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4 core ways multi-agent AI systems are designed. I’ve explained each one in simple steps below. 1. 𝗣𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 (𝘚𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) • One input (task) comes in. • The task is 𝘀𝗽𝗹𝗶𝘁 𝗶𝗻𝘁𝗼 𝗽𝗮𝗿𝘁𝘀. • Multiple AI agents start working 𝗮𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝘁𝗶𝗺𝗲. • Each agent solves a different part. • Their results are 𝗰𝗼𝗺𝗯𝗶𝗻𝗲𝗱 𝗶𝗻𝘁𝗼 𝗼𝗻𝗲 𝗳𝗶𝗻𝗮𝗹 𝗼𝘂𝘁𝗽𝘂𝘁. Simple example: • One agent writes content • One agent checks facts • One agent improves clarity All work 𝘀𝗶𝗺𝘂𝗹𝘁𝗮𝗻𝗲𝗼𝘂𝘀𝗹𝘆, then results are merged. ____________________ 2. 𝗟𝗼𝗼𝗽 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 (𝘚𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) • Input is given to an AI agent. • The agent creates an output. • That output is 𝗿𝗲𝘃𝗶𝗲𝘄𝗲𝗱 𝗼𝗿 𝗰𝗿𝗶𝘁𝗶𝗾𝘂𝗲𝗱. • Feedback is sent back to the agent. • The agent improves the output. • This cycle repeats until quality is good enough. • Final output is delivered. Simple example: • Agent writes an answer • Another agent reviews it • Feedback goes back • Answer gets refined multiple times ____________________ 3. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 (𝘚𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) • Multiple inputs or tasks exist. • Different AI agents work 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁𝗹𝘆. • Each agent produces its own output. • A 𝗺𝗮𝗶𝗻 (𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿) 𝗮𝗴𝗲𝗻𝘁 collects all outputs. • The aggregator agent 𝗺𝗲𝗿𝗴𝗲𝘀, 𝗰𝗹𝗲𝗮𝗻𝘀, 𝗮𝗻𝗱 𝗳𝗶𝗻𝗮𝗹𝗶𝘇𝗲𝘀 everything. • One final output is produced. Simple example: • Agent 1: research • Agent 2: summary • Agent 3: examples 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿 agent combines everything into one article. ____________________ 4. 𝗛𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝗶𝗰𝗮𝗹 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 (𝘚𝘵𝘦𝘱-𝘣𝘺-𝘴𝘵𝘦𝘱) • A 𝘁𝗼𝗽-𝗹𝗲𝘃𝗲𝗹 𝗮𝗴𝗲𝗻𝘁 receives the input. • This agent acts like a 𝗺𝗮𝗻𝗮𝗴𝗲𝗿. • It breaks the task into smaller tasks. • Assigns each task to 𝗹𝗼𝘄𝗲𝗿-𝗹𝗲𝘃𝗲𝗹 𝗮𝗴𝗲𝗻𝘁𝘀. • Lower-level agents complete their assigned work. • Results are sent back to the top-level agent. • The top-level agent reviews and produces final output. Simple example: • Manager agent plans the project • It delegates the tasks to worker agents • Worker agents handle research, writing, editing • Manager agent assembles final result Very important to understand such fundamentals of multi-agent design patterns. ✅ Repost so others can understand and benefit from this.