Explicitly tracking task state in a separate ledger helps agents avoid stale information and policy violations—two major failure modes in tool-calling agents—without requiring model retraining.
LedgerAgent is a method that helps AI agents handle customer service tasks by maintaining a separate record (ledger) of important task information like facts and constraints. Instead of having agents dig through long prompts to find relevant details, the ledger keeps this information organized and visible, and also checks whether tool calls follow domain rules before executing them.