AI agents and tool use
AI systems that can take actions, such as searching, running code or using apps, to finish a task.
What is it?
Tool use lets a model do more than write text. The developer describes tools the model may call, such as a web search, a calculator, a database query or sending an email. The model decides when a tool would help, asks for it to be run, reads the result and continues.
An AI agent repeats this loop: it plans, uses tools, checks results and adjusts until the task is done or it needs help. Agents can handle multi-step work like researching a topic or fixing a bug, but they need clear goals, limited permissions and human oversight.
Which models use it?
- OpenAI, Anthropic and Google APIs all support tool (function) calling.
- Coding agents such as Claude Code, GitHub Copilot's agent features and Cursor edit files and run commands.
- ChatGPT and Claude can use tools such as web search and code execution in some plans.
- Frameworks such as LangChain help developers build agent workflows.
How to use it
- Define a clear, limited goal and what "done" looks like.
- Give the agent only the tools and permissions it really needs.
- Require approval before actions that are destructive, costly or hard to undo.
- Let it work in small steps and review progress regularly.
- Check results yourself instead of trusting the agent's own report.
- Keep logs of what the agent did so you can audit and fix problems.
Benefits
- Automates multi-step tasks that plain chat cannot finish.
- Can use up-to-date information through search and data tools.
- Saves time on repetitive work like research, data gathering and code fixes.
- Results can be grounded in real tool outputs rather than memory.
Limits and risks
- Agents can make mistakes that compound over many steps.
- Broad permissions can cause real damage, such as deleting files or sending wrong messages.
- Content from the web or documents can contain prompt injection that tries to hijack the agent.
- Long agent runs can be slow and expensive.
Prompt template
Copy it, replace the parts in [brackets] and paste it into any AI chat.
You are helping me with [task]. You may use these tools: [list tools]. Goal: [clear outcome]. Rules: work in small steps; before any action that deletes, sends, pays or cannot be undone, stop and ask me; never assume a tool succeeded, check its result; if you get stuck, explain why and suggest options. Start by writing your plan.
More in Building with AI
- Using AI through APIsHow apps and scripts send requests to AI models in code instead of a chat window.
- MCP (Model Context Protocol) and connectorsAn open standard for connecting AI assistants to tools and data sources in a consistent way.
- RAG (retrieval-augmented generation)Letting an AI answer from your own documents by finding relevant passages first.
- Embeddings and semantic searchTurning text into numbers that capture meaning, so you can search by idea rather than exact words.
- Fine-tuning vs promptingWhen to customize a model with extra training, and when better prompts are enough.
- Evaluating AI outputPractical ways to check whether AI answers are accurate, useful and safe before you rely on them.