# Abstract Agent swarms are a particular area of excitement in AI. Agents collaborating to achieve shared outcomes represents a logical next step in unlocking the true potential of AI and 2025 has been referred to as the “Year of Agents” by industry leading figures. OpenAI in 2024 released experimental frameworks that enable us to explore how early AI agent swarms can manage multiple tasks simultaneously and make quick, informed, and data-based decisions. Their upcoming autonomous AI agent that can control computers and perform tasks independently, code-named “Operator”, will no doubt change the face of human/AI interactions once more in 2025. Likewise, hierarchy in agent swarms sits at the bleeding edge of AI innovation, adding structure to how agents interact and coordinate their efforts. Instead of coordinated agent swarms operating in a flat formation, agents are arranged in levels or roles, with higher level agents typically overseeing or directing lower level agents. The Shadō Network project exists as a collection of open source frameworks that expand possibilities for AI agents, task management, agent swarms and their operational hierarchies. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://shado-network.gitbook.io/shado-network/readme.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.