𝗔𝗜𝗖𝗵𝗮𝗶𝗻 𝗔𝗴𝗲𝗻𝘁: 𝗣𝗹𝗮𝗻, 𝗔𝗰𝘁, 𝗥𝗲𝗳𝗹𝗲𝗰𝘁

𝗔𝗜𝗖𝗵𝗮𝗶𝗻 𝗔𝗴𝗲𝗻𝘁: 𝗣𝗹𝗮𝗻, 𝗔𝗰𝘁, 𝗥𝗲𝗳𝗹𝗲𝗰𝘁

A Chain follows a set path. You define step one, step two, and step three. It works if you know the steps in advance.

But real tasks are rarely predictable. What if a search returns no results? What if one result changes your entire plan?

This is where an Agent takes over. An Agent plans, observes, and decides. A Chain is a script. An Agent is thinking.

Choose your mode based on your task:

• Waterfall Mode: The Agent builds a full plan before it starts. It runs steps in order. It can retry a step or stop early, but it cannot change the original plan. Use this for predictable tasks like "search, then summarize."

• Agile Mode: The Agent looks at the result of every step. It can rewrite the remaining plan on the fly. If a search reveals new information, it adds new steps. If a task finishes early, it skips the rest. Use this for unpredictable tasks.

To keep costs low and prevent loops, always set a max_steps limit. An Agent without a limit will burn through your budget or run until it crashes.

You can also optimize costs using executors. Use a high-quality model as your orchestrator to handle reasoning. Use a cheaper, faster model as an executor to handle simple tool calls.

A simple rule to follow:

• If you can draw the workflow on a whiteboard, use a Chain.
• If you need to draw "it depends" arrows between different paths, use an Agent.

Source: https://dev.to/yait/aichain-agent-plan-act-reflect-2n71

Optional learning community: https://t.me/GyaanSetuAi