Integrating non-deterministic, non-durable elements like AI agents into our workflows tends to lead to a lot of do-overs. But restarting AI processes can be costly, burning through tokens and losing valuable progress. Wouldn’t it be easier if there was always a clear checkpoint to restart a task from?

Today I talk with Qian Li, co-founder of the DBOS durable execution engine, about reliability, ergonomics, and actually understanding your software. We discuss the long history of checkpointing, mental models, and how using durable execution allows systems to resume right where they left off after a crash. It makes your software resilient by default.

Learn how this architectural pattern can impact an AI-assisted or any complex system that could use a little improvement in how developers work with it.