[alittletooraph2]

Temporal’s great! That being said, there is something about being able to orchestrate LLMs and agents using what many already use to orchestrate their data workflows because there’s already proven out reliability, scalability, observability, etc. I’m sure there are boundary conditions for really advanced agentic workflows though…

[acchow]

Temporal is for a static graph with idempotent nodes. Powerful LLM workflows don’t fit this model.

[ldjkfkdsjnv]

Temporal is absolutely not for a static graph, idempotent nodes yes. Please explain your argument more

[tomwheeler]

> Temporal is absolutely not for a static graph

I'd clarify this to say "Temporal is absolutely not limited to a static graph." It can certainly handle a static graph, but it can also handle a dynamic one. Here is an example in Go (https://github.com/temporalio/samples-go/tree/main/choice-mu...), there are similar ones for other languages.

I think the confusion might stem from the determinism requirement in Temporal (and other replay-based Durable Execution platforms). It's not the Workflow Definition (i.e., the code) that must be deterministic, it's the Workflow Execution (i.e., a specific running instance of that code) that must be deterministic. Each running instance is allowed to take a different path through that code, so long as it does so consistently when executed with the same input.