[DataDaemon]

Agentic workflow is great only for demos without real business cases. Each agent can hallucinate, which will pass this hallucination to another agent. In the end, you have just garbage. But... It's better to be silent, we still need to inflate this bubble.

[bwfan123]

there are workflows where the outputs are "narratives" - an example is customer support. another example is summarization of text. characteristic of these use cases is that there is no one right answer. in these use cases agents fit in well.

issue however, is that the agents cannot be chained. ie, chaining requires deterministic outputs and not narratives.

[frgtpsswrdlame]

>characteristic of these use cases is that there is no one right answer

I think what you mean is that they work best in cases where it's very hard to measure how well they are working.

[wpietri]

And where it's also hard to tell who is doing the work! I'm reminded here of psychics and cold readers. They can easily convince people that they have great mental powers by outputting ambiguous text and letting the consumers of it do most of the work. You'll see similar effects with Meyers Briggs tests and other sorts of business astrology: some people feel like they get a lot of value out of them, but rigorous tests don't back that up.