Building AI Agents with Claude and Tool Use

The Age of AI Agents

AI agents — autonomous systems that can plan, reason, and execute tasks — represent the next evolution of AI applications. Claude's tool use API makes building them accessible to every developer.

What Are AI Agents?

An AI agent is an AI system that can:

• Understand a complex task
• Plan a sequence of actions
• Execute those actions using tools
• Evaluate results and adjust

Building a Research Agent

import anthropic
client = anthropic.Client()
tools = [
    {
        "name": "web_search",
        "description": "Search the web for current information",
        "input_schema": {
            "type": "object",
            "properties": {
                "query": {"type": "string", "description": "Search query"}
            },
            "required": ["query"]
        }
    },
    {
        "name": "read_url",
        "description": "Read the contents of a URL",
        "input_schema": {
            "type": "object",
            "properties": {
                "url": {"type": "string", "description": "URL to read"}
            },
            "required": ["url"]
        }
    }
]
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=4096,
    tools=tools,
    messages=[{
        "role": "user",
        "content": "Research the latest trends in web development for 2026"
    }]
)

Agent Architecture Patterns

ReAct (Reasoning + Acting)

The agent alternates between reasoning about what to do and executing actions.

Plan-and-Execute

The agent creates a full plan first, then executes steps sequentially.

Multi-Agent Systems

Multiple specialized agents collaborate on complex tasks.

Best Practices

• Define clear tool boundaries — each tool should do one thing well
• Implement guardrails — limit what agents can do
• Add human-in-the-loop — for critical decisions
• Monitor and log — track all agent actions
• Handle failures gracefully — agents will make mistakes

Conclusion

AI agents are transforming how we build software. Start with simple tool-use patterns and gradually build more complex agent systems as you gain confidence.