AI Agents Explained: the Thought-Action-Observation Loop

📰 Dev.to · Devanshu Biswas

Learn how AI agents use the Thought-Action-Observation loop to solve complex tasks by leveraging LLMs and tools

beginner Published 20 Jun 2026

Action Steps

Define the task and tools for the AI agent
Implement the Thought-Action-Observation loop using an LLM
Test the agent with a multi-step task, such as using a calculator and search
Refine the agent's performance by adjusting tool descriptions and loop iterations
Deploy the agent in a real-world scenario, such as customer service or data analysis

Who Needs to Know This

AI/ML engineers and researchers can benefit from understanding AI agents and their applications, while product managers can explore potential use cases

Key Insight

💡 AI agents combine LLMs, tools, and a loop to achieve autonomous problem-solving

Key Takeaways

Learn how AI agents use the Thought-Action-Observation loop to solve complex tasks by leveraging LLMs and tools

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Title: AI Agents Explained: the Thought-Action-Observation Loop

URL Source: https://dev.to/dev48v/ai-agents-explained-the-thought-action-observation-loop-3mgb

Published Time: 2026-06-20T07:07:51Z

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[Devanshu Biswas](https://dev.to/dev48v)
Posted on Jun 20

# AI Agents Explained: the Thought-Action-Observation Loop

[#ai](https://dev.to/t/ai)[#beginners](https://dev.to/t/beginners)[#llm](https://dev.to/t/llm)[#machinelearning](https://dev.to/t/machinelearning)

A chatbot answers in one shot. An AI agent runs in a loop, uses tools, and acts — Thought → Action → Observation → repeat — until the job's done. Watch one solve a multi-step task by calling a calculator and a search.

🤖 **Run the agent:**[https://dev48v.infy.uk/ai/days/day11-agents.html](https://dev48v.infy.uk/ai/days/day11-agents.html)

## [](https://dev.to/dev48v/ai-agents-explained-the-thought-action-observation-loop-3mgb#agent-llm-tools-a-loop) Agent = LLM + tools + a loop

You describe tools to the model (name, purpose, arguments). It can't divide big numbers reliably or know

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AI Agents Explained: the Thought-Action-Observation Loop

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