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11 min read
Lesson 3 of 3AI Agents: From Chatbots to Autonomous Workers0 of 3 complete (0%)

Building Agents with Claude

11 min

What you will learn

  • Use the Claude Agent SDK to build a tool-using agent in Python or TypeScript
  • Define custom tools and integrate them into the agent loop
  • Implement agent memory patterns for multi-step task continuity
  • Evaluate agent performance considering cost, latency, and quality trade-offs
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Building Agents with Claude

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Knowledge check

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What does the `max_turns` parameter do in the Claude Agent SDK?

Key takeaway

The Claude Agent SDK gives you programmatic control over the same agent loop that powers Claude Code — tools, permissions, cost limits, and output streaming. Building agents is accessible, but evaluating them is the hard part: you must measure task completion rate, cost per task, and failure modes to know if your agent is production-ready.

Practice Exercise

Hands-on practice — do this now to lock in what you learned

Open an AI assistant and try this:

If you have Python or Node.js installed, try the Claude Agent SDK quickstart at platform.claude.com/docs/en/agent-sdk/quickstart. Build a minimal agent with one custom tool (even a simple one like a calculator or string formatter). Watch the agent loop in action — seeing the perceive-think-act cycle run in real-time builds intuition that reading about it cannot.

Open in ChatGPT
+10 XP when completed