Latent Space: The AI Engineer Podcast
00:15:45 · Shawn Wang, S1
[00:15:45] S0: Do they use ComfyUI? Yes. Oh, wow. [00:15:47] S1: And also and also then they, like, gradually invite more people to learning public and contribute more contributions on online document, which was on the Lark, which was facial under Bai Dansba, which was on the Lark. So everybody contribute their knowledges, share their use cases about stable, efficient, ComfyUI, and then become larger and larger. Actually, think right now, the online community has around a million users learning together and several million users, like, learning together. So become the largest AI community in China as well. So that's also, I think, that happened exactly at the same time, I think you start to feel like you need a... We need a new word for this type of engineer, and then as... Which is you just published the essay of the AI engineer.
00:16:36 · Shawn Wang
[00:16:36] S0: Yeah. I think people... So here are some of the alternatives. I think you can best understand it by the alternatives that people were trying at the time. So there was AI Tinkerers, which is another significant community. I I know Joe and Alex well. And then there are people who are saying LLM engineers or applied AI engineer or all these all these other terminology. And I think, basically, you have to focus on the job title that people want to have. And I think that for us, that was very key. And I think I picked this up from the James Clear. Is it James Clear that wrote Atomic Habits? I think so. I I forget I forget I forget the authorship relationship, but I think it's James Clear. Basically, if you want to deeply understand or connect with somebody, you have to connect with them not on the level of their job, not on the level of their activities or hobbies or whatever, it is their identity. Like, who are you? Right. What what do you aspire to be? If you can give them the path towards being the better version of themselves, then you can build a community around that. And so a lot of non AI people wanted to be in AI. And what is the path for them? While you give them a job title that pays money, Like, then they will be loyal to you. Yeah. Yeah. Yeah. Right. And so so, Yeah. Now there's a lot more AI engineers in the world.
00:18:00 · S1
[00:18:00] S1: Yeah. And to follow-up just to my interest as well. So I know that there are just a lot of works or to do, all right, as an AI engineer. I know you mentioned harness, a of developments happen in the AI. So do you think the role of the world AI engineer has been evolved as well, or is different from what you just mentioned, like three years ago, once you started this
00:18:24 · Shawn Wang
[00:18:24] S0: work? Honestly, it hasn't really changed that much. I think that what's hot within AI Engineering has changed, but the job title is pretty much correct. I think there are people... In the early days, it used to be RAG and managing context and all that. And then more recently, it's been coding agents, it's been harness engineering. It's been maybe loop engineering or whatever. Yeah. There's also other disciplines on memory and all these things. So for those who are interested in all the fields of AI engineering, in AIE World's Fair, which is the the the flagship biggest conference, we have 30 different tracks of what it means to be an AI engineer, and evals is part of that. Multimodal is part of it, you know, all that stuff. So I think it has shifted over time. I think agent engineer maybe is is one of them or AI architect, you know, so AI engineers, like, the individual contributor version of this, but who is, like, the company level, company wide boss, and AI architect is... Seems to be the emerging term for for that that person that decides this is how everybody in the company does AI. Yeah. That's AI architect. So... And then, like, there's there's all the all the other, like, AI designer, AI PM, all these things. So it's just, like, who does that work and who writes code and who is responsible for checking that code? If if something fails, are you responsible? No. You're not an AI engineer. Right. You know, if the the person who wakes up in, 4AM in the morning to go and fix it, that's the engineer. Yeah. Right? And so we wanna serve those people, and that's the real core of it. The other problem with AI is that there's a lot of bullshit. There's a lot of talking heads who have never coded a single day in their lives, but they are very big picture. They're very, very senior. They're like, oh, I'm CTO, blah blah blah. And... But they haven't... They don't touch code. Mhmm. And so a lot of AI conferences and communities focus on those guys because they have big fancy titles, but then they all sound the same. They're all like, oh, my timeline to AGI is, like, two years away. You know, all of you are gonna have... Not gonna have jobs in the future. You need to prepare for what's next. Conveniently, whatever is next looks like their job. So it's very self serving.
00:20:36 · Shawn Wang, S1
And I think that that's one of the reasons that AI Engineer works is that we try to focus on the lower level engineer that usually doesn't get the spotlight, that actually did the work, and is able to talk about all the war stories and share with their fellow engineers about what they're doing. And so I borrowed this idea from other parts, other conferences I've seen in my career, like GDC and KubeCon and JSConf and PyCon and all these other conferences that I've spoken at, where basically it is engineer to engineer, and they are the decision makers for the tech stack, And they are the people who create and innovate the new things, and they're not necessarily the most famous person, but they are definitely correct when it comes to the engineering. There's no bullshit. Right? And I think there's a lot of bullshit in the other things. [00:21:25] S1: Yeah. Yeah. You know, and that comes to the the first AIE Summit that you had organizing, like, three years ago, and then now it's actually a three day full summit with over 7,000 people who joined this year, just just for the audience who are not that familiar with what this event is and different kinds of content stat or workshops or the topics you actually, an AI engineer is caring about. And then how did you actually bring this, like, small event to this such a big event this year?
00:21:56 · Shawn Wang
[00:21:56] S0: AIE World's Fair is basically a similar industry flagship conference similar to the ones that every other industry already has. So gaming has GDC, 30,000 people in San Francisco. Security has two. Security has RSA. Security has Black Hat. If you're in the cybersecurity field, you go to one of those things. Yeah. And that's that's where you learn. I I really like the gaming one because gaming is very similar to labs. You have AAA studios, They work on the hardest games in the world, and it is extreme engineering, and they're all top secret. They don't do anything else. But one time a year, they come to GDC, and they will share, like, this is how I did game of the year. And that's the only way. If you're trying to be a game developer and you wanna work at a AAA game studio, that's the only way you learn. Yeah. So I think that now the model labs are similar to game studios. They have a lot of money. They're working on very, very big major projects. There's a lot of smaller companies that are, you know, trying to compete with them, but the labs are the important ones. And you want to learn from the labs, and where are you gonna learn from them? You know, they they do, like, very small conferences where they, like, they launch, like, Developer Day for OpenAI or Code with Claude for Anthropic, but those are super small and, like, very selective and mostly for customers, and they're not for engineers Mhmm. Talking to other engineers. And then there's, like, 50 other labs that are not open air and topic that also have something interesting. Right? So they... Usually, industry needs one big... Like, everyone comes here, and then you just walk around the room and just talk to everybody. Mhmm. And then they can talk to each other Yeah. Which is very interesting because... Especially for Chinese labs, of whom are on the entity list. Is this something that you guys talk about?