I've been building a workflow engine for agent orchestration and the workflows are just data for the engine to execute. While I haven't experimented with it yet, I envision that an LLM would be rather good at generating the workflows based on a description of your needs (and context about how best to utilise the workflow engine).

LLM's are pretty good at reasoning about workflows, its just that when they have to apply them directly, the workflow context gets muddled with your actual tasks context. That's why using an orchestration agent that delegates work to worker agents works so much better.

I still think there's a huge amount of value in having the workflow executed in a deterministic way (as code, or by a workflow engine) because it saves tokens, eliminates any possibility of not following it, and unlocks other cool things, like being able to give each step in the workflow its own focused task-specific context, splitting plans into individual actions and feeding them through a workflow one by one, and having workflow-step specific verification.

But that workflow absolutely CAN be created by an LLM, it just shouldn't be executed by one.

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