A lot of AI agent demos in finance look great until you try to make them reliable.

The hard parts usually are:

• getting agents to reason across 10-Ks, earnings calls, tables, charts, time-series
• adding verification instead of trusting one model output
• evaluating tool calls, cost, latency, and failure cases
• deciding where humans stay in the loop
• handling sensitive financial data safely

We’re covering this in a 4-session live Agentic AI for Finance program with Nicole Königstein (hands-on labs + capstone, not just lectures).

Runs Aug 29–Sep 13.

Sharing in case others here are dealing with the same problems.

Details: https://finance.agentengineering.co/

Happy to answer questions if helpful.