Feature Comparison
| Tutorial | Use when | Output |
|---|---|---|
| 1. Pick the workflow | You are choosing between editor, terminal, IDE, and GitHub-agent work | A tool shortlist mapped to real tasks. |
| 2. Add project instructions | The tool keeps ignoring local patterns | CLAUDE.md, AGENTS.md, Cursor Rules, or Copilot instructions. |
| 3. Run the first agent task | You want a safe trial in a real repo | A reviewed diff, command output, and notes on manual corrections. |
| 4. Add MCP carefully | The tool needs GitHub, browser, database, docs, or design context | A small reviewed mcp.json or client config. |
| 5. Build a review loop | Generated code is plausible but not always trustworthy | A checklist for tests, diffs, risks, and handoff notes. |
| 6. Roll out to a team | Multiple developers will use the workflow | Shared rules, ownership, approval boundaries, and fallback steps. |
Tutorial 1: Pick The Workflow
Before installing anything, write down where the work starts and what artifact you expect at the end. This prevents tool choice from becoming a feature checklist.
Starts in editor -> Cursor, Copilot, Cline, Continue Starts in terminal -> Claude Code, Aider Starts from issue or PR -> Codex, Copilot agents, Claude Code Needs external context -> MCP-enabled workflow
Tutorial 2: Create Repo Instructions
The first configuration file should explain stable project behavior: package manager, test commands, architecture boundaries, style rules, and review expectations.
- Use CLAUDE.md for Claude Code project memory.
- Use .cursor/rules/*.mdc for Cursor project rules.
- Use AGENTS.md when instructions should travel across tools.
- Use .github/copilot-instructions.md for GitHub Copilot.
Tutorial 3: Run A Safe First Task
Pick a small bug fix or test update. Ask the tool to inspect relevant files first, propose a plan, edit only scoped files, and run the narrowest useful validation command.
Prompt template: Find the smallest safe fix for [bug]. Inspect only the relevant files first. Before editing, list the files you expect to touch. After editing, run [test command] and summarize the diff.
Tutorial 4: Add MCP Servers
Add MCP only when it removes real context copying. Start with one low-risk server, verify the command in a terminal, then connect it to the coding tool.
- Start with Filesystem or GitHub for coding context.
- Add Playwright or Browser for frontend verification.
- Keep database servers read-only at first.
- Store secrets outside committed config files.
Tutorial 5: Review The Output
Treat AI-generated code like a junior contributor with unusual speed. Review behavior, not just syntax.
Review checklist: [ ] Did the diff stay in scope? [ ] Are tests or checks included? [ ] Did the tool preserve local patterns? [ ] Are secrets, permissions, or data flows affected? [ ] Is the handoff clear enough for another developer?
FAQ
What is the first AI coding tutorial a team should follow?
Start by documenting one repository's commands and conventions, then run one small real task with a clear validation command.
Should beginners start with Cursor or Claude Code?
Start with Cursor if you want an editor-first experience. Start with Claude Code if you are comfortable in the terminal and want the agent to run commands.
When should I add MCP?
Add MCP after the basic workflow works and only when the tool repeatedly needs external context such as GitHub issues, browser checks, database schema, or documentation.
How do I teach an AI coding tool my project?
Create durable instruction files with commands, architecture notes, coding patterns, and validation expectations. Avoid one-off chat context for rules the team needs repeatedly.