Your Finance Agent's Bottleneck Is You

Official Schedule Context

Most "AI for Finance" demos look great and almost none survive past pilot. If you've pushed an agent

past one workflow, one tenant, or one Workday schema, you know the bottleneck isn't the model - it's

the engineer behind the agent, who can't iterate fast enough to keep up with real AP data, real

RBAC, and real query volume. What if you built your dev loop with the same primitives you're

shipping to the finance team? In this talk, I'll show the subagent + skills + MCP stack - a

production multi-agent system over AP, PO, vendor, and multi ERP systems, a LangGraph pattern that

survives production, and the three failure modes that kill finance pilots before they ship.

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

Pending transcript synthesis when an official recording or confirmed matching video is available.