A wiki the LLM compiles from the sources in raw/ and the legacy articles, following the conventions in the repository’s CLAUDE.md. Every page lists its sources; pages marked status: draft have not been reviewed yet.
- Domains - Concept pages grouped by domain.
- Sources - One summary page per ingested source.
- Syntheses - Answers filed back from queries.
- Log - What changed and when, newest first.
Concept
- AI adoption maturity - A four-stage ladder from individual chat use to end-to-end processes, driven by growing user fluency, system access, and governance.
- Agent skill - A folder of task-specific instructions and optional resources that Claude Code loads only when a request matches its description.
- Auto Mode - A Claude Code permission mode where low-risk actions run directly and a separate classifier reviews higher-risk ones against user intent and a configured trust boundary.
- Context isolation - Keeping an agent’s intermediate work out of the main context window, at the cost of losing whatever the summary leaves out.
- Claude Code extension mechanisms - How CLAUDE.md, skills, subagents, hooks, and MCP servers differ, and which job each one owns.
- Prompt injection - Instructions hidden in content an agent reads, such as web pages, files, or issue comments, that try to redirect it away from the user’s request.
- Subagent - A worker agent that Claude Code hands a bounded task to, which runs in its own context and returns only a focused result.
Pattern
- AI-native SDLC - A software delivery loop where each stage leaves a committed artifact, agents work between human approval gates, and production evidence returns as new intent.
- Measuring an AI rollout - Judge an AI tooling rollout by comparing concurrent cohorts against pre-set baselines, and lead with expansion rather than hours saved.
- Agents propose, people and policy accept - Route every agent change through pull requests so that required checks, code owners, and approval gates, not the agent, decide what is accepted.
- Risk-based autonomy - Give agents more autonomy on low-risk, reversible work and keep human approval for high-risk and production changes, widening scope gradually.
- Self-improving skill loop - A scheduled agent reads human feedback on another agent’s output and opens a pull request that edits that agent’s skill file.
- Delegation contract - What a subagent must be told up front: when it is used, what its output looks like, and which obstacles it must report.
- Least-privilege tool access - Grant an agent only the tools its job requires, starting from what it must do.
- Progressive disclosure - Expose only a short summary up front and load detailed material into context only when the task needs it.
- When to delegate - Delegate when only the result matters to the main thread; keep work in one context when its intermediate steps matter.
Tool
- Claude Code GitHub Actions - The anthropics/claude-code-action workflow step that runs Claude Code inside a GitHub Actions job, triggered by @claude mentions or a fixed prompt.
- Claude Projects - In the September 2026 redesign, a Claude project is one long-running conversation whose coordinator splits a goal into parallel threads sharing memory and a library.
- Pull request auto-fix - A Claude Code cloud feature that watches a pull request and responds to CI failures and review comments, with known blind spots.
Service
- Claude GitHub App - The GitHub App that gives Claude features repository access, and which features depend on it rather than on other sign-in methods.
- Claude Managed Agents - An Anthropic-hosted agent harness that runs the agent loop, sandbox, and tools for long-running tasks, driven by events instead of your own runtime.
- Cloud session - A Claude Code session that runs on an Anthropic-managed VM instead of your machine, cloning your repository from GitHub and running after you disconnect.
Configuration
- Cloud environment - The saved configuration that sets network access, environment variables, and setup scripts for Claude Code cloud sessions.
- Skill configuration - The SKILL.md frontmatter fields and directory layout that define a Claude Code agent skill.
- Subagent configuration file - The Markdown file with YAML frontmatter that defines a custom Claude Code subagent, and how to create it with /agents.
Command
- Moving work between terminal and cloud - The CLI commands that start, message, and pull down Claude Code cloud sessions, and what each one needs.
Source Summary
- Building an AI-Native Revenue Organization (summary) - Summary of Anthropic’s 2026-09-15 guide and eBook on rolling Claude out across a sales organization.
- The AI-Native SDLC Playbook (summary) - Summary of Anthropic’s 2026-08-21 playbook that redesigns software delivery as a loop of versioned artifacts with human approval gates.
- Introduction to Claude Code Agent Skills (course study guide) - Study guide covering all six lessons of Anthropic Academy’s Introduction to agent skills course.
- How Claude Code Auto Mode Works (video summary) - Summary of Claude’s 2026-08-04 video explaining how Auto Mode reviews higher-risk actions with a separate classifier.
- Claude Code Cloud Sessions (summary of the official docs) - Summary of Anthropic’s Use Claude Code in the cloud documentation, reviewed on 2026-09-18.
- Claude Code GitHub Actions (summary of the official docs) - Summary of Anthropic’s Claude Code GitHub Actions documentation for anthropics/claude-code-action@v1, reviewed on 2026-09-15.
- Claude Managed Agents (summary of the official overview) - Summary of Anthropic’s Claude Managed Agents overview documentation, reviewed on 2026-09-15 while the product was in beta.
- Claude Projects, Redesigned (announcement summary) - Summary of Anthropic’s 2026-09-17 announcement that Claude Projects became one long-running conversation coordinating parallel threads.
- Introduction to Claude Code Subagents (course study guide) - Study guide covering all four lessons of Anthropic Academy’s Introduction to subagents course.
- GitHub Certified: Agentic AI Developer (study notes) - Study notes for GitHub’s GH-600 exam and its Microsoft Learn course, with one architecture module read in full.
- How Warp Builds Self-Improving Agents on Claude (summary) - Summary of an Anthropic post and Warp webinar on agents that improve their own skill files through reviewed pull requests.