Meet Shawn Wang (Swyx) 🇺🇸! Swyx is a developer, writer, and startup advisor. If you listen to our show regularly, you know him as the biggest advocate for learning in public! Today, he's the founder of smol.ai and a podcast host and teacher at Latent Space. Last summer, Swyx wrote a blog post titled The Rise of the AI Engineer, which quickly went viral.
In this episode, Swyx will revisit that blog post to see if anything changed. You will learn why AI engineers are a thing, the differences between AI and ML engineers, and why the demand for this specialization is larger than the supply. Swyx also reveals what defines an industry (and why it's not only about tools) and gives many good examples of successful products made using existing foundation models. Swyx and Alex also talk about the inner workings of AI and whether it's a good idea to run AI models on your own hardware.
🔗 Connect with Swyx
⏰ Timestamps
- Swyx wrote a blog post about The Rise of the AI Engineer, and it went viral (02:32)
- The three-stage progression of an AI engineer (04:33)
- Can an AI agent become a CTO? (05:36)
- We can become AI engineers now. What changed? (07:50)
- We didn't invent AI foundation models; we discovered them (11:27)
- Are we evolving new intelligence? (14:20)
- AI researchers vs AI engineers (15:36)
- Why is AI engineering a specialization? (17:04)
- What's an inference API (20:50)
- What are weights (21:09)
- There's a lot of interest in small AI foundation models (24:27)
- Should you use the cloud or run your AI models locally? (25:37)
- Is there a demand for AI engineers? (27:26)
- What AI products do companies want to build? (29:40)
- Updated career advice for new developers (34:51)
🧰 Resources Mentioned
