Prompting AI Agents

An AI agent does not just answer once, it works toward a goal over multiple steps. The simple formula is LLM + tools + a loop : it plans, acts, observes the result, and iterates until done.

Learn Prompting AI Agents in our free Prompt Engineering course — a beginner-friendly interactive lesson with worked examples, a practice exercise and a…

Part of the free Prompt Engineering course at LearnCodingFast — hands-on lessons with examples you run in your browser, plus practice exercises and a quick quiz.

This lesson covers multi-step planning, the ReAct (reason + act) loop, reflection and self-correction, and the guardrails and stopping conditions that keep agents safe and on track.

Give the agent a goal and tools. In each turn it reasons, acts, and observes, then loops back. This is the ReAct pattern:

Strong agents pause to review their own work. Asking the agent to critique itself catches mistakes before they pile up:

This reflection step is often the difference between an agent that drifts and one that reliably reaches the goal.

Loops can run forever. Always set limits so the agent stops cleanly and stays within safe bounds:

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Practice quiz

What is an AI 'agent' in this context?

  • An LLM combined with tools and a loop that pursues a goal over multiple steps
  • A single one-shot answer
  • A type of database
  • A human worker

Answer: An LLM combined with tools and a loop that pursues a goal over multiple steps. An agent is an LLM plus tools plus a loop that works toward a goal step by step.

The ReAct pattern stands for…

  • Reading and acting on emails
  • Reacting to errors only
  • Reason plus Act: the agent thinks, then takes an action, and repeats
  • A JavaScript library

Answer: Reason plus Act: the agent thinks, then takes an action, and repeats. ReAct interleaves reasoning and acting in a loop.

Why do agents work in a loop?

  • To avoid using tools
  • So they can plan, act, observe the result, and adjust until the goal is done
  • To waste time
  • Because loops are required by law

Answer: So they can plan, act, observe the result, and adjust until the goal is done. The loop lets the agent take multiple steps and react to each result.

A simple formula for an agent is…

  • A spreadsheet
  • Just a prompt
  • A printer
  • LLM + tools + a loop

Answer: LLM + tools + a loop. An agent is an LLM with tools driven by an iterating loop toward a goal.

What is 'reflection' or self-correction in an agent?

  • The agent reviewing its own progress and fixing mistakes before continuing
  • Restarting the computer
  • Looking in a mirror
  • Deleting the goal

Answer: The agent reviewing its own progress and fixing mistakes before continuing. Reflection means the agent critiques its own work and corrects course.

Why are stopping conditions important for agents?

  • To hide the goal
  • Without them an agent can loop forever or run up cost
  • They are not
  • To make answers random

Answer: Without them an agent can loop forever or run up cost. Stopping conditions prevent endless loops and runaway cost.

Guardrails for an agent typically…

  • Make it faster
  • Remove its tools entirely
  • Translate its output
  • Limit which actions it may take and when to stop or ask for help

Answer: Limit which actions it may take and when to stop or ask for help. Guardrails bound the agent's actions and define safe limits.

Multi-step planning means the agent…

  • Picks a random tool
  • Answers in one shot only
  • Breaks a goal into steps and works through them in order
  • Ignores the goal

Answer: Breaks a goal into steps and works through them in order. The agent decomposes the goal into a sequence of steps.

A good task for an agent rather than a single prompt is…

  • Saying hello
  • A multi-step goal like 'research a topic, gather sources, and write a summary'
  • Echoing a word
  • Counting to three

Answer: A multi-step goal like 'research a topic, gather sources, and write a summary'. Open-ended, multi-step goals benefit from the plan-act-observe loop.

When an agent observes a tool result, it should…

  • Use it to decide the next step or to finish the goal
  • Repeat the same step forever
  • Ignore it
  • Delete it

Answer: Use it to decide the next step or to finish the goal. The observation feeds the next reasoning step toward the goal.