Claude Code: A Practical Introduction

Claude Code is Anthropic's agentic CLI for software development. It runs in your terminal, reads your codebase directly from the filesystem, executes shell commands, calls tools, and works through multi-step coding tasks without you writing each line. It's different in kind from editor-based AI tools like Cursor — the interaction model is more like delegating a task than getting inline suggestions.

For developers encountering it for the first time, Claude Code can feel either impressive or chaotic depending on how it's used. Give it a vague task and it wanders. Give it a precise one and it can handle a refactor in minutes that would have taken an hour. The tool rewards clear thinking about what you want, which is both its design philosophy and the reason teams that adopt it without changing their workflow get disappointing results.

Laxaar has used Claude Code across multiple client projects (internal tooling, API development, test-suite work), and the practical picture is more nuanced than most coverage suggests. This is a ground-level introduction to what Claude Code actually does and where it fits.

How Claude Code works under the hood

Claude Code is an agentic system built on top of Claude (currently Sonnet or Opus depending on your plan). "Agentic" means it doesn't just respond to a single prompt — it plans a sequence of actions, executes them using tools, reads the results, and continues until the task is done or it gets stuck.

The tools it has access to are the ones that matter for coding: reading files, writing files, running shell commands, searching codebases with grep and ripgrep, and managing git. It uses these to understand your codebase before writing anything, which is the core behavior that distinguishes it from a prompt-and-response model.

When you give Claude Code a task, it typically:

Reads relevant files to understand the current state
Plans the changes it needs to make
Implements the changes file by file
Runs tests or build commands if available
Reports what it did and asks if you want to continue

This loop runs autonomously within a session. You can watch it work, interrupt to redirect, or let it run and review the output. The session model is conversational — each turn has access to everything that happened before, including tool call results.

The CLAUDE.md file in your project root is the primary configuration mechanism. Claude Code reads it at session start and treats its contents as persistent context — your architecture rules, naming conventions, off-limits files, and project-specific constraints all go here.

# CLAUDE.md — example project configuration

## Architecture rules
- All database access goes through `src/db/` — never write raw SQL elsewhere
- API routes live in `src/api/routes/` — one file per resource
- Use the shared `AppError` class for all thrown errors (src/lib/errors.ts)

## Do not modify
- src/db/migrations/ — migration files are append-only
- src/generated/ — this is auto-generated, changes will be overwritten

## Testing
- Run `npm test` to run the test suite
- Tests live alongside source files in `__tests__/` directories
- New features require at least one happy-path and one error-case test

Setting up and configuring Claude Code

Claude Code installs via npm and requires an Anthropic API key.

npm install -g @anthropic-ai/claude-code

After installation, set your API key:

export ANTHROPIC_API_KEY=your_key_here
# or add to ~/.zshrc / ~/.bashrc for persistence

Run it from your project root:

claude

You'll get an interactive prompt. Type a task and Claude Code starts working. A few commands worth knowing from the start:

# Start with a specific task
claude "add input validation to the POST /api/users endpoint"

# Ask Claude Code to explain a file before touching anything
claude "explain what src/api/middleware/auth.ts does without making changes"

# Use --print to get output without interactive mode (useful in scripts)
claude --print "summarize the changes in the last 5 commits"

The --dangerously-skip-permissions flag disables the confirmation prompts that appear before file writes and shell commands. Don't use it unless you understand exactly what the agent is going to do. The prompts exist for a reason — they're your chance to catch drift before it lands on disk.

Permissions for which files and commands Claude Code can touch without prompting are configurable in .claude/settings.json. Whitelisting specific read-only operations (like running npm test) avoids constant prompts while keeping write operations gated.

{
  "permissions": {
    "allow": [
      "Bash(npm test)",
      "Bash(npm run lint)",
      "Bash(git diff:*)",
      "Bash(git log:*)"
    ]
  }
}

What Claude Code is genuinely good at

Multi-file refactors with a clear criterion. Renaming a type across 15 files, moving a module, extracting a shared interface from duplicated code — these tasks have a precise success criterion (does it compile and do tests pass?) and a clear scope. Claude Code handles them well and produces reviewable diffs.

Writing tests for existing code. Ask Claude Code to read a module and write tests for it. The output is a useful starting point: it covers the obvious cases, uses your existing test patterns, and imports from the right places. You'll want to review and add edge cases, but the scaffolding is solid.

Implementing a spec with clear interfaces. If you provide a function signature, a description of the behavior, and a pointer to similar existing code, Claude Code can implement it to a level that survives review. The key word is "spec" — the more precisely you define what done looks like, the better the output.

Debugging with reproduction steps. "Here's the error, here's the stack trace, here's the test that triggers it — find the bug." Claude Code can read the relevant files, trace the execution path, and propose a fix. It's not always right, but it's often faster than starting cold.

Documentation generation. JSDoc, README sections, API documentation. Claude Code reads the code and writes accurate descriptions. Not glamorous, but the time savings on documentation work are real and the error rate is low.

Laxaar typically uses Claude Code for these task types on projects where it's been adopted — the throughput gain is clearest in refactoring and test writing, where the agent's speed and the human's reviewing judgment are genuinely complementary.

Where Claude Code struggles

Ambiguous tasks. "Improve the auth module" is not a task Claude Code can do well. It will do something, and it will look plausible, but without a clear success criterion it'll make changes that feel wrong in subtle ways. The ambiguity forces the agent to guess, and its guesses reflect what looks like good code generically, not what's right for your specific system.

Context that doesn't exist in files. Architectural decisions made in conversations, implicit constraints from adjacent systems, the reason a particular approach was chosen and why the obvious alternative was rejected — none of this is in any file. Claude Code doesn't know it. Tasks that require this context produce output that misses the design intent even when the code is technically correct.

Long-running sessions with scope drift. Ask Claude Code to do five things in one session and by the fifth task it's often lost track of constraints it acknowledged at the start. This isn't a failure of the model; it's context window dynamics. Long sessions accumulate tool call results and conversation history that push earlier instructions down. Fresh sessions for fresh tasks is a real discipline, not just a suggestion.

Novel debugging without a reproduction case. "Something is slow in production" without a specific trace, a reproducible test case, or a concrete error message doesn't give Claude Code much to work with. It'll suggest generic performance improvements that may or may not apply. The more specific the debugging task, the more useful the assistance.

Claude Code vs. editor-based tools

Claude Code and Cursor solve different problems. Knowing which to reach for is a practical skill.

Dimension	Claude Code	Cursor
Interface	Terminal / CLI	Editor (VS Code-based)
Best for	Multi-file, multi-step tasks	Inline suggestions, quick edits
Context	Reads full filesystem	Active file + imports
Task model	Agentic (plans and executes)	Completion and chat
Interruption model	Turn-by-turn conversation	Inline accept/reject
Setup	API key + npm install	App download + subscription
Code review flow	Produces diff to review	Inline accept/reject

The developers Laxaar works with often run both. Cursor for daily coding flow where inline suggestions speed up writing; Claude Code for larger tasks where you want the agent to hold context across many files and plan a sequence of actions. They don't compete — they cover different parts of the development workflow.

We cover Cursor's workflow in detail in Cursor: A Practical Introduction and compare both tools directly in Claude Code vs. Cursor.

Getting real value from Claude Code

The practices that actually work, based on Laxaar's use across projects:

Write the task spec before opening Claude Code. Five minutes of writing (the files involved, the interface the output must satisfy, the constraints and out-of-scope areas) produces dramatically better output than describing the task conversationally as you go. Treat this as a required step, not optional.

Use the plan-first workflow. Before Claude Code writes any code, ask it to describe its approach: what files it'll read, what it'll change, what it'll leave alone. Read that plan. If it's wrong, correct it before a line of code is written. Fifteen seconds of plan review saves 30 minutes of rework.

You: "Before writing anything, describe your plan for adding rate limiting 
to POST /api/comments. What files will you read? What will you change? 
What's out of scope?"

Claude Code: [describes plan]

You: [correct or approve]

Claude Code: [implements, now aligned with your constraints]

Gate your review at merge, not mid-session. Let Claude Code run, watch it work, redirect if it drifts badly, but save serious review for when it's done. Interrupting every few steps breaks the agent's context and doesn't improve quality. Review the full diff at the end.

Keep CLAUDE.md current. If you add a new architectural pattern, update CLAUDE.md. If a file becomes off-limits, add it. The file is the agent's persistent memory of your project's constraints — if it's stale, the agent's behavior degrades accordingly.

For team-level adoption, our Claude Code best practices guide for teams covers configuration management, shared CLAUDE.md patterns, and how to integrate Claude Code into existing PR workflows. The agentic coding overview describes how Laxaar structures agent-assisted development for client engineering teams.

Frequently Asked Questions

Is Claude Code safe to run on a production codebase?

It's safe if you use the confirmation prompts. Claude Code asks for permission before writing files and running shell commands — don't skip those prompts. Run it on a feature branch, not directly on main. Review the diff before merging. The agent isn't reckless by design, but it can make changes you didn't intend if the task was underspecified. Treat it like any other tool that touches your codebase: branch, review, merge.

How much does Claude Code cost to use?

Claude Code uses the Anthropic API and you pay per token. The exact cost depends on which model your plan uses and how long your sessions run. A typical multi-file refactor session uses somewhere between 50k and 300k tokens — at Sonnet pricing, that's a few cents to a couple of dollars per session. Monitoring your API usage dashboard in the first few weeks will give you a real number for your specific workflow. Anthropic also offers a Claude Code subscription that includes usage.

Can Claude Code run tests and fix them automatically?

Yes, and it's one of the more useful workflows. Tell Claude Code to run npm test and fix any failures. It reads the error output, finds the failing assertion, and patches the code. The caveat: if the test is testing the wrong thing, Claude Code may patch the code to satisfy the test rather than recognizing the test itself is wrong. Review the changes before accepting — passing tests aren't the same as correct behavior.

How does Claude Code handle large codebases?

It reads files on demand rather than loading everything up front. For large codebases, this means it may miss relevant context in files it hasn't read. Help it by naming the specific files relevant to the task in your prompt. A project CLAUDE.md that maps the architecture (which directory contains what) also helps the agent orient quickly. Codebase size isn't a hard limit, but task specificity matters more on large projects.

What's the difference between Claude Code and the Claude.ai chat interface?

Claude.ai is a conversational interface where you share code by pasting it. Claude Code is a CLI agent that reads your codebase directly from the filesystem, runs commands, and writes files. Claude Code is purpose-built for software development tasks; the chat interface is general-purpose. For coding work that involves real files and running code, Claude Code is the right tool.

Does Claude Code work with any programming language?

It works with any language that can be read as text files, which is all of them. Its quality varies based on how well the underlying Claude model understands the language. TypeScript, Python, JavaScript, Go, and Rust are very well covered. More niche languages work but you'll see more errors in generated code and need to review more carefully. The test-and-fix loop helps regardless of language — it reads the actual error output and iterates.

Want help integrating Claude Code into your team's development workflow? Talk to Laxaar — we help engineering teams adopt agent tools with the practices and configuration that make them productive from day one.