Temporal’s co-founders join Barr Yaron and Lenny Pruss to unpack how durable execution became the backbone of modern distributed apps and why it’s a perfect fit for AI agents. Samar and Max trace the path from Amazon SWF to Uber’s Cadence to founding Temporal, dig into developer experience choices, hard lessons with Cassandra, and what “code that can’t crash” really means in practice. This episode also covers open source strategy, multi-agent orchestration, Nexus RPC, how startups and enterprises are adopting Temporal, and what scaling the company taught them as leaders.

If you ship backend systems, build AI agents, or care about reliability at scale, this one’s for you.

This episode is broken down into the following chapters:

00:00–00:06 — Origins: Samar and Max, Barr and Lenny, why this convo

00:06–00:14 — Early systems: Amazon SWF → Azure Durable Task; DX lessons

00:14–00:23 — Uber years: replacing Kafka, “Jeremy,” birthing Cadence, open-sourcing from day one

00:23–00:31 — Durable execution, explained; code-first over DSLs; SDK ergonomics (Go/Java)

00:31–00:36 — Hard tech war stories: Cassandra, queues on Cassandra, multi-region replication

00:36–00:45 — AI agents ≈ dynamic workflows; why Temporal fits agents and tools

00:45–00:59 — Roadmap: streaming, large payloads, data workflows, Nexus RPC for long-running calls

00:59–01:13 — Adoption & GTM: digital natives, fintech, startups; greenfield AI vs brownfield; “Temporal is overkill?”

01:13–01:22 — Case study: OpenAI Codex on Temporal; internal dogfooding

01:22–01:40 — Scaling the org vs. scaling the tech; remote shift, hiring; mission & next five years

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