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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