This week, we’re joined by Ivan Burazin, co-founder of Daytona - a company rethinking developer environments for an AI-native world.

We talk about how Daytona creates real value for developers, why the most advanced agent companies are emerging bottom up, and the idea that agents should be treated as first class users with reliable access to compute. Ivan also shares some of Daytona’s most demanding use cases including AI scientists in chemistry and pharma running agents inside massive sandboxes with hundreds of CPUs.

We also cover what reliability looks like when customers define success as whether the system works at all, how Daytona maintains sub 90 millisecond latency while spinning up millions of environments per day, and how they support always on usage with no fixed schedule. Finally, we dig into go to market lessons from putting engineers on the front lines early to why Daytona prioritizes in person engagement and intentional events as the most authentic way to build trust with developers.

Episode chapters:

1:43 – Market timing and why now
3:18 – Building for developers and dev tools
4:55 – Global developer communities
7:55 – Computers as infrastructure for agents
10:32 – Product-led growth
12:17 – Enterprise use cases and adoption
16:25 – Managing cost, performance, and latency
19:20 – Hiring for resiliency at scale
20:40 – Internal AI use cases at Daytona
24:25 – Creating a bottom-up go-to-market motion
27:42 – Hiring and scaling developer relations
29:55 – Partnerships and ecosystem strategy
31:00 – Quick-fire round

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E65: Infrastructure for AI-First Teams with Ivan Burazin (Daytona)