[2026 Edition] The Complete Guide to Claude Code: From Installation to Advanced Techniques
A comprehensive guide covering Claude Code installation, basic operations, practical tips, and pricing plans. Packed with best practices you can apply immediately to real projects — suitable for beginners through intermediate users.
Claude Code is a terminal-based AI coding agent developed by Anthropic. This article systematically covers everything you need to put it to work in a real project — from installation to practical usage.
What Is Claude Code
Claude Code is an agentic AI coding tool that runs in your terminal. It understands your entire project codebase and can generate, edit, and debug code — as well as handle Git operations — end-to-end based on natural-language instructions.
The key difference from traditional IDE autocomplete tools is its ability to autonomously make changes across multiple files. A single instruction like "write tests for this function" or "add error handling" can trigger coordinated edits spanning many files at once.
Installation and Initial Setup
System Requirements
- OS: macOS 12+, Ubuntu 20.04+, Windows (via WSL2)
- Node.js: v18 or higher
- Anthropic account: Pro plan or above (Max plan recommended)
Installation Steps
Run the following command in your terminal:
npm install -g @anthropic-ai/claude-code
After installation, navigate to your project's root directory and run the claude command:
cd your-project
claude
On first launch you'll be prompted to log in with your Anthropic account. A browser window will open automatically; once authentication is complete, control returns to your terminal.
Configuring Your Project with CLAUDE.md
Creating a CLAUDE.md file in your project root lets you pass project-specific rules and context to Claude Code:
# Project Rules
- Write in TypeScript with strict mode enabled
- Use Vitest for tests
- Write commit messages in Japanese
- Match the existing code style
This file is loaded automatically at the start of every session, so you never have to repeat the same instructions.
Basic Usage
Code Generation and Editing
The core of Claude Code is simple: just give instructions in plain language:
- "Create an authentication middleware"
- "Add error handling to this function"
- "Look at the database schema and generate a CRUD API"
When Claude Code receives an instruction, it automatically reads the relevant files and proposes changes. Because you can review changes before they are applied, there is no risk of unintended modifications.
Git Operations
You can also manage your Git workflow with natural language:
- "Commit the changes" → automatically generates an appropriate commit message
- "Create a PR" → handles everything from branch creation to pull request submission
- "Show the diff against the main branch"
Debugging
Resolving errors is another strong suit:
- Paste an error message and say "fix this error"
- "Find out why the tests are failing"
- "Resolve the build error"
Claude Code analyzes the error message, reads the relevant code, and proposes a fix.
5 Practical Tips
1. Use Plan Mode to Design Large Tasks
Before tackling a complex task, use the /plan command to build an implementation plan. Claude Code will organize the files that need to change and the steps required. Reviewing and refining the plan before starting implementation dramatically reduces rework.
2. Automate Repetitive Work with Custom Commands
Create markdown files in the .claude/commands/ directory to define custom slash commands:
<!-- .claude/commands/test.md -->
Please create unit tests for this file.
Cover happy paths, error paths, and edge cases, following the existing test patterns.
Typing /test will produce consistent, high-quality tests every time.
3. Grow Your CLAUDE.md
Add rules and conventions you discover while working on the project to CLAUDE.md. Every team member benefits automatically.
4. Be Mindful of Context
Claude Code retains the conversation history within a session. You can leverage prior context with instructions like "add validation to the function we just discussed." When switching to a new task, however, running /clear to reset the context tends to improve accuracy.
5. Use Sub-agents for Parallel Processing
Claude Code internally uses sub-agents to investigate and modify multiple files in parallel. Even broad instructions like "add rate limiting to all API endpoints under src" are handled efficiently.
Pricing Plans and Cost Estimates
Claude Code runs on Anthropic's Claude subscription plans:
| Plan | Monthly Price | Claude Code Usage |
|---|---|---|
| Pro | $20/month | Available (usage limits apply) |
| Max 5x | $100/month | 5x usage |
| Max 20x | $200/month | 20x usage (for heavy users) |
| API | Pay-as-you-go | Billed per token |
For everyday development, Max 5x ($100/month) offers the best balance. If you work on large-scale refactors or multiple projects, consider Max 20x.
For API access, the Claude Sonnet model costs approximately $3 per million input tokens and $15 per million output tokens.
Comparison with Other AI Coding Tools
Claude Code | Terminal-first agentic tool
Understands the entire project and autonomously makes cross-file changes. Lightweight and fast as a CLI tool. Highly extensible via CLAUDE.md and custom commands.
Cursor | AI-powered IDE editor
An AI editor built on VS Code. Excels at intuitive, GUI-driven workflows. Best suited for work that stays within the editor, such as code completion and inline editing.
Devin | Autonomous AI software engineer
A fully autonomous AI engineer developed by Cognition. Hand it a task and it independently handles everything from design to implementation. Requires minimal human supervision.
Frequently Asked Questions (FAQ)
Q. Is Claude Code free to use?
It requires a Claude Pro plan ($20/month) or higher. It is not available on the free plan.
Q. Does it work on Windows?
Yes, via WSL2 (Windows Subsystem for Linux). Install Node.js inside WSL2 and run npm install -g @anthropic-ai/claude-code as usual.
Q. Can it be used offline?
No. Claude Code communicates with Anthropic's API and requires an internet connection.
Q. Is my private repository code safe?
Code accessed by Claude Code is sent to Anthropic's API, but per Anthropic's privacy policy it is not used to train models.
Q. Which programming languages are supported?
Major languages including TypeScript, Python, Rust, Go, and Java are supported. TypeScript and Python tend to yield the highest accuracy.
Related: securing the skills Claude Code assumes
Claude Code is an agent that takes the terminal as its ground. Reading the diff it proposes, interpreting an error and recovering a broken state all happen at the CLI. How to build that foundation for free is covered in "CLI and programming study in the age of AI coding agents" (WebTerm and WebTerm Learn are both free, and Progate has a Claude Code Introduction (beta) in Japanese).
AI tools featured in this article
Related articles
[2026 Edition] 20 AI Tools Transforming Developer Workflows | Coding Assistance, Automated Code Review, No-Code Web Development, and Workflow Automation
A curated look at the best AI tools for developers in 2026. Covers 18 tools across coding assistance, automated code review, no-code development, and workflow automation — all aimed at improving productivity.
![[2026 Edition] 20 AI Tools Transforming Developer Workflows | Coding Assistance, Automated Code Review, No-Code Web Development, and Workflow Automation [2026 Edition] 20 AI Tools Transforming Developer Workflows | Coding Assistance, Automated Code Review, No-Code Web Development, and Workflow Automation](/_next/image?url=%2Fimages%2Farticles%2Fdeveloper-ai-programming-tools.png&w=3840&q=75)
Top 4 AI Coding Tools Compared | Choosing Between Claude Code, Cursor, Codex, and Antigravity
A side-by-side comparison of the leading AI coding tools — Claude Code, Cursor, Codex, and Antigravity. Guides you to the right choice based on features, strengths, and ideal use cases.

What Jev Is [September 2026]: The AI That Generates No Text — How System One Models Work, Pricing and Use Cases
On 15 September 2026, TypeSafe AI came out of two years of stealth with $40M in funding and shipped Jev — and it spread past social media into developer communities, with Qiita running an official campaign from 16 September to 2 October. What caught on was not the benchmarks but the positioning: an AI that does not generate text. Jev does not chat; it picks from options you defined and returns the answer with a probability attached. This article covers what the three question types (Choice, Score, Noul) actually return, the speculative fan-out that makes stacking questions free in latency, the pricing model of $0.042 per million input tokens with output free, the path from waitlist to Python SDK, HTTP API and the Claude Code skill, how to gate on confidence and route the uncertain cases to a person, and where it pays off — support triage, LLM guardrails, RAG re-ranking. It also covers what TypeSafe publishes about its own weak spots: lower accuracy on CJK scripts, unreliable counting, and weak date comparison.
![What Jev Is [September 2026]: The AI That Generates No Text — How System One Models Work, Pricing and Use Cases What Jev Is [September 2026]: The AI That Generates No Text — How System One Models Work, Pricing and Use Cases](/_next/image?url=%2Fimages%2Farticles%2Fjev-typesafe-ai-guide.png&w=3840&q=75)
CLI and Programming Study in the Age of AI Coding Agents [August 2026]: 11 Services, Starting from the Terminal and Git
With Claude Code, Codex and Cursor in everyday use by 2026, what you need is no longer the ability to write from scratch but the ability to read the diffs an agent produces, interpret its errors and recover a broken state — and all of that happens in the terminal. This article compares 11 learning services — WebTerm, WebTerm Learn, Progate, dotinstall, paiza Learning, ZEN Study, Techpit, Recursion, Boot.dev, KodeKloud and DeepLearning.AI — by entry point (language or environment), format, language support, free tier and price. It also covers the courses rebuilt around agents, including Progate's Claude Code Introduction (beta), KodeKloud's Claude Code For Beginners (8h32m) and DeepLearning.AI's course co-produced with Anthropic, and lays out an order to learn in: environment, syntax, agent, evaluation.
![CLI and Programming Study in the Age of AI Coding Agents [August 2026]: 11 Services, Starting from the Terminal and Git CLI and Programming Study in the Age of AI Coding Agents [August 2026]: 11 Services, Starting from the Terminal and Git](/_next/image?url=%2Fimages%2Farticles%2Fcli-programming-learning-for-ai-coding-agents.png&w=3840&q=75)
Claude Fable 5 vs. GPT-5.5 vs. Gemini 3.1 Pro: Which Should You Choose? A Deep Dive into Performance, Pricing, and Use Cases [July 2026]
A thorough comparison of the latest flagship models from the industry's three leading AI labs, all released in the first half of 2026: Claude Fable 5, GPT-5.5, and Gemini 3.1 Pro. Covers benchmark performance, API pricing, context windows, multimodal support, and how to use them on consumer plans like ChatGPT Plus, Claude Pro, and Google AI Pro — with recommendations by use case, based primarily on official data.
![Claude Fable 5 vs. GPT-5.5 vs. Gemini 3.1 Pro: Which Should You Choose? A Deep Dive into Performance, Pricing, and Use Cases [July 2026] Claude Fable 5 vs. GPT-5.5 vs. Gemini 3.1 Pro: Which Should You Choose? A Deep Dive into Performance, Pricing, and Use Cases [July 2026]](/_next/image?url=%2Fimages%2Farticles%2Fai-model-compare-claude-fable-5-gpt-5-5-gemini-3-1.png&w=3840&q=75)
What Is Claude Fable 5 | A Deep Dive into Anthropic's Latest Frontier Model: Performance, Pricing, and How to Use It
A comprehensive look at Claude Fable 5, Anthropic's latest model released in June 2026. Covers benchmark performance in coding, knowledge work, and science, how it compares to Mythos 5, API pricing, and usage guidance — all backed by official data.
