CrewAI makes multi-agent crews and flows a production pattern

Multi-agent products need a runtime shape that is more explicit than a group chat between models. CrewAI's `llms.txt` documents a production-oriented framework for collaborative AI agents, crews, and flows, and points to API endpoints for required inputs, kickoff, resume with human feedback, and execution status. Its docs also expose crew concepts, collaboration, processes, flows, checkpointing, event listeners, files, knowledge, memory, planning, production architecture, tools, MCPs, apps, and skills. For agent builders, the practical signal is to evaluate multi-agent stacks by whether they make team structure, task delegation, workflow control, resumability, memory and knowledge boundaries, event observability, and human feedback loops inspectable through documentation and APIs instead of leaving orchestration hidden in prompts.