the log is the agent!

This post explores the concept that an agent's log or execution history serves as the primary mechanism for decision-making and learning, suggesting that the sequential record of actions and outcomes is fundamental to how AI agents operate and improve. The post likely discusses how logs can be leveraged for agent transparency, debugging, and self-improvement rather than treating them as mere byproducts of execution. This idea emphasizes the importance of comprehensive logging in agent-based systems for understanding behavior and enabling better performance.

Source: Yohei Nakajima (X) | 2026-07-01