An assistant that works inside your project, not outside it.

Claude is an AI assistant made by a company called Anthropic. It is built on a large language model, a program trained on huge amounts of text, including a great deal of programming material, so that it can read and write both human language and computer code. In an ordinary chat, you talk to Claude in a window, and anything it knows about your project is whatever you paste in.

Claude Code is different in one important way: it is an agent. An agent is a program that does not only answer, but also takes steps toward a goal. It can look at files, search through them, decide what to do next, make changes, run commands, read the results, and try again. You describe the goal in plain words, such as “find out why the login page is slow” or “add a search box to the products page”, and it works toward it while keeping you informed.

Software work is full of time spent on things that are not the real thinking.

Anyone who builds software knows the feeling. A large part of the day goes into searching, reading, and repeating: finding where something is defined, working out what a confusing section does, making the same small change in twenty places, writing routine tests, tidying up. These tasks need care but not much creativity. They crowd out the work that does need a human: deciding what to build, weighing trade-offs, and understanding the people who will use the product.

Eighteen short definitions that make everything else easy.

The same assistant, available in several places.

Claude Code started in the terminal, the text window where many developers work. Over time it has also become available in other places, which suit different habits. The exact list changes, so check the official documentation for what exists today, but the general picture is as follows.

Ten kinds of jobs, from reading to releasing.

flowchart TD
    CC["Claude Code"] --> U["Understand: explore and explain a project"]
    CC --> W["Write: create features and files"]
    CC --> F["Fix: find and repair bugs"]
    CC --> T["Test: write and run checks"]
    CC --> R["Refactor: tidy and restructure"]
    CC --> D["Document: explain in plain words"]
    CC --> G["Version control: commits, branches, reviews"]
    CC --> A["Automate: repeated chores"]
    CC --> I["Integrate: connect to other tools"]
    CC --> L["Learn: guide a newcomer through the code"]
    

Often the most valuable first use: understanding before changing.

Imagine opening a project you have never seen. Claude Code can search through the files, read the important ones, and give you an explanation in plain language: what the project does, how it is organized, which folders hold what, how a request travels from the user’s click to the database, and where a particular feature is handled. Because it can read many files quickly, it can answer questions that would take a person hours of searching.

From a plain-words request to working changes across several files.

You can describe a feature in ordinary language, such as “let users export their orders as a spreadsheet”, and Claude Code can plan the work, find the places that need changes, write the new pieces, edit the existing ones, and connect them. Because it sees the project as a whole, it can follow the style and conventions already used, rather than inventing its own.

From an error message to a cause and a repair.

When software breaks, it often shows an error message: a few lines saying what failed and where. To a beginner, these messages can look like another language. Claude Code can read the message, search the project to find the code involved, work out why it failed, suggest a repair, and check that the repair works by running the program or its tests again.

flowchart TD
    A["You report the problem or paste the error message"] --> B["Claude Code reads the message"]
    B --> C["Searches the project for the related code"]
    C --> D["Forms a theory about the cause"]
    D --> E["Checks the theory by reading code or running a command"]
    E --> F{"Theory confirmed?"}
    F -->|"No"| D
    F -->|"Yes"| G["Proposes and makes a fix"]
    G --> H["Runs tests or the program"]
    H --> I{"Fixed with nothing else broken?"}
    I -->|"No"| D
    I -->|"Yes"| J["Reports what it found and changed"]
    

Because quick changes need quick checking.

A test is a small automatic check. For example, a test might confirm that adding two items to a basket gives the right total. Projects with good tests are far safer to change, because the tests shout when something breaks. Writing tests is useful but repetitive, and Claude Code can help create them, run them, and explain failures.

Making code clearer without changing what it does.

Refactoring means reorganizing code so that it is easier to read and maintain, without changing its behavior. Examples include giving things clearer names, splitting a very long section into smaller parts, removing repeated code, and updating old patterns to newer ones. These are broad, repetitive changes across many files, which is exactly the kind of work an agent can do tirelessly. They are also risky, because a small slip can change behavior, so good tests make them far safer.

Keeping a clean history of what changed and why.

Most projects use a tool called Git to keep a history of every change. Each saved snapshot is a commit, each separate line of work is a branch, and each proposal to bring a branch into the main project is a pull request. Using these tools well takes practice, and the commands can be confusing. Claude Code can help with the routine parts: looking at what has changed, writing a clear description of the changes, creating commits, switching branches, and drafting a pull request description for reviewers.

Words that make code understandable to the next person, who may be you.

Documentation is the writing around code: guides for how to install and run the project, descriptions of how parts work, and notes about decisions. It is easy to neglect because the code seems to work without it. But projects with poor documentation are slow for everyone. Claude Code can read the code and draft clear explanations, then update them when the code changes.

Small jobs that eat up time can be handed over.

Beyond one-off tasks, Claude Code can help with chores that come up again and again. Updating the same pattern in fifty files, converting a batch of files to a new format, checking that notes follow a template, preparing a weekly summary of what changed. Some setups also let it run without a person present, started by a schedule or by another program, for jobs like regular reviews or reports. What is available depends on the version and plan, so check the documentation.

A patient tutor that can look at your actual code.

For learners, Claude Code can be a tutor that works on real material. You can ask it to explain a function line by line, to describe a new concept using your own project as the example, to suggest small exercises, and to review your attempts with kind but honest feedback. For teachers and team leads, it can prepare explanations, sample tasks, and notes for newcomers.

Gather, act, check, repeat.

Under the surface, Claude Code follows a simple loop. It reads your request and looks at the available context. It decides on the next step, such as reading a file or searching. It uses a tool to do that step. It reads the result, which becomes new context. Then it decides again. The loop continues until the goal seems met or it needs your input.

flowchart TD
    A["Your request"] --> B["Gather context: read files, search, look at results"]
    B --> C["Decide the next step"]
    C --> D{"Is a tool needed?"}
    D -->|"Yes"| E["Use a tool: read, search, edit, or run a command"]
    E --> F{"Does this need your permission?"}
    F -->|"Yes"| G["Ask you to approve or deny"]
    G -->|"Approved"| H["Carry out the step"]
    G -->|"Denied"| C
    F -->|"No"| H
    H --> I["Read the result"]
    I --> C
    D -->|"No, ready to answer"| J["Report to you: what was done and why"]
    

What the agent actually uses to read, change, and run things.

Claude Code uses a set of built-in tools, and each is simple on its own. The power comes from combining them. Exact names and the full list change over time, so this is a general picture.

A limited desk, used wisely.

Claude Code, like all language models, can keep only a limited amount of text in view at once, called the context window. Files it reads, commands it runs, and the whole conversation all take space. In a big project, it cannot read everything at once, so it searches and reads selectively. As a session grows long, older material can fade or be condensed, and the quality of work can drop.

A short note that saves you from repeating yourself every session.

Each new session starts without memory of earlier ones. To avoid explaining the same things again, projects commonly keep an instructions file that the tool reads automatically at the start. It is a plain document with the facts that a new colleague would need on day one.

Ways of adding to what it can do or how it behaves.

Claude Code can be customized. You do not need any of this to start, but it helps to know what exists. Names and details differ between versions, so check the documentation for the exact current options.

An agent that can run commands must be told clearly what it may do alone.

Because Claude Code can edit files and run commands on a real machine, it is built to ask before taking sensitive actions. You choose how much it may do on its own. A careful setup starts with it asking for most things and loosens only for actions you trust. Names and options differ between versions, so read the documentation, but the general levels are as follows.

The parts that work together when you give Claude Code a task.

flowchart LR
    U["You"] --> UI["Interface: terminal, editor, or app"]
    UI --> AG["Agent loop"]
    AG --> M["Claude model"]
    AG --> PM["Permission manager"]
    PM -->|"allowed or approved"| TL["Tools: read, search, edit, run, web"]
    TL --> PR["Your project and machine"]
    TL --> EX["Connected services"]
    PR --> TL
    EX --> TL
    TL --> AG
    AG --> CTX["Context: notes file, conversation, results"]
    CTX --> M
    AG --> UI
    

The Model Proposes, the Gatekeeper Decides

An important design idea: the part that suggests actions is separate from the part that permits them. If the model is confused, or tricked by misleading text, the permission layer can still stop a harmful step. This is why your settings matter and why you should read approval prompts rather than click through them.

From idea to merged change, with you in the loop.

stateDiagram-v2
    [*] --> Idea
    Idea --> Explored: ask it to read and explain
    Explored --> Planned: agree a plan
    Planned --> Changing: approve changes
    Changing --> Checking: run tests
    Checking --> Changing: failures found
    Checking --> Reviewing: tests pass
    Reviewing --> Changing: you ask for edits
    Reviewing --> Committed: you accept
    Committed --> Shared: pull request
    Shared --> Merged: reviewers approve
    Merged --> [*]
    

A tool that can act on your machine deserves careful handling.

You can see its work, and you should.

One advantage of Claude Code is that its work is visible. It shows which files it reads, which edits it proposes, and which commands it wants to run. Teams can also review the resulting changes through the usual review process. Developing a habit of looking at this trail is how you catch problems early.

The quality of the request shapes the quality of the work.

As with a human colleague, clear instructions save time. A good request has a goal, the place to work, the limits, and the way to check success. Compare the two requests below.

Reusable ways of working that give reliable results.

Tempting shortcuts that cause trouble.

A short list to keep nearby.

Speed and reach, balanced against care and cost.

Knowing the edges helps you trust it in the right places.

Five everyday situations and how the capabilities help.

One small feature, handled carefully.

A developer wants a simple “last updated” date to appear at the bottom of a product page. Here is how a careful session might go.

Copy the shape of these, and change the details.

A gentle path from curiosity to confidence.

Five common beliefs that are only partly true.

A common thread runs through these myths. Each assumes that the tool is either magic or useless. It is neither. It is a fast, tireless, imperfect colleague, and the best results come from people who give clear direction, check the work, and keep the responsibility.

Quick answers to what beginners ask most.

If you remember only a few ideas from this guide, make it these.