Latent Space: The AI Engineer Podcast
00:00:00 · Shawn Wang, Mihail Eric
[00:00:00] S0: Okay. This is a pretty special episode because we're celebrating 1,000,000 subscribers on the AI code, AI Engineer YouTube channel. So go over there and subscribe if you haven't heard about it. Or the guest is Mihail Eric, who is not only teaching the modern software developer at Stanford, is going viral right now, for basically covering all the AI native development best practices, but also he is head of AI at Monaco. So he's not only a teacher, but he's a practitioner. And those of you coming to AI Engineer Code Summit next week, it's gonna be the celebration of all the extreme progress that you've seen in coding in the last year. I'm excited about all the themes of fighting slob, of system one models, and of increasing your ambition for major rewrites of basically everything that you've seen in code. There's never been a more exciting time to be an AI engineer. And with 1,000,000 AI engineers, I think it's just getting started. So let's get into the interview. Okay. We're in the studio with Mihail Eric, adjunct professor at Stanford and head of AI at Monaco. Welcome. [00:00:56] S1: Thank you. I'm glad to be here. [00:00:58] S0: You caught our attention because of your course that you are refreshing for the third time... Third time? Second time. Second time? Yep. The CS one forty six... One four six s, the modern software developer at Stanford. [00:01:09] S1: This particular generation of junior developers, of junior engineers, the people that are now entering the workforce, will I think be the first kind of generation of that new shift.
00:01:09 · Mihail Eric, Shawn Wang, S2
[00:01:09] S1: This particular generation of junior developers, of junior engineers, the people that are now entering the workforce, will I think be the first kind of generation of that new shift. [00:01:17] S0: And I looked at the syllabus, and I was like, here's everything we cover. And so every now and then, I like to invite people like yourself who, like... You cover a broad range of topics. Mhmm. And then we can sort of go topic by topic and give people the state of the art on each of these things, which I I assume you're doing with all your guests anyway. For sure. [00:01:35] S2: Tell us the history of the course. What made you wanna spring out CS146S?
00:01:40 · Mihail Eric
[00:01:40] S1: Yes. This is the second time it's being taught. And I taught it for the first time last fall, so fall twenty twenty five. This was pre, like, opus four five, four six days. But even before fall twenty twenty five, the course had been about, like, a year in the making. The genesis of the class was like November 2024, and I had sort of had this idea that we're seeing all this stuff happening in coding agents. And yes, they were an earlier version of the coding agents, but already it felt like there was something drastically changing in terms of how developers were doing their work, how quickly we were getting work done, all that fun stuff. And so, at the time, I just... It was all just scattered blog posts, scattered, like, things you could find online if you were trying to really get into the the methodology of how to do these things. And so I I had this idea, like, hey, well, is there a way to kind of structure a curriculum around this that's a little bit more formal? Had the idea and, you know, I I... My all matter is Stanford, and I always had this dream to go back and teach something and and kind of pay it forward. I've always been very deep into education. I talked to Chip, who also taught a class, one of my friends. Chip, Chip. Yeah. Chip, she exactly. I spoke to her, who had... She had taught her, I guess, designing machine learning systems. And so, like, asked her what that process was like and sort of, you know, took a lot of inspiration from how she designed the curriculum and and thought about, you know, getting something through the school. Put it together, spent about nine to ten months. This was now fall of twenty twenty four through to, like, you know, mid to late of twenty twenty five. Got it through the committee, made a case for the class to exist. You know, I had to put together a proposal and everything. And that took me to fall twenty twenty five when I had it for the first time, which was very well received. You know, students were really interested in it. There was even, I guess, like, a Business Insider article that was written about the class last year. And then, yeah, this year, a lot of things changed. I would say, really, coding agents, autonomous coding agents really picked up in a way that that we had not seen before. So it felt like it was time to do this again, refresh things, and then here we are.
00:03:30 · Shawn Wang, Mihail Eric
[00:03:30] S0: Meanwhile, you're also head of AI at Monaco, which is also a very buzzy startup. [00:03:34] S1: Yes. Yes. We are we are we are... We're in the airwaves right now and and, having a fun time doing it. Yeah. [00:03:39] S0: Yeah. So, like, I I do like that you're also, I guess, a practitioner. You guys are obviously implementing all this stuff in Monaco. Yeah. Any, I guess, principles or observations about just what you have changed from last year to this year at a high level?
00:03:54 · Mihail Eric
[00:03:54] S1: Yeah. Yeah. I mean, a ton. I think that when I reflect on what last year's version of the class was, I mean, coding agents had been around, but we were still in kind of that phase where companies were emerging that were tackling every single part of like the AIS DLC. There was like a coding agent for code review. There was a coding agent for, you know, spec design. There was a coding agent for SRE. And, you know, some of those, of those companies still exist. But it felt like last year, it was a lot more about a broad tour of here's everywhere you can use coding agents. And in a way, lot of the curriculum last year was geared toward exposure and this this kind of survey, this kind of like odyssey of sorts through, hey, everything that you knew about the ASDLC is now changing because of AI. This year, I think there's some principles that are solidifying. Right? The idea of, like, very careful context engineering. The idea of, like, really thinking through sort design and architecture as a way of handling really complex tasks. And so the nature of my class is it's not intended for the, like, beginner programmer. It is not it is not a replacement for, like, traditional computer science in the sense of, like, algorithms and if, in fact, a lot of those classes are prereqs to what I'm what I'm doing here. But I do know that if you have a good foundation, going now toward applying that and and and sort of using those principles in in production environments in, like, real world, that's something that I think is is now at a place where, you know, at Monaco, deal with massive code bases. You know, I help a lot of companies also with thinking through their massive code base, designs and things like that. So, really, it's more of a practitioner's course for once the students have graduated or now entering the workforce, how to be the most productive members of the workforce.
00:05:25 · S2
[00:05:25] S2: You said you're passionate about education. I feel like students in that phase of being in college are in a pretty interesting spot. Any advice and any take? Should people study computer science right now? Is Claude Code and Codex all we need? Like, I wanna hear your thoughts.