Agentic AI Notebook
Phase 12

Code Execution & Sandboxing

~2 min read

Concept & How It Works

  • Key points are in the visual diagram above.

Learn these elsewhere (not covered in depth here)

  • Sandbox Security — Phase 20

Why Does It Exist?

Unexpected code execution is an OWASP 2026 agentic top risk.

Real-World Analogy

A lab behind glass.
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Visual Workflows

What is Code Execution & Sandboxing?

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Example

Scenario

Scenario (Claude Agent SDK): A user triggers a workflow that depends on Code Execution & Sandboxing. Code execution must be sandboxed: no network unless allowlisted, no secrets, CPU and time caps, workspace root. Your implementation handles the request, logs the step for observability, validates the output, and returns a grounded response — e.g. cutting manual work from 20 minutes to under 30 seconds.

Solution

In Claude Agent SDK, apply Code Execution & Sandboxing to this scenario: Scenario (Claude Agent SDK): A user triggers a workflow that depends on Code Execution & Sandboxing. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Practice Task

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 Code Execution & Sandboxing (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Code Walkthrough

Highlighted lines show where Code Execution & Sandboxing happens in the code.

Code Execution & Sandboxing
1# Code Execution & Sandboxing — 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 Code Execution & Sandboxing8    model="gpt-4o-mini",9    messages=[10        {"role": "system", "content": "You explain code execution & sandboxing clearly."},11        {"role": "user", "content": f"What is code execution & sandboxing?"},12    ],13    temperature=0,14)15print(response.choices[0].message.content)  # show output for debugging

Commands to Remember

Commands to Remember

  • npm install @anthropic-ai/claude-agent-sdk # Claude Agent SDK
  • pip install claude-agent-sdk # Python Claude Agent SDK

Common Mistakes

  • Skipping evaluation for Code Execution & Sandboxing before production
  • No logging or tracing around claude code execution steps
  • Ignoring cost and latency implications

Cheat Sheet

Quick recap — the most important points from this module.

Cheat Sheet

quick ref
  • Code execution must be sandboxed: no network unless allowlisted, no secrets, CPU