The Esperanto of AI Agents: How the Agent Data Protocol Unifies a Fragmented Ecosystem
Every engineering team has met this problem: the useful data exists, but it lives in thirteen different shapes, three different tool conventions, two incompatible logs, and one heroic spreadsheet that nobody dares to open. AI agents have the same disease, only with more acronyms. The paper behind the Agent Data Protocol, or ADP, argues that large-scale supervised fine-tuning of AI agents has been held back less by a lack of data than by a lack of shared representation.1 Agent datasets already exist for coding, software engineering, web browsing, API use, operating-system interaction, and general tool use. The difficulty is that each one tends to encode actions, observations, tool calls, web states, messages, and execution feedback in its own local dialect. Naturally, every dataset is special. How convenient for nobody. ...