The Pragmatic Engineer - Why Rust is different, with Alice Ryhl

Episode Date: May 20, 2026

Brought to You By:• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.• Sentry⁠ – application monitoring software considered “not bad” by millions of developers• ⁠Craft Conference⁠: join Gergely, Kent Beck, Hillel Wayne and others at the conference dedicated to the art and science of software delivery craft.—Rust is one of the most admired programming languages around – and also one of the hardest to learn. What makes developers stick with it?In this episode of The Pragmatic Engineer Podcast, I sit down with Alice Ryhl, a software engineer on Google’s Android Rust team, and a core maintainer of Tokio, which is the most widely-used async runtime in Rust.We discuss what makes Rust different from other languages like TypeScript, Go, and C++, and why so many developers say that “once it compiles, it works.” We go deep into memory safety, ownership, borrowing, unsafe Rust, and Cargo.We also cover how Rust is governed by RFCs, feature flags, its six-week release cycle, how engineers get paid to work on the language, and also look into how Rust’s use inside the Linux kernel is progressing.—Timestamps(00:00) Intro(04:09) Tokio: an overview(05:11) What Alice likes about Rust(12:48) Rust for TypeScript engineers(13:51) Moving from C++ to Rust(14:34) Memory safety(18:12) Garbage collection tradeoffs(21:46) Ownership, references, and borrowing(26:59) Unsafe in Rust(31:21) Crates and Cargo(35:55) Language design and RFCs(43:02) Building new features(46:30) Editions vs. versions(49:47) Getting paid to work on Rust(51:27) Contributing to Rust(53:03) Rust in the Linux kernel(55:45) AI use cases for Rust(1:01:35) Learning Rust(1:03:54) Book recommendation—The Pragmatic Engineer deepdives relevant for this episode:• The past and future of modern backend practices• How Kotlin was built with Andrey Breslav• How Swift was built with Chris Lattner• How Linux is built with Greg KH—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [e-mail]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

Rust is quietly spreading as a language of choice to build reliable and performance applications, but what makes it different? Ellis Real is a software engineer working on Google's Android Rust Team, a core maintainer of Tokyo, the de facto async runtime for Rust, and is a Rust language team advisor. In today's conversation, we cover the pitch on why Rust is worth to consider, whether you are using TypeScript or C++ today, how concepts like ownership, the borrow checker, and the unsafe keyboard work. And what are things that trip up newcomers to Rust?

how the language is governed without a benevolent dictator, and how RFCs and additions work, and many more. If you want to understand what makes us different and why so many engineers say, once it compiles it works, this episode is for you. This episode is presented by Antisys. Verify your system's correctness without human review or traditional integration tests and avoid bugs or outages.

This episode is brought to you by Century. Century is application monitoring software built by developers for developers. The first time I used Sentry was 10 years ago, back at Uber, where Sentry helped keep us honest on when and where our services were breaking. I also use Sentry today to help me understand if the services and APIs are built for the pragmatic engineer are healthy or not. Sentry shows you the full context on issues, stack traces, user actions, environment details, and even the exact line of code that caused the issue. It supports pretty much every modern tech stack, TypeScript, JavaScript, Python, Go, and others. It works on back and front and mobile, you name it. One new feature Sentry launches Sear, their AI debugging agent.

Let me show you. I open the Sear agent and ask about what are some repeated errors happening on my backend. Sear figures out that a repeated issue is a network call failure. I can then ask for more details and debug more efficiently with this AI agent integrated neatly into Sentry. Sear is a neat tool to fix the hard issues, the ones that are just hard to debug. Check out Sentry at Century.i.o slash pragmatic and start monitoring today. Alice, welcome to the podcast. Thank you for having me.

It's really not nice to have you here. How did you get into software engineering? It actually all started with Minecraft. No way. I wanted to write my own mod for Minecraft, so I learned Java. I didn't get very far with the Minecraft modding, but that's where it started.

How did you continue? Did you go to university? This was just before I started in high school, and then after high school, I had a year where I worked full-time as a software engineer and then I moved on to start my bachelor.

I did that for three years and then I did a master's for two years. How did you end up at Google? Was that straight out of university? I actually started part-time at the same time as when I started my master's and then I switched to full-time after I finished. How did you get involved with the Rust community?

Was it at Google? Was it before Google? Oh, way before. Way before. I've been doing Rust for a long time. When I was in school, I spent a lot of time on the what's called the Rust Users Forum.

Well, I was answering questions, really. I have maybe 10,000 posts on there or something. At some point, I also started being active in some chat servers, the Discord server for something called Tokyo. I kept doing that, answering questions. When I saw comment questions, I would fix the documentation. That's how I got into Tokyo, which I'm now one of the maintainers of. And then for those of us not as familiar with Rust and Tokyo,

what is Tokyo inside of Rust and why is it important? So Tokyo is, well, it's an asynchronous runtime for Rust. You can think of it as the standard library for Rust when you're using async. I mean, if you compare with something like JavaScript in the browser, you might compare Tokyo with the browser itself. For example, in JavaScript you have this loop, this event loop, which has all the tasks that are able to run, and then they get executed one after the other.

and especially if you use the await stuff, then you can have tasks, pause, and then another task start running on the same thread. And Tokyo does something similar. It has a queue of things that are able to run, and then it will run them. So unlike JavaScript, Tokyo can be multi-threaded, so you can have multiple cues running in parallel.

This seems like a pretty core part of Rust as a language, as a ecosystem. How did you gravitate towards this? Because it sounded like you were, if I understand, you were lurking on the Rust forums, you were helping out here and there. What drew you to this part of the language? Or the ecosystem, should I say?

I think part of what I liked about Rust is this feeling that as you write the code, when it compiles, it works. I mean, this has to be in quotes, right? Because obviously it's possible that there are bugs. but this is something a lot of people say about Rust and there's a reason people say it, even though it's not necessarily literally true.

How do some other languages compare? To begin with, I think, to have a language that feels this way, you have to have a type system. That's where it all starts. Yeah. I do think that even compared to other languages with type systems, I think Rust does a better job than many languages, even others with type systems.

I mean, the classic example is Java, was null. It was Tony Hare, who invented the null, and he called it his billion-dollar mistake, because it's so easy to have, I mean, every time you call a function, you might have a crash in your program. And in Rust, I think they're really good at making sure that when you call a function, there's no chance that it might be null, right? That problem just doesn't exist. So you can't have that kind of crash. And so you have to explicitly say this object might be null, and then the compiler will force you to check for null before you use it. So you can't forget.

Like you can in Java. Can we talk about rust as a whole? This was a language that was created in, 20 years ago, in 2006. And it feels like it's become a lot more popular over time. Do you know of like the scale that Rust is at in terms of usage or popularity or things that along the Russ community, the numbers that are known there? One thing I found kind of funny, I checked here all the day, and we have actually overtaken PhP and Go on the Taobi index. Oh, that index tries to estimate the usage of languages, right?

Usage or popularity or something like that. Wow. Because the feeling I have, again, in general, is that rust is popping up in more and more places, more companies are building on rust. Oxide is a good example. They decide to go all in on rust. And, like, there's a sense of rust is, is becoming. becoming a popular place to build, I guess, high performance applications,

even increasingly contributing to the kernel. As an engineer who might know other languages from TypeScript, Java, etc. What would your pitch be on why it's worth checking out Rust or working with Rust? That depends a lot on which language you're coming from. Let's come from TypeScript. It's one of the most popular languages right now. The pit from TypeScript would be a lot different than the pitch from C++. But okay.

So to begin with, I think when it comes to TypeScript, Rust fits in as the backend language. That's where I would put it. I wouldn't use it in the front end. I think it's a pretty good fit for backend's API servers. One way to put it is you don't want to be waking off at night because there are problems with your web server. You need a language that's reliable that's going to have as few bucks as possible

I mean obviously it would be nice if it had zero bucks but you know it's going to be hard to get there but as few bucks as possible that's the idea of rust I mean I already mentioned null but it does a lot of stuff like that so there's no null checking and this is done through

you know it has this enum type which I mean I think TypeScript can do something similar TypeScript is actually kind of good on that front but okay The other thing I think is quite good is error handling. So on one hand, Russ doesn't really use exceptions. So it actually returns the error as a value.

So you return a value that's either using an enum, either the result or the error. And the way this is done is that there's an operator, question mark, which says, so you write my function and then question mark at the end. And this means if this function fails, return the error. So it's really easy to handle errors, but it's not zero characters like it is with exceptions.

So it's explicit. On the other hand, and if you forget to put the question mark, that's a combination error. Wonderful. So you have to check it. Yeah. Right?

And of course, you can also handle it manually. But the point is, it's this idea of there are these things where you write some code and there's some implicit error condition you didn't think of. And now you just,

you know, took down your server or something. Another thing I quite like is how it handles documentation. How does it? For one, when you have a comment, you make it into a documentation comment by having three slashes instead of two. Now, the thing is, you can, of course, write examples in your documentation.

And Rust makes all examples into tests. This means that if you change the underlying code, now your test fails and so this means that you can't even you can't forget to update your examples in your documentation yeah and I guess there's also things like

you can you forget to initialize a variable in Rust I mean no it doesn't allow you right yeah you have to set a value before you use it for the first time yeah and I guess the things with checking the format of incoming JSON it also forces you to do that

yeah so there's a pretty cool library called Surday in Rust where you have your struct, so your type with fields, and then you can say, I want to be able to parse this from, for example, JSON. And then Surrey will,

it's a macro, it will generate code, which checks the JSON that it's in the same format, it has all the fields you need, and they have the right types, and it generates native code that's specific to that particular shape of JSON, so it's also really efficient.

And again, yeah, and so it helps you avoid errors. and there's this thing which again I learned just very recently thanks to thanks to you as we're talking ahead of this is the switch statement right so in almost every language you have a you have a switch for an enum and you handle cases and then you might have a default or you know everything else and sometimes you forget one of them it's not a big deal or maybe it's a big deal but in rust you cannot do that either right that's right so in rust it's not called switch it's called match but it's the same idea

you can match on your enum and then you can have a branch for each possibility at RANDB and if you are missing one, that's a compiler error. Of course, you can have a catch-all case if you want to, but most of the time you would just list all the cases and then in the future,

when you add a new variant, the compiler will tell you oh, you need to update your code here, here, here, and here. And I think this is kind of leads to another way that Rust really helps with reliability, which is that if you're just that, you're refactoring, I think Rust is really good at telling you all the places you need to update. I've done this sometimes where I would refactor something. I changed the code. I change the return type or whatever it is. And then I just fix the compiler errors until the compiler stops shouting.

And then once I've done that, I've updated every place I need to update. I get a sense that the language designers have thought really hard of what are ways that typically go wrong in a lot of other programming languages, and they just try to fix this to compile. The documentation example is the one where I'm still like, wow. It happens all the time. You have a comment example or not, and then it gets out of sync, and we always complain about this, and we don't know how to fix it. I think we've been, I know I've been complaining for, you know, like a decade plus. This dross is the first language where I hear like an actual solution, even if it's not a perfect one.

And I really think this pattern just everywhere you look, you have this kind of thing again and again that, oh, if you messed up, they, you know, either it won't compile, but at the very least there's a lint for it. They just catch a lot of cases at compile time. And we've had the pitch from TypeScript or similar languages. What about the pitch from C++?

So here I actually think it's even stronger. The thing with C++ plus is that if you make a mistake, right, in JavaScript, maybe you take down your server, which is already bad enough. But in ZEvas plus, when you make a mistake there, now it's actually a security vulnerability, most of the time. If you do something as trivial as you did an off-by-one in your IRA or whatever it might be, that's a security vulnerability. and that this just keeps happening. Small mistakes become security vulnerabilities. And in Rust, so Rust is memory safe, right? I mean, we talked a bunch about different ways

that Rust is more reliable. We didn't even touch about memory safety. Let's talk about memory safety. Memory safety is this idea that no matter how stupid the code you write is, it's not going to have a certain class of bugs. And this is the kind of bug that usually leads it to security vulnerabilities.

You know, the kind of thing where you read past the array and you just look at random memory. Or you destroyed an object and then you used it afterwards. So now you actually touch the memory of some other random object. Yep. And then an attacker who figures this out could populate something there, eventually get that code somehow executed or configuration read, and then boom.

The classic example in the kernel is, let's say you have some object and you manage to make it so that the object that's actually there, right, because the original object is gone. So the memory got reused and now it has a task struct, it's called, and that's basically

your process. And it has a field called user ID. And it's pretty common for code to write zeros to memory. But if you write a zero to the user ID, now you're root. That's a root user. Yeah. that's a really classic way

of exploiting this kind of vulnerability and then once an attacker manages do that they can take over the whatever your server or whatever is running and then of course from there on it can just spiral out of control right

once you're rude you've lost yeah do I understand that a very strong pitch of rust especially coming from C++ is memory safety eliminates this whole class of bugs which are which can turn into security vulnerabilities

which are one of the most serious threats any software can have. Plus all of the reliability ones I mentioned in the beginning. That is a pretty good pitch. We just talked about how Rust offers several safety features like memory safety, error handling, and the type system. This is because reliable is not about one thing, but several things at once.

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So you can easily add determinism and the world's most thorough runtime verification to your reliability arsenal. Go to Hegel.dev to learn more. I'd also like to mention two conferences this year. Well, I'll be talking and where we can also meet. On the 4th of June, I'll be doing a keynote at Craft Conference in Budapest, Hungary. This conference is one of the very best ones in Europe, focused on software craftsmanship, and one where I'm a returning speaker.

For more details, check out Craft-C-Conf.com. And on the 15th and 16th of September, I'll be doing a keynote at LDX3 in New York. This is the festival for modern engineering leadership. Last year, I was at LDX3 in London, and so I'm excited to be back this time in New York. For more details about this conference, head to lead dev.com.

If you'll be at either of them, I'll see you there. And with this, let's get back to Rust and to Alice. I wanted to ask why Rust is getting so popular, but I think we're starting to answer this question, right? I think where Rust is really unique is in the combination of things. So on one hand, it doesn't have a garbage collector, and it's usable in low-level context, like the Linux kernel or firmware or whatever.

Why is it a good or a bad thing to have a garbage collector? Java has a garbage collector, C-Sharp has a garbage collector. So a garbage collector says once you've done using your objects there's going to be a little piece of code that checks all of your objects and says this is not used anymore and then it cleans it up whereas in languages like Rust or C++ plus

the variable is cleaned up at the end of the scope when it goes out of scope and in the other one they have to detect afterwards and this kind of little piece of code that runs every so often to check all your objects for embedded use cases this might simply be not possible or unacceptable. The performance overhead, the fact that you will not be able to control the memory as much.

Even for back-end, it can be a problem because if you have a request incoming right when it checked for all of your objects, like you have some sort of latency spike where it takes much longer to reply. So that's one of the reasons it can be helpful in backend as well. For someone who has not yet seen RustCode, how would you describe it, how it compares to, for example, type script? I mean, in many cases, Rust code is similar to many of the other languages. It has braces.

It's not like Python where you use indentation. It has braces. It has semicolons and so on. So it's pretty easy to read, even if you don't. If you know some similar languages, you can look at it and you can get a rough idea. Yeah, I think you'll figure it out. It's not that. It's not that foreign.

Rust has a learning curve on the side of the more difficult languages to learn. What do you see devs typically strong? with, who are new to Rust, and what are the things that just makes it click for them? I think the most tricky thing people run into is how should you put together your data structure? I mean, for your code, you can mostly do the same things as you can in other languages.

I mean, that's not entirely true, but the big thing is really the data structures. So if you have, I don't know what would be a good example, let's say some sort of, okay, let's just say you have an object for a book and it has an area of pages and then you have an object for each page. If I was writing TypeScript, I would probably have a book field in the page

that references the book and then the book, of course, also references the page. Right, so it's cyclic. So the book goes to the page, goes back to the book. And in Rust, you usually have to design your object so that they're not cyclic.

It has to be a tree or a deck, if you know what that means. Yeah, yeah, the diurek and async graph. So if you go out and actually start to use reference counting, it becomes possible to have cyclic objects with some cavities like you mentioned, but what people end up doing when they're learning the language, is that they try to make cyclic objects without anything like that. And then it just doesn't work.

And they're going to run into all sorts of problems in their code while they're constructing, they're maybe creating their thing, and then they get a compiler error and then they try to change the code and they get a compiler error again. But the thing that a lot of people struggle with is that they keep trying to change the code when the solution is to change the struct.

I can see how that's frustrating. Rust has another model that might be new for, especially for people coming from language to typeship, is Rust's ownership model. What is the ownership model? The ownership is just the idea that if you have a variable containing some object, then the object is only there.

It's kind of exclusive. So, for example, if you have a variable, let A equals your string or whatever, and then you do let B equal to A, then this is a move. And so this means that using A afterwards is now a compiler error because its contents have been moved away.

And of course, this is important when we don't have a garbage collector, because then when B goes out of scope, it has to clean up the string. Now, if A was also valid, then when they both went out of scope, it would clean up the string twice, which is not legal. In most other languages, the garbage collector takes care of this. A and B just go out of scope, do nothing, and then later it cleans up the string. But here, we actually have to do it when we go out of scope. And the ownership model allows you to move from A to B, and then A becomes inactive or unusable, and does not

get cleaned up because it doesn't have a value to clean up anymore. And how does reference counting relate to all of this? In Rust, we have a bunch of different types, which are essentially different kind of pointers. And one of the pointers is it's called arc and it's reference count. And so the idea is you have some object somewhere and then you have an arc to the object. And what you can do is you can call clone on the arc and this increments a counter. And now you have two arcs. to the same underlying memory.

So the object might be really big, but you have two arcs that share the same memory. And when they go out of scope, the counter is just decremented, and when the counter reaches zero, the object is cleaned up. So this is a way of saying, this object actually needs to be in multiple places.

There's no one place that owns it. And so this way you can use a counter to know how many owners are there, and then when the last owner goes away, it gets cleaned up. And on Rust also, another thing that was new to me, the borrow checker. So another pointer type we have in Rust is called the reference.

And a reference is basically all it is that it's a pointer to the object. And that's it. So we do no checking at runtime. So of course, this means that compile time, we have to make sure that the last use of the reference has to be before the object goes out of scope. And creating a reference is called borrowing, right? The owner owns the value, and now we have a borrow of the value, the reference. And the borrow checkout checks that the reference is, like the last use of the references

before the object goes out of scope. So if you have, say, let's say you have an immutable reference, you're reading, then if you change the object, let's say it's a vector. So I have an immutable reference. I'm reading element 5 and then I change the vector I call clear then the borrower checker also ensures that you

can't use the reference to object five afterwards. Yes, because now it has been as soon as you change it, it went out of scope it's now cleared, right? Yeah, the way it works is that if there are mutable boroughs it ensures that

the mutable borrow ends or starts before or after the previous boroughs have ended, basically. So they don't overlap. So you can only have one writer at the time, or you can have any number of readers. It checks that on the scope, like in a function.

This concept is news to me as someone who's not used for us for sure. It's very interesting. One thing I read is on forums, people complaining about so-called fighting the borrow checker, what can make it challenging? When you write some code that uses the object in a way that doesn't follow the rules I mentioned, that's a compiler error.

And fighting the borrower is when you can't get out of those compiler errors, I guess. I think a lot of the time this has to do with the struct. One common mistake I see is that if you have a struct with a reference in it, Rust kind of assumes that it can check the scope of that reference by just looking at a single function. but if you have your struct and you're passing it over functions, it might not be possible to make that analysis. And so you just get a compiler error.

And so in this case, the solution is maybe to use a different pointer type. For example, the reference counterpoint of type often solves this kind of bug. So the solution is, again, to change the data structure. Yeah, I'm starting to understand why you mentioned that data structures were a place of learning coming from other languages. oftentimes the solution seems to be. Just think about your data structures, understand them, and do it in the Rust way, right?

We talk about memory safety, but there is a keyword in Rust called unsafe. What does this do? And in what cases do people typically use? One does it make sense to use them? Why does it even exist? That's just a naive question from me. So let me begin with the what,

and let's take the why afterwards. So the what is, so unsafe is the escape hatch, essentially. So I explained before how there are certain bugs where if your program has one of those bugs, that's usually a security vulnerability. What Rust ensures is that if you have no use of unsafe,

then no matter how stupid your code is, you will never have one of those bugs. Now, if you do use unsafe, then there are still some guarantees, but it's a bit weaker. Because each unsafe operation that you can perform has a list of rules and if you violate these rules,

then you might end up with one of these bad bugs. But of course, if you don't, then you... It's okay. And it's interesting to point out here that unsafe does not disable the borrow checker or anything like that. It just gives you a few more operations you can perform that are not safe in general. And so you have to check yourself

yet this is actually okay in this particular case to... I mean, let's take the vector example. again, normally when you index 5, it will say oh, let me check the length. So if the length is at least 6, is at least 6. Yeah, because it's 0. Then

it's okay, otherwise you get a crash. But maybe you're writing some super high performance code and you want to avoid this if. You want to avoid this check or if you're in a loop every time. So unsafe will just avoid checks.

May that be, is it runtime or compile time checks or both. What I would say here is that vector has two different ways of getting a value. There's the normal bracket operator we'll use for other languages, which will do the check and crash your

program if you get it wrong. But there's another function called get unchecked. And so if you do write vect that get unchecked 5, then it will give you element 5 without checking the length. And this function, like in the function signature, it says

unsafe fn, that's the function signature. And so you can only call this function from an unsafe block. Got it. And so all that the unsafe block lets you do is call functions marked unsafe. And then in practice for sensible use cases of unsafe, is it usually to do with high performance code typically? Or have you seen, like what cases have you seen which are legitimate? This is a great use case for unsafe. So usually it will never show up in, say, a backend server.

you would have zero uses of unsafe there. Generally, when unsafe is used, it's to add a new feature to the language. Let's say the language didn't have a vector. The language still has a function to allocate memory, a function to free memory, a function to read at this pointer address. Then you could write struct,

the pointer is here, and this is a raw pointer, so it's unsafe to use. The length is this, the capacity is this. So I might, and then you can write your little API. Of course, the fields are private, so you can't access them from outside the module. I mean, if I could do vector length equal 20,

just access the field, that would be pretty bad. And so you can write your own vector API, and using field privacy and good API design, you can add a vector to the language if it doesn't already exist. And unsafe, if encapsulate, it properly in this kind of API that doesn't permit you to mess it up, then you can have a safe vector that you can use from Safecode,

and no matter how stupid the thing you do with that vector is, it's not going to do something bad, it's just going to crash or whatever, check the length properly. As long as you design your API right, you can add new language features by using unsafe. The other classic example would be to call into a C library. You can write a library that calls into C, and you can even have a safe API,

and then you can enforce that you only call the CAPI in the right way. Can we talk about the Rust ecosystem, the broader ecosystem? And when it comes to this, the first thing that people come across, including myself, is the crate ecosystem, Rustus package manager. What is crate, and how does it compare to other package managers in places like NPM or PIP in Python? So crate is just the Rust word for a package. So it's just a package.

of your code. So the way it works is that Rust has a tool called cargo, and cargo is kind of, it does a lot of stuff. It's actually pretty neat tool that's kind of all in one. So it will do, it's both what you use to run your code. You do cargo run, and it will compile your code. You have this thing called cargo tumble, where you specify your dependencies and other information about your crate.

And when you do cargo run, it will download the dependencies to something called a registry, which is basically just a directory with all the crate you've ever downloaded. Yeah. And you can also do cargo test. It will run all your tests. Cargo dock.

It will generate your dock. Cargo test will also run your dog tests. There's even benchmarks and examples. So it does all the whole suite, so to say. So you don't need different tools to fetch dependencies and run your code and generate docs. I think the biggest difference from something like PIP would be that,

They're not installed to your machine, right? With PIP, you either install things globally or you have these virtual environments. So with cargo, it's all local. You just run cargo run, and it's only local to this. The only thing that's shared is this registry, which is just to avoid downloading the same thing twice. You told me a funny anecdote about Linus Tor Worlds

and his reaction or what he told you about Rust and cargo. The first time I was at the Linux plumbers conference, at the very end, so Linux wasn't anywhere to be seen throughout the entire conference, but at the very end at the social event, he showed up. And I went over to say hi. I mentioned I worked on Rust, and immediately he started telling me about how he didn't like cargo. And so the reason for that is that cargo downloads code from the internet and runs it,

like any package manager. Yep. And he doesn't want any code in this computer. to do that other than his distributions package manager. He doesn't trust anybody else to do that. In the node world, we're seeing more problems with vulnerabilities being injected into packages, just a bad actor overtaking packages, you know, they put in whatever code might be from crypto, which is, I guess, the better part to security vulnerabilities.

Does cargo have this problem as well, just like any package manager that is on the internet? I mean, in principle, yeah. I mean, ultimately, if you somehow got a hold of, you know, my keys to upload new Tokyo versions, you could upload, I mean, it's just one. I don't think we've had much problems with it compared to something like NPM, but I don't really know if we, I mean, it's a hard problem, right? It's a hard problem. If somebody can impersonate the maintainer of a library, then, I mean, I think they do do stuff like delete, uh, Kiboos, ratting malicious crates and stuff like that. Yeah.

Where do you see the Rust ecosystem being the most mature and the least mature right now? My opinion is that the least mature area is front-end. There have been some attempts to compile Rust to WebAssembly and then run it on the web as a front-end as a replacement for TypeScript. But if I was writing a web server, I would totally use Rust. for the backend and TypeScript for the frontend. I would not really go the WebAssembly route. On the other hand, for backend,

I actually think it's a pretty great fit. And there's also stuff like command line tools. I think it's really, really great fit for that. And then, of course, we are expanding into Linux, and we are also expanding into a lot of embedded projects. And there are even projects that are like C code bases that are starting to say, hey, it's went into Linux. Maybe we should start using it too.

Maybe we should have a memory-sick language too. I know that Git is talking about it. I know that C-Python is talking about it. There are probably others. QEMO maybe. Can we talk about how the language is built? Who builds Rust? What the process for doing it?

How does it compare to a project like Linux? I know it's not a language, but it's still a large open-source project. I mean, it's really an open-source project. I mean, you may, know that it originally originates from Macilla, but it's not a Macilla project anymore at all. So today,

there's the Rust project which has a bunch of different teams. There's the language team, which, you know, deal with the language. There's the library API team, which deals, which decides on the API of the standard library. And these

teams kind of govern it. So it's the people who are on these teams that run the language. And one interesting difference compared to some other popular languages like Python or projects like Linux is they have a benevolent dictator for life. And Russ does not. How is this working on? How are decisions made, especially when they're contagious or what it could help for just someone to just make a decision? Honestly, if the team doesn't sign off on it, it doesn't happen.

I mean, if something is really contentious or really big, it will probably end up being discussed. at a conference. For example, so there's a conference called Rust Week where they have an event called the Rust All Hands

where they're basically taking all of the Rust developers and putting them in one place. So if there was a problem like that, they would probably discuss it there. And how are these teams

structure? So like you said there's a compiler, language, library and deaf tools at the very least. How do they define the boundaries? Is it just a team

kind of roughly defining them and then you just kind of agree. Because as I'm thinking at a corporate level, like as a company would run, there's typically teams are found that often top down, leadership does a mandate, this will be this team, that team. There's bottoms up happening,

but oftentimes it's top down just because it's easier. But here, as I understand, there is no top down. It's people self-organizing. Yeah, really when it comes to the design of the language, the teams are really, that's really it. Teams have been pretty good as far as I've seen at delegating.

So I've seen them sometimes say, we think this is a Lips API decision and we will go with whatever Lips API decides. One thing that is interesting to talk about is the RFC process. So there's requests for process. RFC request for comment is the way the Ross project makes big decisions.

But, you know, big ones, is important to say. Basically, the way it works is, let's say you have a language feature, that's kind of big. For example, I had one called

derived smart pointer which basically make some types in the standard library less special. So I mean, sometimes people

begin implementation already. But the idea is that you write the RFC first. By the way, that's no different inside of like

at Uber we had at RFC process and the same thing. Usually you follow it, but sometimes you kind of

start to build it and then just... The idea is you write the RFC first. Yeah, I know. It's just funny how

happens everywhere where there's engineers, I think. It's the ish to build. You write this dog and it has a template and I think it's actually a pretty good template. The idea is the first section is, I think, motivation. Well, the first one is summary. But the first important one is motivation to explain why this feature. And then I think they have two really interesting sections.

They have the guide level explanation and the reference level explanation. And what this is is that in the guide level explanation, you explain your a feature as if you were writing a guide, as if the feature already existed. And in the reference level explanation, you explain your feature again as if it already existed, but as if it would be in the language reference instead of a tutorial. This is really interesting. You know, Amazon does just relate to this. When they ask people to build a feature, they have a press release.

Like imagine if you announce this. I just love how, like, both this and what you're saying, it forces you to just think from a very different perspective, right, from how people will use this feature. And then other sections, there's, I think you mentioned, rationale alternatives, higher art, future possibilities.

Yeah, so, you know, you get to explain. So rational and alternatives, I think is a pretty important section because you get to answer all of the questions before they get asked and you get to explain, why did you pick this design and that's similar design.

And I think that's usually a pretty big part, part of an IFC. And then, of course, it's good to look at what did C++ do and what can we do in the future as well. And once you have the RFC, you send it out. What happens then? Well, somehow people get people to look at it.

There is an IFC's repository and you can open a pull request there with your MACDN document with the RFC and people can discuss it. You might also write up your dog somewhere else then we call it the pre-IFC if it's not in the IFC directory, but it's kind of the same thing. Let's say that the language team,

like it's a language team, IFC, and they're happy with it. So I said the IFC was how the language makes big decisions. But then they actually use a process that comes up for all decisions, essentially, called the final comment period. And so the idea is they tell the bot to please start their approval process, and then it will rate a comment on GitHub, with a checkbox for every team member. And then team members check their own checkbox.

And once everybody from the team except for at most two have checked their checkbox, then the final comment period will begin, which is two weeks. Oh, so when it's only two checkboxes left, then two weeks to start. What's the rationale for this? This is very interesting.

It's a historic fact more like? I mean, you know, let's say that everybody checks that bog immediately, and then the two other people didn't get a chance to look yet. So it's to make sure that everybody has a chance to see it. Yes, I understand. And also to keep things moving at a sensible pace. So there's another part of the process, which is concerns. Team members can file a concern, which basically pauses the process until it's resolved.

And then once the two weeks pass, it's accepted. So that's essentially how the team makes. decision. And this is not just RFCs. If you have, I don't know, a pull request changing something in the reference, then the language team might say, oh, we need to make sure that everybody is on board with this change. They'll tell the bot to start an FCP on this random PR or some random issue or whatever it might be. The same process applies. And then once, let's say it's this language feature, okay, the RFC is accepted.

We know what we're going to build. Then the feature is just built. You just start to open your pull request. and get into a language? Pretty much. But you put the feature behind a feature flag. In Rust, we have this thing called nightly features, which basically means that you can't use it normally. But if you use the nightly build of the compiler, you can.

Once you have your feature, I mean, you might begin. But, you know, once you have your accepted RFC, you start submitting pull requests, you implement your feature. It gets merged and people start using it experimentally. On an idly build. Yeah. And then at some point, you might say, okay, I think this feature is ready.

And this is kind of a recent invention, but we have come up with this idea of a stabilization report. In the pull request that removes the feature flag, we write up a little report saying, for example, how it's been used and explaining like, oh, here are the dangerous edge cases, here are the tests for each of the dangerous edge, so that kind of stuff.

And then they use the FCP process again to agree to stabilize it, and then it's merged. And so now you have a feature without a feature flag. Yeah. In the main branch. Yes. Between zero days and six weeks from that,

there will be a beta release of the compiler, and it will be... And it will be in it. Yeah, it will be in it. And then six week later, the beta release becomes the next stable release. release. Okay. So like Russ has a strict six-week release cycle, unlike with Linux. Well, Linux also has a rough female, but here you just take the stable bench. You're not doing any special. Yeah. And so we don't really have a concept of beta features that are only available on beta. You have the nightly, pretty much nightly, or people can get onto the latest branch, which is not yet cut. Yeah. The main purpose of beta is to test, like you get six weeks to test the same. stable release. So hopefully if there's any problems, we can fix them before it goes out into a

stable release. And you mentioned that RFCs are only for large decisions that need to be made, and you haven't written that many either just because they're large. What about smaller decisions that you also want to get consensus on? So here, there are a few different ways to do it. So let's say you want to add a new function in the standard library or a new type. Then the library team actually has this thing called an ACP, an API change proposal, which is basically just an issue on GitHub. So you open your issue, you describe your API, describe what the interface is, and explain why you should have it.

And it's much smaller than an IFC would be. And then the library team can say, this is okay with us, and then you can implement it unstable, or nightly. And then later you can then stabilize it. And similarly, the compiler team has, it's kind of a major change proposals. You need to say how it's called. MCPs.

What is going to confuse a lot of people outside of, we're not inside of Rust. Yeah, it is what it is. We shall have with the smaller features. Yeah. Even though it's called major, right? It's big enough that they need you to put up an issue, but not big enough to need an IFC.

And for the compiler team, the classic example, would be a new compiler flag. Now, Russ has new builds every six weeks, right? But it also has additions. There's one in 2015, 2018, 2021, 2024. What are additions? So the thing about additions that is different from versions is that if you're using version 1.90 of the compiler,

everything is using that version. But different crates can use different additions. And so I might have a crate using the 2025 edition of the language. And I can keep using that forever. Because Rust has a really, really high backwards compatibility guarantee. So you write all of your code, and the guarantee is that it's going to keep working forever. That's the idea anyway.

Editions are basically the way that Rust makes breaking changes without breaking people. because they might change the syntax of the language. For example, async await was added to an edition. And so code using the old edition can't use async await. There you could have a variable called async, if you want, let acy equal 5. And then in the new edition, you can't.

But you can still mix and match code written in different editions, so they work together. Oh, interesting. So I might have a library written in the 2021 edition, and you can write your library in 2024 edition or your binary project and then you can still use my library. Why do you think

Russ decided on additions which feels a bit more confusing to me as a developer as opposed to versions like when I look at Java's versions or T.HP's versions or even Ruby on Rails versions there's always a major number and I might be wrong but it sounds to me that an addition is almost

an equivalent of a major version at other languages. Is that putting it correctly or am I missing some details here? Really the big idea is to say, we want the old code to continue working, but we still want to change the language. And so the difference from other kinds of versions of languages, I mean, Python 2 version Python 3 comes to mind, is that you can totally mix and match in any way you want. You are a language team advisor or use and it became one.

What is language team advisor? And what do you do as part of this role? We have, of course, the language team, which, you know, they have meetings every week and they do a lot of stuff and so on and so forth. The language team advisor role is a way to be part of the language team light in some sense. So you're someone that they've said, okay, we trust this person's opinion. but you don't necessarily go to every single meeting. There's no checkbox for you on an FCP, so you can still file a concern.

So, yeah, it's really a way to participate in or help the language team without full membership. And full membership might entail a lot of things, right? For example, for me, it would entail going to meetings every Wednesday evening instead of, like, when I would normally have dinner. From your observation, what is the corporate influence like on Rust in the sense that when I talk with Greg K.H., he was telling me that in practice, about 80% of the frequent Linux contributors are typically employed by a company which sees value in adding their features or maintaining their features in Linux, which turns out to be a nice kind of, I guess, symbiosis in some ways. for Rust, the people working on it, are they usually paid by their employers like you are? I'm sure there's people who are just every now and then contributing with people who are spending more time on this.

Do you see a pattern of corporations actually supporting this or is there a foundation that also supports people to work on this full time or close to full time? I would say here that the Linux kernel is truly unique in this particular aspect, in that they have thousands of contributors doing it on work. time. I actually think that the Rust project is doing pretty well at having people do it and get paid for it, like by their employer, but it's nowhere near to the same extent as the Linux kernel. The Rust project also has a few other interesting things. So the Rust Foundation have some grants that allow, I mean, for example, if you're a student and you want to work on something, you might be able to get a grant, some money from the... the Rest Foundation. I think that's a super cool thing that the foundation is doing.

Especially, I think, getting people and both students involved or, you know, the people who would find it harder or more daunting to get a mobile project like this. Speaking of which, for a software engineer who would be interested to contribute to the ecosystem, what would your suggestion be in terms of both resources or ways to get started? I mean, obviously you can go to the issue tracker and look for issue. that interest you, I think that often it's, I mean, the best way to contribute something

is if you have something you want to change about it. I think that's often a pretty good starting point. So if you wanted to contribute to the Rust language itself, Russ does a lot of its stuff on something called SULIP, which is a chat server where people talk and you could go there and talk to people. So the Rust for Linux project has a pretty nice contribution, page. So rust for Linux.com

and there's a contributing page there. With, for one, there are a few different drivers you might be able to contribute to and they have links to the issue tracker there. Another thing that's really cool is you can contribute to the Linux kernel without contributing to the Linux kernel, right?

Because you might take a Rust language feature we need and implement it. And now you, contributed to the Linux kernel indirectly. Or maybe you want to work on the Rust in GCCC project and help move that forward. And so I think there are a lot of different projects other than the Linus kernel

that would help Rust in the Linux kernel a lot to contribute there. Can we talk a little bit about Rust in the Linux kernel, on how that has evolved, how you got involved in writing Rust in the Linux kernel? and have you seen the approach of especially Linux kernel devs change or soften towards Rusk? Because I know it was a very heated topic earlier on. Linux has this conference called Linux plumbers, which, you know, as part of my work on Rust for the Linux kernel,

I've been going to for the past few years. And one thing I think has been really obvious is every time I've gone, you can say things have totally changed since last year. I've experienced this like four times in a row. That's kind of pretty cool. Yeah, I think there's really a lot of stuff that's happening. I mean, one year I might go and people think, oh, that's some nice little thing you have there, right?

And then the next year, now they have Rust Code in their subsystem. It kind of keeps going. The most recent Linux plumbers from December 2025 was there the big news were that at the Linux kernel maintainer summit, we agreed that Rust is no longer experimental in the kernel. That was really big for us compared to the previous year. So now that means that it's official like Rust has the same status as C, which is the language that the kernel is written in, right?

I guess. Wow. Not the same status, but not being experimental, it clearly marks that it's more stable. Experimental sounds like it's not as stable. Basically, we've proved. this is going to work. I mean, based on what you've laid out with just with memory safety, and of course being able to use unsafe when you need to, that already shows a lot of, I guess,

promise. Plus, there's some regulation as well, right? There's, I think the UNAS Department of Defense passed some regulations saying that they will not allow their agencies to use non-memory safe languages for the concern of security vulnerabilities and this would practically mean that rust and other memory safe languages could be used but C, C++, or

maybe one day systems that are built in this one might see larger scrutiny. Yeah, there have been different stuff like that from multiple different governments, right? These governments are saying, you guys are using C or C++ plus in this project

and it's causing an unacceptable amount of memory safety vulnerabilities that simply don't happen if you just don't. So what if you didn't do that? In this conversation, we managed to go for a very long time without even mentioning AI once, which given where the world right now is and how these tools are spreading. That's pretty impressive. I was interested. Do you use any of the AI tools for your day-to-day work, building Tokyo, contribution?

contribute to Rust projects, have you found a need for them at all? So I have been trying to use them. Honestly, I'm still learning how to use these tools, but I have used them. I quite like the Gemini command line interface. I think it's pretty neat. These tools are pretty proficient at outputting code, or you're giving a prompt and putting out code.

But in your day-to-day work, how much code do you actually type, as opposed to reviewing code, thinking about what to do, making a plan. Because it sounds like, as we're talking about, for example, the RFC process, my sense was most of that was thinking about what to build, getting a consensus, making sure it's right. And it almost sounded like the actual code itself would be the, I don't know, lesser. Of course, you know, there's a lot of work involved, but you see what I mean. The actual time spent will probably less than everything else around it.

I think it's still an important part of the process. I mean, a lot of people talk about that when you use AI, it's really important to write tests and that kind of thing, because then the AI is actually able to tell if it did it right. I explained this story from before about how I was refactoring something. I just did what the compiler told me. I think the same kind of principle applies with agents in that they can talk to the compiler.

it will tell them what to fix. I guess this could be a case. We'll see, but Russ could be a pretty promising candidate to use for agents because they can get more feedback, and it's just harder to ship certain type of bugs or maybe impossible to have certain type of bugs. Yeah, I think there is an aspect of that. For places like the Linux kernel, where, I mean, correctness is extremely important,

reliability is very important. There's already multiple layers of human review, which is in place. Do you see potential for AI generated code to prove helpful somewhere like actually truly helpful? Like again, assuming that these things can generate, you know, as per specification or as per what you need. Or could this be a place where it might be one of the places where we might not need that much? Because it already feels occurring. To me, it feels like a place where there's a lot of people coming in, contributing.

And there's there's a reason that change can propagate. slower. When I was at the Linux Kernel Maintainer Summit, one of the topics that came up was using AI for code review. And there were some people there who had, for example, set up butts that would say when you send an email to the mailing list, it would feed it into an AI agent, which would leave a review. That kind of stuff. And for example, Linus and others

were talking about how these reviews were actually really impressive. for kernel code. At least what's being discussed in the kernel community, that kind of use case seems like something people are excited about. And it sounds like this would not be a replacement, obviously, but just one more way to get feedback, maybe doing quicker, and just additional safety net, if you will, right? I mean, that's the thing with memory safety, right? You make some sort of trivial mistake. It's not some complex thing. It's just you make some trivial mistake and there's a

bigillion places you could make it so even if you're a really good programmer and only make it point one percent of the time or whatever it's still going to happen right and so if the AI can catch a lot of those then you know that's pretty good well and I guess some creative

use cases could be for example their tests are a big thing but AI might be able to help figure out if there's edge cases missing again if the language itself is not supported but there could be what I understand and there could be a lot of potential to add more safety nuts

that do not exist today. I think that's right. I like this approach. So this is one of the first conversations I'm having where we're talking about AI where we're talking about how to increase quality with AI because in, again, in startups or whoever's building,

there's a lot of talk about how it can make it faster, faster iteration, and there's usually a quality trade-off that we usually do not talk about. But I love that. We're actually talking about the things that can increase quality or at least keep it at the same level. I mean, I have actually written a few patches with AI myself. It worked okay. I mean,

it definitely required my review before sending it out to the list. It really did sometimes. But, you know, another place I remember using it was I had this commit that made Binder faster in some way. And one of the review comments I had received was, hey, can you run a benchmark? I said, oh my God, now I have to write a benchmark. But then I got the AI to benchmark. it for me. And what it did, it actually went and found an existing benchmark and modified it a little bit in a quite clever way. And then

it ran it for me and then it wrote a Python script to analyze the text file with the numbers and presented it in a nice table. So it sounds like this was toil work that you could have done, but you might have not been as good of a work because you might have not found that.

You might not figure it out to do that. I mean, at least in that instance, it saved me time if nothing else. For a senior engineer who would like to learn Rust or just build with it, what would your suggestion to get started? Of course, for example, AI might be one of the things, which makes it a lot easier just to get started. But if you would like to learn,

what do you recommend for people who actually want to become profession at the language? So for one, I would say that the Rust book, which is, so it's on the official Rust website, it's actually really good, right? And you don't have to, it's freely available online. Rust has this idea of calling tutorials for books, even though they're online, which is kind of funny.

But anyways, I think the Rust book is really good. Other than that, I think, honestly, the way you learn a language is you have a project. You implement some sort of project. With it, I mean, maybe some sort of web server or something. And one more thing on AI. So it's easy to get started with languages these days because you can just prompt the AI to, like, write this or that.

in the case of Rust, do you think that could create a false sense of understanding, especially we talked about the importance of understanding structures, of understanding compiler issues which are there for a reason? Tools could just generate through this and create code that runs. Yeah, it's totally a danger. I recently tried using it for something where I guess I was not writing Rush Code. I was writing make files. I wanted to add some support in the Linux kernel build system for some feature.

and it went into the make file and added the rust flags necessary to do it but then I looked at the code and it was it had added the necessary built flags but to the seaside it was passing a few more flags which were not required per se but they were there for a reason and it had just ignored them any human looking at this would be like why did you add rust versions of all the flags what is your favorite rust feature if there is one I'm currently working on a new feature, which I think is really exciting. It's something that we ran into in the Linux kernel, where we needed in place initialization,

the ability to construct values while knowing where they're being constructed so they don't get moved afterward. I'm pretty excited about our work to put that into the language, but it's very much ongoing. I think that's pretty cool stuff. And as closing, what are books you would recommend that you've enjoyed and why? I already mentioned the official Rust book. I also think that, so John Gingert has another book that I think is really good. And this book is kind of aimed at the intermediate Rust developer, the Rust developer who has gotten some Rust experience, but wants to go further.

I think that's also a pretty good book for that audience. some other resources, which are not books, but which I think are also really good, is there's this thing called Rustlings. And the idea is that they give you some unfinished Rust Code and your task is to finish it. Oh, nice. And I think that's a pretty cool way to learn the language as well.

Awesome. Alice, thank you so much for this. This was really interesting and I've learned a bunch. Thank you for having me on. I hope you enjoyed getting into the details about Russ as much as I did. One thing I appreciated talking about is how to look virtually Russ seems to have been designed around the question, what mistakes do programmers actually keep making and how do we eliminate those mistakes?

A few examples include memory safety, not having a null, and the errors being values that you cannot ignore. The documentation example is also an interesting one. Documentation tests or doc tests are automatically run as tests. If your example breaks, then you'll build breaks. This is the first time I've heard this clever idea implemented in a way that's easy to use in a language. Finally, the question on why Ross is becoming so popular might be

be because it's in a category that did not exist before, a language that's reliable and also performant at the same time. This makes it usable for high-performance computing cases like kernel work, while also being a good alternative for higher-level backend languages. Do check out the show notes for related, the pragmatic and your deep dives that go even deeper into backend topics and stories of building languages like Kotlin and Swift. If you've enjoyed this podcast, please do subscribe on your favorite podcast platform and on YouTube. A special thank you if you also leave a rating on the show. Thanks and see you in the next. one.