[AIE Summit Preview #2] The AI Horcrux — Swyx on Cognitive Revolution

**SPEAKER_1** (0:06)
Ladies and gentlemen, it's the Latent Space Weekend Edition.

**Swyx** (0:09)
Woohoo!

**SPEAKER_1** (0:10)
This weekend is a special one, as we are gathering many of our former and upcoming guests and over 10,000 of you for our very first AI Engineer Summit, both in San Francisco and on YouTube. We were interviewed by a few of our fellow AI podcasters about the summit, and figured we would cross post them over the weekend to help you prepare, even if you can't join us in person. Now, we'll have a very current episode recorded with Nathan Labenz of Cognitive Revolution, where we discussed how to hire AI engineers, key tools for AI engineers, skepticism around AI being a fad, the AI engineer conference speaker lineup, and then an hour of AI podcast Inside Baseball around the future of AI agents, multimodal ChatGPT and AI Horcruxes.
While you are listening, there are two things you can do to be part of the AI engineer experience.
One, join the AI engineer summit Slack. Two, take the State of AI Engineering Survey and help us get to 1,000 respondents. Both are linked in the show notes and we would really love to have you. Now here's Swyx's conversation on the Cognitive Revolution.

**Nathan** (1:14)
Swyx, welcome to the Cognitive Revolution.

**Swyx** (1:20)
Nice, I've been a long time listener and very excited to be a first time caller.

**Nathan** (1:24)
Well, thank you.
Glad to have you here and I'm also a big fan of your work with the Latent Space Podcast, the newsletter and also looking forward to what you guys are putting together with the AI Engineer Summit, which is coming up in just a couple of days. So I'm excited to get into all of that with you.

**Swyx** (1:42)
Yeah, happy to dive into that. We did a cross post, I think, a few months ago and I really liked your deep dive into the tiny stories stuff and that's the one that we featured on our feed. And so I feel like you have the room to go much more in depth than us.
So I really appreciate the work that you're doing, going these two hour things with researchers. It's really impressive.

**Nathan** (2:03)
Thank you very much. I really appreciate it. I guess for starters, I thought we'd kind of organize this by taking a little bit of like a broad view survey of your work over the last year or so.
As far as I know, you've coined this term AI engineer.
And so I guess I wanted to start off by just kind of asking you like, what is an AI engineer? I'm fascinated in general by these like new AI jobs, right? We've got the prompt engineer and kind of a few different things have been put forward. Seems like the AI engineer though might have more staying power than like the prompt engineer. So how do you think about that new emerging role?

**Swyx** (2:38)
Yeah, I definitely think of prompt engineering as like slow 2022 and AI engineering as slow 2023 And I feel like this is a controversial take a little bit because everyone should be able to use AI. There is no restriction on who does and does not use AI, but I do think that people who are choosing to specialize in the AI stack probably deserve a full-time role that describes what they do.
And out of all the possible names that people have proposed, like cognitive engineer, LLM engineer, probably the one that is going to win is AI engineer. And so I'm not so much pointing it as observing that this is a trend that's happening and putting all my chips on red, as they say.
So the AI engineer is a software engineer specializing in AI and the emerging AI stack. An ML engineer is not an ML researcher, both of which are much more established roles and much more on the sort of research oriented and ML ops side of the fence. It is everything to do with what happens after you have a model in production. And maybe with a little bit of fine tuning, which is, as everybody knows, just extra training on top of the vast amount of pre-training that has already been done. And I think it's basically an emerging category for a few reasons. It's more or less just demand and supply. And I started life as a finance and economics guy. I was a trader and hedge fund guy for quite a few years before I was a developer. And I just think it's just pure demand and supply. There's maybe like 5,000 good LLM engineers in the world, LLM researchers in the world, and you cannot hire them as the average company, average startup, whatever. There's no way you'll ever actually be able to build this talent in-house.