LLM-driven systems that pursue a goal by interleaving reasoning, tool calls, and observations inside a loop — and that decide for themselves which step to take next.
How Codex CLI supports delegating to child agents — the experimental /agent system, codex exec as a sub-agent pattern, MCP-mediated agent-to-agent calls, isolation boundaries, and orchestration patterns.
Build multi-agent AI systems with Microsoft AutoGen. Covers agents, group chats, code execution, tool registration, async runtimes, and LLM configuration.
Orchestrate teams of role-playing AI agents with crewAI. Covers agents, tasks, crews, tools, LLM selection, memory, YAML config, and the kickoff lifecycle.
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