Design prompts for AI agents that plan, act, use tools, and iterate toward goals.
An AI agent is a prompt plus a loop. Instead of answering once, the agent plans, acts, observes the result, and iterates until it reaches a goal - often using tools like search, code, or files along the way. The prompt is the agent's instructions, and it determines everything the agent does.
An agent is a prompt plus a loop - the instructions determine the goal, the method, and the safety rules for an autonomous worker.
Agent prompts need three things that ordinary prompts do not: a clear goal, a defined method, and rules for what to do when things go wrong. The goal tells it when it is done, the method tells it how to work, and the guardrails stop it from wandering.
Start with an unambiguous goal. "Research our competitors and produce a comparison report" works because it names the task and the deliverable. Vague goals like "help me with marketing" give an agent no finish line.
Define the method explicitly. Tell the agent which tools to use, in what order, and how many iterations to allow. "Use the web search tool to gather sources, then the analysis tool to score each competitor, then write the report."
Guardrails are the safety net. State what the agent must not do: "Do not invent data; only use cited sources," "Stop if you cannot confirm a number," "Never exceed five search steps." These rules turn a capable model into a trustworthy worker.
The ReAct loop - thought, action, observation, repeat - is the engine most agents run. A well-written agent prompt tells the model to think before acting and to use the observation to plan the next step.
Long-running agents benefit from checkpoints. Ask the agent to summarize its progress at set intervals or after each tool use, so a human can verify it is on track and stop it early if it drifts.
Errors are inevitable, so decide the policy up front. Should the agent retry a failed tool call, switch strategies, or report back to the user? Writing these rules into the prompt prevents infinite loops and silent failures.
Long-running agents benefit from checkpoints. Ask the agent to summarize its progress at set intervals or after each tool use, so a human can verify it is on track and stop it early if it drifts.
Practice by designing a small agent for a bounded task, such as gathering product reviews and scoring them. Write the goal, the method, the guardrails, and the failure policy, then run it and refine.
Vague goals, no iteration limits, missing guardrails, and granting tools without instructions each weaken the agent's reliability.
Design a small agent for a bounded task - write the goal, method, guardrails, and failure policy, then run and refine it.