jfjeschke

Agreed. I've got a few of them ready to open source. It's almost like there needs to be a reference library of best practices for agent types

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.

Different agents for different situations...

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?"

Where is the tracking data going? Your cloud or theirs? Where are you training the AI's?

This is out there for Excel already, with Cortana... officeautomata.com

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.

What does the tool do exactly?