Add three new sections to all 14 examples: - "Carry Forward": what output feeds into later examples (01-10) - "The Cumulative Path": alternative prompt building on previous output (02-10) - "Now Try It Yourself": personalized template with transferable pattern (all) - "Building On" callout connecting back to previous examples (02-10) Add Example 14: Build Your Personal Agent - capstone that guides reader through writing their own CLAUDE.md, creating a personal skill, connecting a messaging channel, setting up automation, and testing end-to-end. Update README with cumulative path diagram, two usage modes, and example 14. Update GETTING-STARTED.md with cross-references to relevant examples. 17 files changed, 703+ lines added. The examples now form a coherent learning path from "see what it can do" to "build your own agent." Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Example 13: Auto Mode
Let Claude Code run autonomously with an AI safety classifier reviewing every action. No manual approvals needed. This is the feature that makes Claude Code feel like OpenClaw's daemon mode.
OpenClaw equivalent: Default autonomous mode with Docker sandbox + exec approvals for dangerous commands.
Requirements:
- Claude Code v2.1.86+
- Team plan or higher (research preview)
Enabling Auto Mode
From the CLI:
claude --enable-auto-mode
In an active session, press Shift+Tab to cycle through
permission modes until you reach Auto Mode.
The prompt
Clone the repository at https://github.com/example/sample-app,
install dependencies, run the test suite, fix any failing tests,
and create a summary of what you changed in CHANGES.md.
What happens
- Claude Code clones the repo (no permission prompt)
- Runs
npm install(no permission prompt) - Runs
npm test(no permission prompt) - Reads failing test output, edits source files (no prompt)
- Re-runs tests until they pass (no prompt)
- Writes CHANGES.md (no prompt)
Every action is reviewed by the safety classifier (Sonnet 4.6) before execution. If an action is flagged as risky (e.g., mass file deletion, data exfiltration), it is blocked and Claude is redirected to take a different approach.
How the safety classifier works
Two-layer system:
- Fast filter: Quick yes/no on the action category
- Chain-of-thought: Detailed reasoning for borderline cases
Performance (Anthropic's internal testing):
- 0.4% false positive rate (safe actions incorrectly blocked)
- 5.7% false negative rate (risky actions not caught)
The classifier runs on Sonnet 4.6 regardless of your session model.
Permission mode comparison
| Mode | Approvals | Safety | Use case |
|---|---|---|---|
| Default | Every action | Maximum | Learning, sensitive projects |
| Auto-edit | Pre-approved patterns | High | Known workflows |
| Auto Mode | AI classifier | High | Autonomous execution |
| Bypass | None | Minimal | Sandboxed environments only |
How this compares to OpenClaw
OpenClaw runs autonomously by default. Safety comes from Docker sandboxing (container limits what the agent can do even if it tries something dangerous).
Claude Code Auto Mode runs autonomously with an AI classifier reviewing each action before execution. Safety comes from pre-execution screening, not post-execution containment.
Different philosophy:
- OpenClaw: "Let it try, contain the damage" (sandbox)
- Claude Code: "Review before executing" (classifier)
Both have trade-offs. Sandboxes catch unknown threats. Classifiers prevent the action from happening at all but may miss novel attacks (5.7% false negative rate).
Now Try It Yourself
Auto Mode works best for well-defined, bounded tasks. Try it on something safe first:
[With Auto Mode enabled]
Read all markdown files in this project. Create a table of contents
in pipeline-output/index.md listing every file with a one-line
description. Verify the file count matches.
The pattern you just learned: Auto Mode removes the permission prompts. Use it when you trust the task scope and want Claude to work without interruption. Start with read-heavy, write-light tasks and expand as you build confidence.
When to use Auto Mode:
- Research tasks where you trust the search and write scope
- File organization within a known project
- Running a tested pipeline end-to-end without babysitting
- Batch processing files with a predictable pattern
When NOT to use Auto Mode:
- First time running an untested pipeline
- Tasks that touch production systems or external APIs
- Anything involving credentials, payments, or irreversible actions