Uploaded May 2026 | Updated September 2026, 2 weeks ago
In this interview from Google I/O, Greg Bagues sits down with Caleb Eom from the popular YouTube channel @CalebWritesCode to unpack the realities of transitioning from a software engineer to a full time AI technical content creator. Caleb explains why deep diving into the five layer AI stack, from top layer agentic coding frameworks to bottom layer LLM inference engines and data center energy requirements, is essential for optimizing token generation speeds and hardware constraints.
This discussion serves as an overview for cloud engineers and systems architects looking to transition their skill sets, follow algorithmic technical niches, and build data center aware AI applications with a comprehensive understanding of localized infrastructure bottlenecks.
Watch more Google I/O Interviews → https://goo.gle/io-tech-chats
🔔 Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#GoogleIO #GoogleCloud
Speakers: Greg Bagues, Tilde Thurium, Caleb Eom
Products Mentioned: Gemini
In this interview from Google I/O, Greg Bagues sits down with Caleb Eom from the popular YouTube channel @CalebWritesCode to unpack the realities of transitioning from a software engineer to a full time AI technical content creator. Caleb explains why deep diving into the five layer AI stack, from top layer agentic coding frameworks to bottom layer LLM inference engines and data center energy requirements, is essential for optimizing token generation speeds and hardware constraints.
This discussion serves as an overview for cloud engineers and systems architects looking to transition their skill sets, follow algorithmic technical niches, and build data center aware AI applications with a comprehensive understanding of localized infrastructure bottlenecks.
Watch more Google I/O Interviews → https://goo.gle/io-tech-chats
🔔 Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech
#GoogleIO #GoogleCloud
Speakers: Greg Bagues, Tilde Thurium, Caleb Eom
Products Mentioned: Gemini
