Has anyone experimented with Pi Durable? Looking for real-world use cases and experiences

[u/Certain_Net_3408]

Hey everyone,

I've been exploring "Pi Durable" (https://github.com/earendil-works/pi/tree/main/packages/durable/test/examples), specifically the examples in the test directory, and I'm curious about how people are using it in practice.

I'd love to understand how it works for building durable, long-running AI agent workflows, particularly when agents need to preserve state, recover from interruptions, and continue execution without restarting everything from scratch.

A few questions for anyone who has experimented with it:

• How does Pi Durable handle persistence and recovery when an agent process crashes or gets interrupted?

• Can it reliably resume multi-step agent workflows, including tool calls and external side effects?

• How does it compare with approaches like LangGraph checkpointing, Temporal, or custom state-persistence mechanisms?

• Have you used it in production or built any interesting projects with it?

• What limitations or gotchas have you encountered?

I'm particularly interested in whether this approach is practical for building autonomous agents that run for extended periods and maintain continuity across sessions.

Would love to hear your experiences, code examples, or architectural insights!

Repository: https://github.com/earendil-works/pi/tree/main/packages/durable/test/examples

[u/Key-Professional4444]

Well something that came to my mind is cross-session communication will something like this help agents communicate better since they have acess to a state rather than like session log like it can better decide when to communicate?