Ian Smith
CTO, LYOS
Atlanta, Georgia, United States
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Ian Smith spent the late 20th century at Georgia Tech in Atlanta GA USA getting a Ph.D. in computer science; he's recovering nicely. Later, he worked at prestigious research labs like Xerox PARC and Intel Research. Recently, he has been working at numerous startups and is currently the CTO and co-founder of LYOS (lyos.com).. He has published more than 30 peer-reviewed scientific publications with thousands of citations, and holds more than 10 US patents. He started using go before there was the error interface.
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Honey, look! I vibe-coded an OS!
Since December 2025, I've built Mazarin, an open-source microkernel OS written in Go with reasonable Linux emulation and a new UI paradigm. 940 commits over 5 months. Zero lines of code written by me. (The title overstates it slightly—but it is a difference only in degree.)
This talk isn't really about Mazarin. It's about how it got built and what that means for you.
Three points:
1. Vibe-coding is a disaster. Human-directed AI coding is a superpower.
The difference is experience. 30 years of it, in my case—enough to make every architectural and strategic decision myself, then farm out the implementation and cross-check the result. I'll walk through specific strategic calls I made and why.
2. The further you get from the code, the more process matters.
Hard problems—virtual memory, for instance—have to be decomposed into chunks the AI can actually handle. Don't expect architectural insight from the tool; treat it as a bonus when it happens. And because you're moving so fast, you need rigorous internal documentation so both you and the AI can remember past decisions and their rationale. I'll demonstrate by live-fixing a bug in Mazarin on stage with my process.
3. Get on the train or get run over.
Pre-AI, Mazarin would have been a 2–3 person, multi-year project. I'm a solo engineer and I have a day job! The force multiplier for senior engineers is going to have profound consequences for junior ones—and a real bottleneck is coming in how we train the next generation of seniors. I'll share job market data, productivity measurements, and my own take. I can't predict the future, but I can tell you what I'm seeing.
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