Thanks Harrison. LangGraph (eg graph theory + Networkx) is the correct implementation of multi-agent frameworks, though it is looking further into, and anticipating a future, then where most GPT/agent deployments are at.
And while structured output and tool calling are good, from client feedback, I'm seeing more of a need for different types of composable agents other then the default ReAct, which has distinct limitations and performs poorly in many scenarios. Reflection/Reflextion are really good, REWOO or Plan/Execute as well.
CIO's or similar. We've been talking to a number of directors at consulting firms who say they are getting calls daily from CIO's who share with them the enormous pressure that they are under, receiving calls from the C-suite and even board of directors asking "what are we doing about generative AI?"
I think you're correct in that its overused, but the jump from using a spreadsheet and programing even the simplest macros, is a big one for a large portion of the those use Excel. Much less using a RDBMS or programming in Python. Even trying the macro recorder makes most users assume 'that's not meant for me'. If the requirement of the job include building a model that can be used and manipulated by anyone than Excel is the only tool for the job, anything else requires more training.