AI Agent Starter Guide
Pick your AI coding tool. Master it through interactive exercises, guided tutorials, and real-world prompting techniques.
How to Use Claude Code — Interactive Tutorial
Claude Code is Anthropic's agentic coding CLI that runs in your terminal. Unlike traditional AI chat interfaces, Claude Code can read your entire project, edit files, run commands, and manage git workflows autonomously. Our interactive tutorial teaches you everything from installation to advanced techniques like ultrathink mode for complex reasoning, XML-structured prompts for precise instructions, and the CLAUDE.md project configuration file that gives Claude persistent context about your codebase.
Power users leverage Claude Code's plan mode for architecture design before coding, the memory system for cross-session context, MCP servers for database and API integration, and multi-agent workflows for parallel task execution. Start the interactive Claude Code tour above to learn each technique through hands-on simulated exercises.
GitHub Copilot Tips and Tricks 2026
GitHub Copilot has evolved far beyond simple autocomplete. The latest version includes workspace agents that understand your entire codebase, slash commands for instant code review and test generation, and Copilot Edits for multi-file changes. Our interactive guide covers the most impactful tips including how to write effective chat prompts, configure project-level instructions with .github/copilot-instructions.md, and use the terminal integration for command suggestions.
Many developers miss Copilot's most powerful features. The PR review mode catches bugs before they merge. The @workspace mention lets you ask questions about your entire codebase. Custom instructions let you teach Copilot your team's conventions. Try our interactive Copilot tour to master these features through hands-on practice.
Best Prompts for AI Coding Assistants
The quality of AI-generated code depends directly on prompt quality. Vague prompts like 'fix this bug' produce generic solutions, while specific prompts like 'the login form in LoginForm.tsx does not validate email format — fix it using the isValidEmail function from utils/validators.ts' produce precise, correct code. Our guide teaches universal prompting principles that work across all AI coding tools.
Key techniques include providing file-level context, using XML or Markdown structure for complex requirements, iterative refinement instead of one-shot prompting, and chain-of-thought reasoning for architecture decisions. The interactive exercises let you practice these techniques in a simulated terminal and see the difference in AI responses.
What is Extended Thinking (Ultrathink) in AI Coding?
Extended thinking, activated by keywords like 'ultrathink' in Claude Code, makes the AI spend more time reasoning before responding. Instead of immediately generating code, the model works through the problem step by step — considering edge cases, architectural implications, and alternative approaches. This dramatically improves output quality for complex tasks like multi-file refactors, debugging subtle race conditions, and designing system architecture.
Extended thinking costs more tokens but is invaluable for hard problems. The best practice is to use it selectively: simple tasks like formatting or adding a button do not need it, but architecture decisions, security-critical code, and complex debugging benefit enormously. Our Claude Code tour includes an interactive exercise showing the before-and-after difference that extended thinking makes.
AI Agent Configuration Files: CLAUDE.md, .cursorrules, and More
Every major AI coding tool supports project-level configuration files that provide persistent context. Claude Code reads CLAUDE.md, Cursor uses .cursorrules, GitHub Copilot uses .github/copilot-instructions.md, and Gemini uses GEMINI.md. These files contain your project's conventions, architecture decisions, tech stack details, and rules the AI should follow in every conversation.
Well-written configuration files eliminate the need to repeat instructions. Include your preferred coding style, framework-specific patterns, testing conventions, and explicit rules about what the AI should never do. Our interactive editor exercises let you practice writing effective configuration files for each AI tool.
Cursor AI vs Copilot vs Claude Code — Which to Learn First?
Each AI coding tool excels in different areas. Claude Code offers the deepest agentic capabilities — it can autonomously read files, run commands, manage git, and orchestrate multi-agent workflows from the terminal. GitHub Copilot provides the tightest editor integration with inline suggestions, chat, and PR reviews built into VS Code. Cursor AI combines both approaches as a full AI-first editor with composer mode for multi-file generation.
Choose based on your workflow: CLI-first developers prefer Claude Code, VS Code loyalists prefer Copilot, and developers wanting an all-in-one AI editor prefer Cursor. Our interactive tours for each tool let you experience the differences firsthand through simulated exercises before committing to one.
How to Write Better Prompts for Code Generation
Effective AI prompting for code follows a consistent pattern: state what you want built, provide the specific files and functions involved, define constraints and edge cases, and describe the expected output format. Adding context about your tech stack, existing patterns, and testing requirements helps the AI generate code that fits your project rather than generic solutions.
Common mistakes include being too vague, not providing file paths, asking for too much in one prompt, and not iterating on the output. The best developers treat AI prompting as a conversation — start with the core requirement, review the output, then refine with follow-up messages. Our Universal AI Skills module teaches these principles through interactive before-and-after prompt comparisons.
Frequently Asked Questions
Do I need an AI coding tool installed to use this guide?
No. The guide runs entirely in your browser with simulated terminals and editors. You can learn prompting techniques, configuration patterns, and workflow tips without installing anything. When you are ready to apply what you learned, you can install the AI tool of your choice.
Which AI coding tool should I start with?
If you want the most powerful agentic capabilities, start with Claude Code. If you prefer tight editor integration, start with GitHub Copilot. If you want an all-in-one AI editor, start with Cursor AI. Our AI Model Picker tool can also help you choose based on your specific needs.
Are the tips in this guide up to date?
Yes. The guide is updated regularly to reflect the latest features and best practices for each AI coding tool. Tips are accurate as of April 2026.
How long does it take to complete a full tool guide?
Each tool has 4-6 modules with 3-4 lessons each. A typical module takes about 5-10 minutes. You can complete an entire tool guide in about 30-60 minutes, or work through it across multiple sessions — progress is saved automatically.
What does ultrathink mean?
Ultrathink is a keyword used in Claude Code to activate extended thinking mode. When you include 'ultrathink' in your prompt, Claude spends more time reasoning about the problem before generating code, resulting in higher quality output for complex tasks.
Is my progress saved?
Yes. Your lesson completion and quiz scores are saved in your browser's local storage. When you return to the guide, you can resume from where you left off.
Can I share a specific tip with someone?
Yes. Each lesson has a unique URL that you can share. The URL includes the tool, module, and lesson number, so anyone clicking it will land directly on that specific lesson.
Is this guide free?
Yes, completely free with no signup required. All lessons, exercises, and quizzes are accessible without creating an account.