Latent Space: The AI Engineer Podcast
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.
00:05:44 · Mihail Eric
[00:05:44] S1: Yeah. There's a lot of anxiety from students, as you can probably imagine. And I think a lot of what I'm trying to communicate this time around is that the anxiety, a lot of it still is here, and there was anxiety last year as well. But I want to make the case that a well trained AI native engineer, and I know that's like a buzzy but let's see. We'll dive into maybe what aspects that are most interesting. A well trained AI native engineer can be some of the most useful assets, like any company around. And so, this is the first week of class, actually. And like week one, first election, like, I really believe that every company needs you, but the floor is much higher. Right? So you're entering as, like, your first job out of school, but it's not sufficient to just be, like, a, you know, an L three and, like, a Google term, if you're gonna use, like, that that kind of leveling system there. It's like you have to generally be better than, you know, almost at the senior level going to this. So, like, what what can we... How do we get there more quickly? Right? And so, I'm trying to say that there is still a core bit of, like, foundational software engineering that is important to have. Some of these core values of of sort of how software systems are built and the trade offs of those systems. But then beyond that, we go and, you know, that's where I think you as a human should still be valuable rather than... And the rest of the implementation details, you can kind of defer more often.
00:07:02 · Shawn Wang, S2, Mihail Eric
[00:07:02] S0: Yeah. This is something I've said before, which is is almost like the controverse... I I... It's it's like the kind of thing you say to be spicy, but I almost... Like, I I do generally kind of believe it, which is most students are cooked. Some of them are gonna be super valuable. I I don't think it's a very popular thing. Stanford's... Some of... Some these kids are gonna be fine. Right? They're they're from Stanford. But, like, what happens to, like, the rest of America? Right. Right. That that is a [00:07:28] S2: normal a situation, because I feel like a lot of education is slow to move. Like I'm even curious on how do you determine where do you put the end date to curriculum in a course on that? [00:07:39] S0: Oh my God. [00:07:40] S2: You're teaching a Stanford modern software law. Like that's changing everything. [00:07:43] S0: You cheat, You just get the people from the coding agents to come and speak, right? [00:07:48] S1: Oh, Like, yeah, have them be the... Yeah. That's a funny... We [00:07:51] S2: all have guest lecturers.
00:07:51 · S2, Mihail Eric
[00:07:51] S2: all have guest lecturers. [00:07:52] S1: Well, yeah. I mean, that was... Okay. So so on on the guest lecturer's point, I think that was... I mean, that was also last year. That was also the case. So so that was by design because I... Look. I I came in. Right? And I'm saying, I'm a practitioner, as as you pointed out, Swyx. Like, I'm a practitioner. I do this thing on my on my, you know, my day to day. I design these systems. You know, we build we build these things in Monaco and have seen that many times before. And so that that being said, I don't wanna claim that I have all the answers today. And that would be that would be, like, very, you know, a lot of hubris to to make that claim. So the structure of the class was always, here's one practitioner's sort of aggregated set of insights from working in the field, from, like, talking to a lot of people in the field. But then there's people that are, like, literally on the frontier, you know, seeing things even beyond that, and invite them to sort of put their their their proposals forward, their view of the world forward. And that's why the guest does [00:08:45] S2: this I think it's really impactful for students to see big names, people actually doing it, like hear from them directly, be able to like ask them, of course, you know, they want to intern, they want to get jobs. It's good to have guest lecturers.