Context Management

• Key points are in the visual diagram above.

Claude Code survived long sessions because context was engineered, not concatenated.

The SDK is the dishwasher. You still decide what plates go in.

Scenario

The SDK is the dishwasher. You still decide what plates go in.

Solution

In Claude Agent SDK, apply Context Management to this scenario: The SDK is the dishwasher. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Do this before moving to the next module — reading alone is not enough.

Open the Code Walkthrough below and run it locally. Change one parameter related to Context Management (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Highlighted lines show where Context Management happens in the code.

1# Context Management — minimal example2from openai import OpenAI3
4client = OpenAI()  # create API client5
6# Ask the model to explain this topic7response = client.chat.completions.create(  # core API call for Context Management8    model="gpt-4o-mini",9    messages=[10        {"role": "system", "content": "You explain context management clearly."},11        {"role": "user", "content": f"What is context management?"},12    ],13    temperature=0,14)15print(response.choices[0].message.content)  # show output for debugging

• Skipping evaluation for Context Management before production
• No logging or tracing around claude context steps
• Ignoring cost and latency implications

Quick recap — the most important points from this module.