When automating accounting tasks like trial-balance reconciliation, should you build on deterministic code and add AI where needed, or go all-in on autonomous agents? Speaker B warns that agents hallucinate and drift off-track, missing crucial details. The real question is knowing when to trust math and when to trust the model.
people were just calling their modified chatbot an agent or whatever, whether it was OpenClaw experiment, especially I guess what Claude is doing right now, what Anthropic is doing with agents is just amazing. If your tech handles the heavy lifting, I'm wondering, 'cause we were talking a little bit before we came on air about deterministic versus probabilistic. The trial balance has to balance what we know we can automate, sure, but we don't need generative AI to come in and weigh on it. So I'm wondering for you guys, how did you make those decisions and what is your stack without without giving away any, you know, secret sauce proprietary information, but what's the approach you guys took to this is hardcore Python or math that we're doing standard here and this is where we're putting AI in, or are you just leaning more heavily into letting agents run?
So no to the latter half. If you let agents run, they basically make stuff up or head off in the wrong direction. Or my favorite thing, sometimes they miss the forest for the trees and sometimes they miss the trees for the forest. And they do that consistently.
Trust and Leadership Lessons for FP&A From 100+ Top Leaders with CFO Jon Laudie
