me about the experience not working as well as it should because there's plenty of things that should work way, way better.

or philosophical differences that you want to call out. No, I think it's like, it's, as you kind of mentioned, it's somewhere in between, right? It's like the ability to run stateful, long running, like, you want to call them workflows, want call them executions, you want to call them whatever.

the app runner. App runner and The new one. Yeah.

I forget forget the bunch of them. Yeah. I think like that's kind of where everything roughly And this is why we've been working on it for the last like six years.

It's like, we just believe like you do need access to a computer, like box that speaks Linux, right? So that you can deploy the things that you want to go in and deploy on it, right? Like other things are going to, I mean, they're going to change the almost like surface area of what you can kind of go in and build.

For us, we're always like, no, like users need a computer and they need to be able to deploy anything that they truly want. Right? And that's why we focused on a long time, for a long time on those primitives, right, of like network compute and storage.

Right? Because if we can give you those things and we can expose them to you and allow you to run these things indefinitely, right? That's of course like where we believe that it's going to go in general, right?

And so I think you're seeing right now where, again, the whole like Twitter has no nuance, whereas everyone's like servers, right? It's servers. It's like, no, it's like, it's always somewhere in the middle, you know?

Like, it's always some sort of convergence of, well, I want to run it for a long time, but also I don't want to like provision this resource statically or pay for just things that I'm not using or anything else like that. And that's always been our thesis from like day one. It's like, pay only for what you use, run it indefinitely.

It is just like full Linux, basically.

Yeah. Mean, just have, you have so many people just like, you're just like, like you were running stuff on here? Like you as this company?

Like, it's crazy that like you, whatever, like name that you would know is running this thing, and then you're coming to us be like, yeah, we kind of like want to like move a lot of this stuff off or whatever. Like, oh, okay, cool.

guess, I guess, right? Like, I mean, I think it's just hard when, like, it's not your business. Like, the business of Salesforce is to build a really, really good CRM, you know?

Right? And, like, that's their focus. Right?

They should be really, really focused on building a really, really great CRM. And then you acquire this business that is a compute business that's kind of an offshoot of your business in general, right? And I think like, you know, a lot of the early Meta folks have talked a lot about like focus, right?

And like, I think Boz has a whole like write up that he's done basically, where he talks about in the early days of Meta, we had no money and like, were forced to get focused. Right? And then we basically turned on the money.

This is all like, you know, me verbatim. Rephrasing. Yeah, rephrasing or whatever.

We turned on the money tree and then we had no reason to like, not like have focus because we just had infinite money where we could go and split all of our focus. Right? But that ends up diluting your product.

It ends up like making these things where you kind of have these offshoots where you're just like, is that the focus of the business, right? And it ultimately ends up not being if it's not the core of your business, right? And so to me, it's like kind of no wonder that like it languished in general, right?

Because it just wasn't the core focus of the business. And I think that a lot of companies get in trouble with this when they kind of like split out their focus in general, because it means that you're almost like fighting a multi fronted war, trying to like compete with all these things. Not just like compete with them externally, but compete with them internally for like alignment and like, where are we going?

What are we doing? What is our purpose here? Right?

Like, you're, you know, if you're really, really, you know, like Salesforce built and you're like, Hey, listen, I love Salesforce. I really want to like work on all those things. You know, and you're mission driven, which is like the aspiration for a company in general of like, why do people work on things?

Right? It's like, want to work on something interesting, right? Like, Heroku is off to the side.

It's like, it's not the core of the business. Right? And so to get those resourcing, you know, like budget or focus or alignment or whatever internally, it's just pushed away.

Right?

Whole release was a little bit odd because they like, you know, they they kind of called it up, but they did the Our Incredible Journey. Yeah. Right.

Like, yeah. They didn't say they were like shutting it down, but they're like, yeah. Yeah.

Yeah. So, yeah. And then, you know, behind the scenes, I think they issued some some stuff to people being like, hey, yeah, you should like close these accounts down.

Like, we are going to go in and defecate this and like remove it every time. So, yeah, I mean, it's just like and it's crazy because like some of my first deployment experiences were like on Heroku. Learned to It's like a foundational thing where it's I had this picking alias in my bash for, like, Heroku deployments.

Yeah. Right? Like, you you start with, like, dragging stuff into an FTP server, and then, like, you move on to, like, trying to get a deploy working.

Like, how do I go in and make this happen? And it's like, Heroku. Did you know about Heroku Packs and all those things?

Right? And you learn about all this, and it was the on ramp for us. Right?

You know? But the wheel turns regardless. Right?

Like, there's new stuff that's emerging, and, like, we're very, very happy to, like, almost, like, continue to, like, know, carry the torch on for a lot of that stuff. But we don't want to be the new Heroku. We want to be the way in which people are building and deploying software and ultimately the way that people monetize software over time.

Right? Yeah. So I mean, it's a big crown to be new Heroku.

Like, there's like 50 companies that fought for this. Oh yeah. Everybody's kind of like, you know, holding some portion of this being like, ah, you know?

But yeah, I think, you know, for us, we're just happy to go in and support people, companies, etcetera. The platform works a bit differently. It's like, you know, it's obviously kind of almost the similar kind of like game loop Super of IC.

Yeah, exactly. Right? But we've been quite dogmatic in terms of where we believe these things are going to go in terms of primitives, you know, the agents kind of fan off all of those other things.

Right? And so some things will fit and then some things will, you know, you have to change a few of their workflows, etcetera. Like, we don't have and what's that feature that people really love?

Pipelines? Heroku? Yeah.

Right? Like, there was we have some approximation of it with the environment system in general. Right?

But, yeah, so it's been super exciting. We've got a ton of people that we're able to go and support, so And it's growing a lot.

What's Yeah, your so I have used Temporal for almost like ten years now, right? Because like, Cadence, Uber, all of those other things like Just give people a scale of what Cadence is at Uber. Like, people don't know.

Yeah, so Cadence was the precursor to Temporal, and it powers, like, all of the trip actions, the rides, the, like, you know, when you do you, like, rent a jump bike or scooter or, like, any anything else like that or a car? It's like, you're running these workloads for a period of time, and you're basically saying, this ride will run for an indefinite period until it, like, finishes. Right?

And you can go and attach information, whether it's like, oh, you paused it in this zone. And so, you know, you need to add this dollar charge to, like, the the bill or anything else like that. And then when you end the trip, like, your workflow is done.

That whole experience behind the scenes, I don't know about today in general, but it was like powered by Cadence at that point in time. And so it's a really, really like And I used to say like, it's like, imagine if you could program the entire user journey top down as one function. Yeah.

Right? Yeah. And it's such a powerful idea and it's so, so important.

It's also incidentally so important for the next phase of the agentic journey where like you want an agent to do a specific task and then you want it to like be complete or incomplete on that task and then move on to the next thing. Right? Like, you need a way to be able to go in and manage these workflows.

You need a way to be able to go and manage these workflows dynamically. And I think for me, Temporal was always like really, really, really great in theory. And it was really, really great when you got it working the way that you wanted to in production.

It's just it required you to like model that entire journey in your head. And if you didn't have the entire journey in your head, you could put yourself in a spot where you would cause like issues where like replaying the state of the entire workflow, like causes like a non determinism issue. Yeah.

Because it works on like deterministic workflow history. Yeah, exactly. Right?

And so it's very, very easy. It's like the way that I kind of like would describe it is like, well, it's a jet engine, right? Like if you know how to like go in and operate, if you know how to go in and run it, all of those other things, right?

But you can't hand it to people who are trying to build things that end up being complicated, but don't have that whole kind of like state in their head, right? So if you have a large like, we run our whole deployment pipeline on on top of it. Right?

And so that's like a reasonably complicated workflow. Right? Like, there's pre commit hooks.

There's like signaling. There's queuing. There's like all of this other stuff in in general.

Right? And we kind of ran into the same thing at Uber where like, as you tried to express this large workflow, as you mentioned, like, going all the way down, got more and more complicated, and it got more and more states in the state machine that you had to, like, map the state machine back to, like, the the workload. Right?

Yeah. Exactly. This if that Yeah.

And so so at Uber, we built a system for, you know, doing the the state machine and, like, testing the state machine and all other stuff. And we've started to, like, go and build some of those things here because, like, it's it's grown, you know, quite heavily. Right?

But it's, like, it's such a, like, you know, I don't wanna say love hate relationship because that's, like, too broad in in general. Like, it's it was when it works really, really well, it works, like, super, super well. Right?

But then you run into a spot where you just, like, somebody who hasn't interacted with the system or doesn't have the full context of the system goes and puts something in the system that invalidates some of the state or causes a nondetermin issue nondeterminism issue or spins off a ton of activities or anything else like that. And then you have to kind of keep track of, like, almost underlying SRE knobs of like, oh, we have, you know, the amount of activity slots in, in this thing. Right?

And it's like, well, these should just scale with like memory, vCPU, all of those other things in general. Right?

We have a few internally

It's very, very doable. So, yeah, I think the workflow stuff is very, very interesting. Like, there's a few really cool companies that I think, like, Restate's doing some neat stuff here.

Yes.

we have or we have TypeScript, we have Rust, and we have Go. Those are three languages. Right?

Yeah. We don't add any more stuff. Actually, that's not true.

We have a little bit of C because we write BPF code and and, like, and and it's hooks and stuff like that. So but those are those are the the kind of Is this for this, like, the side container things, side car stuff? No.

Well, so this is for the networking stack as well as the volumes and stuff like that. So, yeah. But it's like yeah.

Yeah. Yeah. Mean, we built an engine for determining dependencies based on your source code, which is super cool.

It's called RailPak. We built the first version called NixPaks, which is on top of Nix. And then, yeah, we moved.

People have been trying to get me to adopt Nix and NixOS for like four years. Yeah. Is it ever gonna be a thing?

I don't. I don't know. Like, we were super excited about it in general, but it's like, it has a bunch of different kind of pain points in general.

Because if you just think of it, it's like, it's a stack of version source code, or it's a stack of version binary at specific slices in time, right? And so, if you want version X and version Y, you end up bloating a lot of your kind of like package, like space, right? Which blows up the size of your images and makes it really, really difficult for like really real world workloads.

Think if you- But you, you know, you content address it, you cache it. It's, you know, there's a lot of optimizations that you, in theory, you should be able to do. In theory, yes.

Right. And what happens ultimately is like, you have a large enough user base and you have a disparate enough set of machines that you kind of run into the problem that there's a paper that Meta released XFAAS, they're like internal kind of like serverless system. It becomes an it ends up being being very, very difficult to go in and and do that at scale unless you break out specific runtimes, basically, which we did not want to go in and and do.

Right? Because we wanted to truly allow you to deploy anything. Right?

Which was our initial kind of thing with NICS. But we've moved towards some interesting stuff that I think we'll we'll be able to talk about a little bit later that we've we've built for doing content addressable file systems to be able to, like, lazy load anything from any point, and then just page that into memory. Amazing.

Okay. Yeah. It's gonna be fun.

There's a the whole future is very, very bright. It's it's crazy. It's it's gonna be nuts.

I think I've had about 25 in and then we have some, you know, power users kind of all the way down. I don't know. Like, we came back from the winter break, and I was basically like, if you're writing code by hand, you are doing this wrong.

Right? Like, the your code the tools are good enough at this point, like, that you can move extremely, extremely quickly. And like, yes, there are issues and pain points and all of these other things, but you should be reviewing the code that you're writing instead of trying to go in and write it by hand.

Like all of those architectural patterns, all of those other things, like, you're not just don't like, you're not going to throw them in the garbage or whatever. Actually, they matter more now than any other time, but you just shouldn't spend your time generating code that you would write. Like, if you know how to go in and write it, just like ask the agent to go in and write it and then reconcile it until it looks like you would have written it yourself.

Right? And I think incidentally, like people misconstrue my propensity to, like, push people towards agents for, hey, we're growing really, really fast, and we've had some kind of, like, bumps in real life. Like, they're not necessarily related in terms of that.

But I think people should really, really understand, like, the tools are good enough for you to be able to move extremely, extremely quickly to build things way, way larger than you could have possibly built before. Right? And so to our point about way earlier about like, how do you cool data centers in space?

It's like, well, I don't know actually. Right? But you're at a point now with software, you can actually be like, well, how would I build block storage from scratch?

How would I go in and do these things? I have ideas because I've got history and I've read all these papers in general. Right?

Let me go in and work them out in general. And let me build like massive test benches with like thousands of tests. Right?

Because they're free to they're free to author right now. Right? To go in and make sure that like this system can now can can be built.

Right? And I think that if you're not using the the kind of AI systems to almost, like, speed run your roadmap to, like, go in and and figure out where you need to go in and be to reconcile your existing system onto the future, then you're kind of missing a large point of of what is currently happening right now. Right?

Because you can just template out anything and validate it on the side for free. Right? What's the path to spend 3,000,000 a month?

Like, is it bound by, like, ideas and things that the customers can absorb? I think for for most companies, it's actually bound by deployment at this point in time. And I think that's why we've seen a lot of, like, a massive boon in terms of, like, users trying like, not just users, like companies, like, you know, Fortune 50s, like, you know, below, etcetera, like going and being like, how do we get our developers to, like, go in and move quicker?

Right? I think you're probably gonna hit your CFO before you hit any of these limits in general, because they're gonna look at this and be like, there's an eye watering amount of, like, money being spent on these tokens. Like, I think I don't know which I think it was the Uber C- Yeah.

It was like, the blue token budget for the entire year or whatever. Right? And so inference costs have to come down, but they're also, you know, they're we're inference constrained at this point in time.

Right? And so you're gonna almost get this, like, price discovery of, like, what makes sense for an org to go and adopt. And I think what you're gonna end up with is actually, you're gonna almost, like, end up with the, like, F1 driver concept, which is if you have somebody who's, like, really, really adept at these things, it makes sense to go and put them into, like, a $3,000,000 car or whatever.

Right? But if you're not, then like, it probably doesn't actually make sense for you to go and do that. And we're going to take a few of these people and say, you can drive the F1 car.

We need to go in this general direction. Figure out if this works and like almost go ahead and prototype it. Right?

And so we've done a few of those things. We're like, we've vastly accelerated our roadmap in terms of, oh, we thought we were going to be able to go in and ship this thing in the next like few years, but actually we can probably ship it in the next like few months now. Right?

Because we're saying, oh, validated it out, it works. Don't have to even like build it incrementally. We can now skip steps to like go and just move towards where our vision is for a lot of this stuff.

And I think that that's kind of where we end up with a lot of it, you know? Yeah.

really naive way to go in and measure this is almost like your percentage of tokens that end up in production. Right. And so if you can measure that you are getting this level of impact because those tokens are ending up in production, that's awesome.

Right? But I think the kind of burden of proof is now going to kind of like arise. And you see it internally too on our stuff.

Like we have a growing number of pull requests that like like, haven't yet been merged. Right? You're just like, okay, how do you get this into production?

Right? And so it's really about like how quickly you can go and kind of build and deploy that software. Right?

Which is exciting because our whole team- You deploy software. We build and deploy software, you know? Right?

So, yeah. Yeah. The SDLC is changing, and it's something that both of us are, like, super interested in exploring as well.

What else is doing? Well, I think the AASRE. AISRE, the tools to to make so the AISRE is, like, one of those things where it's like, you know, it's a pie in the sky aspirational.

What does it take to get an AI SRE? Like what tools And by way, you should expose your tooling to your customers at some point.

center. Oh, central station? Central Yeah.

So we have it template maintainers, right? So template maintainers can like deploy and maintain templates and they get feedback on a lot of that stuff. Right?

And so we're a 100% like going to go in and expose those things like incrementally. Yeah. But like, you know, clustering around incidents, like everyone has a version of that, like, don't think anyone's solved it.

Yeah. Yeah. Right?

They, at some point those will, those will be things that either somebody else goes and builds or we go in and build, but we've always built stuff that like was purposeful for us. And if it made sense and, and there was a way to go in and make it useful for users or monetize it or, or make sure that that loop becomes like a profit center instead of a cost center, like, we wanna go in and do that at some point. Right?

But, yeah. Poor people is definitely dying. Do you do first party feature flagging and incremental rollout type stuff as well?

So we have a feature flagging engine that we built internally that at some point we will will roll Because I don't see it as a user. Yeah. Yeah.

Like that, you know? That would be that's good. Right?

How come you can give us what you have? Because we have to we have to beta test it. Like, we actually care a lot, a lot, a lot about the quality of the the things.

There's plenty of stuff that, like, we've used internally, and then we've got it to a point where like it doesn't make its way entirely through the journey because it fails. Right? It's like this holds for one service, but it doesn't hold for multiple services.

Right? So we'd have to go and build these things for multiple services to go in and make this work, right? And we know for a fact that if we release this thing, we'd have to go and rebuild this thing again and again and again.

And some things are worth doing to go in and do that. But a lot of them are basically like, that also, that kind of just informs our roadmap of, okay, well, for us to go and make that actually a bit easier, we can do a few of these things first, and then we get to that experience, right? We don't want to dilute the experience by basically saying like, oh yeah, this works, but only for this service, right?

Unless it's like a very, very core initiative, which is like, you know, over the next like few months, we're gonna roll out a few things that are like, okay, it works for a single service, and then it works for multiple services, and then it works multiple service across the environment. Right? But you have to be very, very deliberate about those things.

Otherwise, you end up with a bunch of broken disparate experiences, which ultimately end up creating a ton of support load because people are like, how do I use this feature? How do I go in and do this other stuff? Right?

So Yeah. It's kind of the the thing earlier about, like, you expand your company in general to to get those, like, features, and then you almost compact it, smooth out those things so the experience is, like, really, really stellar. Like, we were talking in hallway earlier where you're like, oh my god.

It's gotten so much better. And I'm like, oh, man. Like, just internally, we're like, damn.

This part really sucks. You know, we gotta make this significantly, significantly better. No.

I can I can attest, you know, over the last three years that I've watched you build railway?

you assume the software development life cycle is a 100% gonna go in and change, but it's gonna change because we're trying to do things a thousand times faster and a thousand times more concurrent than we were currently doing, right? So It's routing. Yeah, right?

And so what ends up becoming important at scale, before I even started Railway, actually built a feature flagging product. I tried to go in and sell it to people. Okay.

Because I was like, oh, it's like a, you know, like it's an easier version of like LaunchDarkly or whatever, And I ran into this situation, which is like anybody who's small enough to adopt your technology doesn't care about feature flags, right? And then anybody who's large enough to try and actually need feature flags needs so much scale that you have to like build out all the existing infrastructure. To end up scrapping that.

But it's what is old is new again, because now companies are trying to move really, really quickly, but you can't just YOLO this like vibe coded thing straight into production. You need to basically say, hey, here's my blast radius, here's my impact, here's my like, whatever. I want to shadow it for these users.

Right? Future flags. Right?

Like, you're gonna need those tools that ultimately those larger companies ended up having to go in and build to maintain their structures. Everything's just gonna get compressed by like a 1000X so that everybody can go and do that. And everybody can build those structures really, really quickly.

Right?

portion out parts of them and kill them or whatever. Yeah, exactly. Actually, I actually think that maybe that's the, the hot take, but I think that that's actually going to change.

And I think- Yes, please. You can move towards having pets so long as you have a, and this is going be a jump, so long as you have a cloning machine for your pets. Uh-huh, yeah, yeah.

If you can snapshot every single thing at every frame, then like, it actually doesn't matter if, you know, that thing gets obliterated because you have some sort of like snapshot of it, right? All of the things that we have built right now are to essentially block out any sort of changes or alterations or whatever from that, like, hermetically sealed DevOps, like, line or whatever. It's like, okay, well, you have to write a Docker file because I only need these specific instance like, only this specific cut of the file system, etcetera.

Right? What if you just had the whole file system? What if you just snapshot it?

What if you could lazily load the entirety of the file system? Right? Then you could get around this problem entirely.

You don't need the ceremony of those, you know, having a Docker file or like having an Ansible script or like having all of these other things. You can just iterate on that loop and then like snapshot it. It's like, is this the right loop?

Is this the right thing at this point in time? Okay, cool. Like, now I'm going go and merge it in production.

Like, go merge the file system. Yeah. Right.

It's gonna be really fun. Yeah.

Yeah. Well, so it's surprising. I mean, it's always been surprising to me because these are the things that we've been working on because they're just like, I'm like, it's so obvious.

First principles, you need them. Right. Everyone in theory needs them.

And then like, the big clouds don't do them, so you're like, it's impossible. Or something. I don't know.

Yeah, exactly. Right? And you're like, oh, well, they've, know, Meta has all the people who write, like, you know, eBPF code and they're like doing something with them, you know?

But like, you need that kind of stuff to solve these problems. Right? And like talked about earlier, it's like whatever is required, however deep we have to go in and, like, get to like solve those problems, right?

Like all the way down to like the kernel's TCPIP stack, right? Like we're going to go in and figure that out. Is there something that we need to go in and modify to like go in and make that work for the mental model that we have for the universe moving forward?

Like, yeah, a 100% we're going go in and do it. We'll just keep going all That way sounds fun. That's it.

It's super fun. It's like, it's so much fun. Like I have to literally peel myself away from the fun, interesting problems that we have to make sure that we can scale the company in a way that like works.

And there's so many different fun, interesting problems, whether it is like, how do you get the information from the customer to support, to the person who built the thing internally. Right? Or it's like, how do you do safe iteration?

Or how do you get context, like, from the dashboard to users? Or, like, do how you drill down all the way to the infrastructure layer? How do you manage orchestration as, a real time operating system versus a feedback control system?

Right? Like, it's just so fun. You know?

Yeah. I mean, speaking of maybe you talk about the founder side.

Yeah. How do you do it? Oh, okay.

I was gonna ask, is there a question in there? What yeah. The question is what the hell?

How do you how do do it? Question is how how are you alive right now? Yeah.

Well, I mean, yeah.

be obsessed with all of these things. Like whether it is being obsessed with like, how do people think about your product from a go to market perspective or being obsessed from a perspective of like, well, like, if I can make this change at the like kernel level, then I can make it so that the user's SSH connection never drops. Right?

Like, because that's what I want. Like, I want a universe in which I can go and like a snapshot of these things, and it looks exactly like you would just kind of iterate on on a VM. Right?

And I think you just have to be obsessed with all those things, like at every layer of of the stack. And I think that's what makes it easier for me. I think some people, like, they're obsessed with different portions of the the kind of like Journey the company, like, whatever.

Right? And I think that that's when you can get really, really good almost, like, cohesion by, like, segmenting out these things. Right?

And so, you know, in the elevator, was talking about, like, you know, you have a technical kind of, like, person, etcetera, and then you have the customer kind of like person in general. Right? And I think like if you can segment those lines out really, really well, and you can be very, very clear about what your areas of ownership are for yourself or your, you know, company or any, like just where you're going to operate, you're going to have a good Right?

If you can't be clear about those things, right? And this is why I was saying like two is the worst number of co founders is because you have no tiebreaker, right? You basically are like, well, I disagree on this thing and I disagree on this thing.

Right? Was like, well, how do you resolve that? Right?

Usually someone's CEO, right? Right. Exactly.

Right? Then you're like, okay, you have a tiebreaker. Yeah, totally.

I mean, listen, it's hard. It's hard every single way you cut it. Right?

It's hard. It's hard if you get help. It's hard if you do it yourself.

It's it's just it's just hard to like run things roughly speaking. Right? But it's so rewarding.

It's so fun, you know? What have you found useful? Like a coach?

Like to write a lot. I got in trouble. I get in trouble a lot for my Twitter.

I think there's a pattern. Who do you get in trouble with? The people on Twitter.

Oh, okay. You know, I was talking about it and I was like, Hey, if you, you know, if you're working weekends, you're kind of messing up your planning roughly. Right?

And I've gone kind of back and forth on that, right? Because I think actually right now we're kind of at an extenuating time in general, where it actually makes sense to like work more, right? Because the goals are pretty clear in my mind, right?

And so if you have the vision and you know where you're going, you should work a little bit harder to distill that vision and go and do those things. But if you don't have the like, we're we're like, I think we should be going this journal. I'm not a 100% certain.

I wanna get a little bit of clarity. I think what you need to do is you need to, like, disconnect, you need to take your weekends, like, very, very seriously. You need to write about where are you?

What do you wanna do? Where you wanna go? What problems are you trying to go and solve?

And like, think about a lot of these things. Right? So, you know, like writing is important.

Sitting down, like, I don't like the word like meditation or whatever, but like whatever gets you into the state of like your mental clarity, like, that's the thing that's, like, really, really important when you're trying to go on these journeys of of saying, well, we're here, and we really need to be be here in in general. Or, like, we're here, and I think we need to be roughly in this kind of, like, space for this to, like, work. Right?

So those are the things. And then, you know, disconnect, hang out with the people that you love, and then, like, work super, super hard when when you're, like, you know like, I try and work, like, sunup to sundown, Monday to Friday, all out in general. And then I try and disconnect on Saturday, and then I come back to work on Sunday afternoon.

Right? And then I do my writing plan for the week, all those other things. And it works really, really well for me.

But another hot take is like most advice is to be digested and to be thrown out the window. And if it's helpful, it'll come back. Right?

If it's helpful, you'll have kind of like learned it over time through experience or anything else like that. But yeah, you mentioned like the kind of standard, you know, YC advice, all of those other things. We have a lot like, we've made failure as a society very, very expensive, and it makes it difficult for people to kind of trod off the paths.

Right?

I think the agent stuff is like it's just like it's crazy. It's gonna be the dominant way in which people are doing pretty much everything. Right?

Yep. Provided we can, of course, get the amount of inference required for that to go and happen. But over the next, like, ten years, right, you just you see a fundamental shift in terms of how people are thinking about even just authoring the logic that's in their head.

Right?

Yeah. I think there's a lot of art by now it's actually not becoming a GPU provider. I think I think you're you're defined almost more by the things that you don't do than the things that you do because it's it's really, really easy for you to just say yes to a bunch of different things.

Right? And I think, like, it's gonna be very, very interesting to watch. You know, I I think Anthropic is, like, an amazing company and, like, super, super stellar.

And they're moving into a variety of different zones. Right? They're moving into, like, the Figma kinda, like, stuff that they're they're after.

Right? Yes. As a recording.

I mean, things move very, very fast right now. So, but yeah, it's just going to be the way in which people are Okay. Your answer is focus, no GPUs for now.

Yeah. Never say never. Yeah.

Right. Like, I can tell you for a fact that we will not be doing GPUs now, but we a 100% will be doing GPUs at some point in the future. That's- Oh, good.

And that's not like me leaking our roadmap because we don't have plans to go and do GPUs. It's just a function of, at some point you need flops, right? Like at some point you want, like, if you're fully vertically integrated and you want to make it really, really trivial for people to go and iterate and build and deploy things, you need access to this core piece of fundamental logic.

Right?

some point we got to a 100% data center.

It's and it's right now, it's the vast majority of the stuff that exists on our bare metal data centers. Right? Okay.

You're already there, like vast majority. Yeah, yeah. Right?

Didn't know the extent of the transition. Yeah, until late. It was completed at some point, and then we grew so fast that we had to basically like go in and scale back on that.

Take us back. Yeah. Sorry, Google Cloud.

Yeah. Was funny. Like, we got, it was funny.

We got to like on, on the Datadog dashboard, it's like, got to a 100% and then it like divoted back down into the like nineties or whatever, because we're like, you know. Adding capacity. Yeah.

Yeah. It's interesting.

Yeah. And it's hard, right? Like, you know, we're gonna, you know, figure out a bunch of different things to make sure that like the platform is deeply, deeply reliable.

You have to break ground on a lot of new things when you basically decide you're gonna build a cloud from scratch, but not copy the hyperscalers. Right? Like we've been very, very deliberate to like invent our own infrastructure from scratch based on reading a ton of papers in general, but like almost like promising to ourselves that we wouldn't copy somebody else's homework.

Right? Because we were saying, hey, listen, you know, if we copy somebody else, lose. Like, we just you're just gonna become them over time.

Right? And so you have to have a core thesis about, why does this business need to go and exist at this point in time? And for us, it's always been about the activation energy to get something to go and deploy it in production at any of the hyperscalers as as right now is far too high.

Right? And we believe that it should be instantaneous. We believe that there should be no friction in between what your thought is and reality that kinda comes out that you can share with your friends.

Right? And so that's that's what we're kind of like building toward, again, at every layer of the stack. Like, if we gotta go down to energy, we'll go down to energy at some point.

Right? It matters a lot for us from the experience of giving people access to this tooling because it's gated behind it's not even just gated for regular kind of these citizen developers that are now vibe coding. It's like you have multiple layers.

Have the citizen developer. You have the front end developer. You have the back end developer.

You have a DevOps person. You know, like, all of these layers. Right?

And they all need to go in and disappear so people can just, like, ship like that. Amazing. Alright.

That's the future. Thanks for coming Yeah. Thank you.

Thank you for having me. It's been wonderful.