Glossary

Terms used throughout this curriculum, defined precisely.


Agent — An AI system that can take autonomous actions (reading files, running commands, making edits) to accomplish a task, as opposed to only generating text responses. In this curriculum, agents are AI coding assistants like Claude Code and Codex CLI that operate within your development environment.

Agentic Development — The practice of building software with AI agents as active collaborators that read, write, and execute code autonomously, rather than using AI only for text completion or suggestions.

AGENTS.md — A configuration file used by Codex CLI (and other tools adopting the open standard) to provide project-specific instructions, conventions, and context to AI agents. Analogous to CLAUDE.md for Claude Code.

Anti-Pattern — A commonly used approach that appears effective but actually leads to poor outcomes — wasted tokens, broken workflows, or unreliable results.

Battle-Tested — The highest maturity rating for patterns in this repository. Indicates the pattern has been validated in production by multiple teams with edge cases documented.

CLAUDE.md — A configuration file placed in a project's root (or subdirectories) that provides Claude Code with project-specific instructions, architecture context, coding conventions, and workflow guidance. The single highest-leverage tool for improving agent performance.

Context Window — The maximum amount of text (measured in tokens) that an AI agent can process in a single session. Managing what goes into this window is a core agentic development skill.

Experimental — The lowest maturity rating for patterns. Indicates the pattern has been tried by 1-2 people and shows promise but lacks broad validation.

Fan-Out/Fan-In — An orchestration pattern where a parent agent delegates multiple independent sub-tasks to child agents (fan-out), then collects and synthesizes their results (fan-in).

Headless Mode — Running an AI coding agent without an interactive terminal session, typically in CI/CD pipelines or automation scripts. The agent receives instructions programmatically and returns results without human interaction.

Hook — A script or command that runs automatically in response to agent events (before/after tool calls, on session start/end, etc.). Used to enforce standards, add logging, or customize agent behavior.

MCP (Model Context Protocol) — An open protocol that allows AI agents to connect to external tools, data sources, and services. MCP servers expose capabilities that agents can discover and use.

Orchestration — The coordination of multiple agents or agent sessions to accomplish a complex task. Includes patterns like pipelines, hierarchies, swarms, and fan-out/fan-in.

Pattern — A named, reusable workflow for accomplishing a specific type of task with AI agents. Each pattern in this repository includes when to use it, when not to use it, and a runnable example.

Plan Mode — A feature in Claude Code where the agent analyzes a task and proposes an approach before making changes. Useful for complex tasks where you want to review the strategy before execution.

Project Memory — The collective set of configuration files (CLAUDE.md, AGENTS.md, etc.) that give an AI agent persistent context about your project across sessions.

Proven — The middle maturity rating for patterns. Indicates the pattern has been used successfully by multiple practitioners.

Sandbox — In this curriculum, a self-contained directory within a module that contains a runnable example demonstrating the module's concepts. Also refers to Codex CLI's sandboxed execution environment.

Session — A single continuous interaction between a developer and an AI agent. Session architecture (how you structure, scope, and connect sessions) is a key skill taught in Module 07.

Sub-Agent — A child agent spawned by a parent agent to handle a delegated sub-task. The parent agent coordinates the sub-agent's work and integrates its results.

Token — The basic unit of text processed by AI models. Roughly 4 characters or 0.75 words in English. Token usage directly affects cost and context window consumption.

Worktree — A Git feature that creates an additional working directory linked to the same repository. Used in agentic development to give agents isolated workspaces for parallel tasks without branch-switching conflicts.