Agency vs. Control vs. Reliability in Agent Design

They use Customer Service as their domain example. This is an area that I've spent the last decade applying AI/NLP to. 99% of tasks in this domain are fully deterministic - get information about a product, place an order, cancel an order, get status on an order, process a return, troubleshoot a product, etc. These are all well-defined processes that should make use of orchestrated workflows that inject AI at the appropriate time (to determine the customer's intent using a classifier, to obtain information for slot-filling using NER, and lately to return information from a knowledgebase using RAG). Once we know what the customer wants to do and the information required, we execute the workflow. There's no reason to use an "autonomous agent" to engage in reasoning and planning. Unless we just want to drive up token costs for some reason.

At Intercom we've also a lot of experience here.

I disagree, basically. In our experience actual real world processes are not compactly defined, and don't have sharp edges.

When you actually go to pull them out of a customer they have messy probabilistic edges, where you can sometimes make progress a lot faster, and end up with a much more compact and manageable representation of the process, by leveraging an LLM.

We've a strong opinion this is the future of the space and that purely deterministic workflows will get left behind! I guess we'll see.