What Is Claude Code and How This AI Agent Transforms Coding

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Claude Code se ha convertido en una de las herramientas de IA para programadores más comentadas del momento, hasta el punto de que muchos ingenieros la usan a diario directamente desde la terminal o el navegador para sacar adelante trabajo real de ingeniería de software. Si has visto el nombre en redes y te preguntas qué es, cómo funciona y en qué se diferencia de otros asistentes como GitHub Copilot o los IDEs con IA, aquí vas a encontrar una explicación completa y sin rodeos.

En esencia, Claude Code es mucho más que un autocompletado inteligente: actúa como un agente de ingeniería que entiende tu repositorio, ejecuta comandos reales, modifica múltiples archivos, escribe tests, abre pull requests e incluso se coordina entre tu terminal y la web. A lo largo de este artículo verás qué es Claude Code, qué puede hacer por ti tanto en local como en la nube, cómo se integra con GitHub, qué garantías de seguridad ofrece y cuáles son sus limitaciones actuales.

What is Claude Code?

Claude Code is a command-line application created by Anthropic, the company behind the Claude AI models. Instead of living inside a browser tab or a classic GUI editor, it runs directly in your terminal (PowerShell on Windows, Terminal on macOS or any shell on Linux) as a CLI tool. You install it once, invoke it from the command line and interact with it through natural language prompts mixed with commands.

The key idea is that you can program with Claude from the terminal without constantly copy‑pasting code between a website and your editor. Rather than asking Claude for a snippet, pasting it into your IDE, running tests, going back to ask for fixes and repeating the loop endlessly, Claude Code sits inside the same environment where your code actually runs, with access to your filesystem and tooling.

From a developer’s point of view, Claude Code behaves more like an autonomous engineering agent than a simple suggestion engine. It can read your project structure, reason about architecture, run shell commands, execute tests, inspect error messages and then update your codebase accordingly. You still stay in control, but the tool can drive large chunks of the workflow on its own.

This agentic behavior goes beyond what traditional AI coding tools were doing between 2021 and 2024, when most products were essentially glorified autocomplete: they predicted the next few lines as you typed. Around early 2025, tools like Cursor and Windsurf started offering agent-based coding flows, where you describe a task in natural language and an AI agent handles multi-step work. Claude Code was designed squarely for that new era.

Anthropic’s own team uses Claude Code extensively, which is telling. According to the product lead, at some point roughly half of Anthropic’s sales team was using Claude Code weekly to handle technical workflows. Internally they built it with a long-term vision, even when early versions sometimes stumbled, made mistakes or got stuck in inefficient loops before the models improved.

How Claude Code works in the terminal

In its classic form, Claude Code runs entirely inside your local terminal. Once installed, you launch it in a project directory and start talking to it as you would in a chat, but with deeper hooks into your environment. You can describe a feature, ask for refactors, request bug fixes or ask questions about the architecture, and it will operate directly on your local files.

Claude Code has direct access to your filesystem, which allows it to perform a wide range of coding tasks. It can read, analyze and edit files, create new directories and project scaffolds, update configuration files, generate documentation and generally manipulate everything under your project folder, subject to your approval.

Because it can run real commands on your machine, Claude Code is able to execute tests, linters and build steps. When something fails, it can parse error messages from the terminal, understand stack traces or compiler output, and then iterate automatically to correct the issues. You can let it run fairly autonomously or keep a tight feedback loop, stepping in whenever you want.

This changes the traditional copy‑paste workflow with AI models quite dramatically. Instead of opening a web app, describing a function, copying generated code, pasting it into your editor, running it, getting an error and going back to the AI with screenshots or logs, you simply stay in one place—your terminal—while Claude Code edits, runs and retries in context.

The tool also integrates tightly with Git, especially GitHub. It can create semantic commits, manage branches, resolve merge conflicts and even open ready‑to‑review pull requests based on natural language instructions. That means you can go from “add a payments endpoint and tests” to “here’s a PR with all changes and passing tests” without leaving your CLI. Más aún, su integración con GitHub facilita automatizar revisiones y flujos relacionados con PRs.

What Claude Code can do for developers

Claude Code’s capabilities are best understood as a bundle of agent-driven engineering workflows rather than isolated code suggestions. The tool maps and indexes your project so it can answer questions about architecture, dependencies and how different modules interact. That global view is what lets it safely modify multiple files in a coordinated way.

One of its core strengths is reading and understanding your existing code. Claude Code crawls through your repository, loads important files into context and builds a mental model of your application: routing layers, domain models, data access code, services, tests and tooling. From there, it can respond to questions like “where is user authentication implemented?” or “how does this feature reach the database?”

It can generate new files and full feature implementations, not just tiny snippets. You might ask for a new React page wired to a backend endpoint, or a new microservice with its Dockerfile, CI configuration and documentation, and Claude Code will create the folder structure, write the code and wire up dependencies for you.

Editing existing files is another major use case. Claude Code can refactor complex modules, rename concepts across the codebase, migrate APIs to a new version, introduce new patterns or clean up technical debt. Its agentic nature means it can touch multiple files coherently without losing track of the bigger picture.

Because it can run commands and tests, Claude Code also shines at iterative debugging. It reads error logs, updates the code, re‑runs tests and keeps iterating until everything passes or until it hits a genuine blocker. For developers, that means fewer manual edit‑run‑fix loops and more time spent on higher-level design decisions.

Practically speaking, Claude Code can dramatically reduce the time required for everyday engineering chores. Creating directory trees, setting up linters and formatters, configuring databases, writing boilerplate endpoints, building interfaces or adding tests can all be offloaded to the agent. You focus on describing the application and constraints, and the tool does the heavy lifting.

You can also ask Claude Code to extend existing projects with new functionality. For example, you might say “add OAuth login to this service”, “introduce pagination to all list endpoints” or “migrate this code from Express to FastAPI”, and it will plan the change set, edit relevant files, run tests and surface a coherent diff for review.

Despite its power, Claude Code is not infallible. Like any advanced AI model, it can make mistakes, misinterpret requirements or hallucinate APIs that do not exist. The difference is that modern Claude models like Claude Opus 4.5 have noticeably improved coding performance, to the point that several senior engineering teams report better results compared to alternative agentic tools.

Claude Code vs other AI coding tools

From a positioning perspective, Claude Code is closer to an AI engineering partner than to a Copilot-style autocomplete plugin. While GitHub Copilot and similar tools are fantastic for inline suggestions, they typically operate at the level of the current file or the current cursor, not as a multi-step agent that plans and executes workflows across your whole repo.

Several early adopters have highlighted how Claude Code handles complex, multi-file agent workflows. For example, teams at companies like Vercel have reported that Claude Code performs exceptionally well at orchestrating long, structured tasks: understanding a stack, making coordinated edits, updating tests and keeping everything consistent.

Other organizations, such as Replit, have used Claude Code to build sophisticated web applications from scratch. In those scenarios the agent isn’t just filling in gaps; it is designing architecture, creating routes and components, wiring backend and frontend together and validating the result with tests.

Design-focused users like Canva have remarked on the “taste” of the code and UI that Claude generates. They’ve reported code that feels close to production-ready and default designs that look polished, which reduces the amount of tweaking needed before shipping.

In the broader market, Anthropic competes head‑to‑head with other big players and specialized startups. Cursor, for instance, announced reaching a similar scale of recurring revenue with its own coding agent tooling, and companies like OpenAI, Google and xAI are all building their own . The difference is often in how deeply each tool integrates with developer workflows and how reliable their models feel at scale.

Financially, Claude Code has become one of Anthropic’s fastest‑growing product lines. Within roughly a year of launch, it reportedly crossed one billion dollars in annualized recurring revenue, later increasing further and representing a significant share of Anthropic’s overall ARR. This momentum is one reason Anthropic sees Claude Code as a meaningful lever toward reaching positive cash flow in the next few years.

Claude Code on the web

Beyond the local CLI, Anthropic also offers Claude Code on the web, accessible directly from the Claude app. Instead of running everything on your laptop, you can kick off coding tasks in a managed cloud environment where Claude has access to a cloned copy of your GitHub repository. También existen integraciones con terceros, como la llegada del Claude Agent SDK a Xcode, que amplían escenarios de uso en IDEs y entornos macOS.

Claude Code on the web is ideal for scenarios where you want autonomous, longer-running tasks or don’t have the repo checked out locally. For instance, you can ask it to tackle well-defined bug fixes, routine maintenance tasks, backend changes or parallel work across multiple repositories while you do something else.

The web experience is also handy for asking high-level questions about a codebase. You can query how a feature is implemented, what the architecture looks like, where a particular behavior lives or how dependencies tie together, all while browsing code and diffs in the browser.

Another advantage is parallelism. Claude Code on the web can handle multiple bug fixes or feature branches at the same time, each in its own cloud session. You trigger the work, and the tasks continue running even if you close your laptop, checking back later to review the results.

Importantly, the web version is tightly integrated with GitHub. You connect your account, install the Claude GitHub app on your repositories, and Claude will clone the repo into a secure virtual machine, run its workflows and then push changes into dedicated branches ready to become pull requests.

Who can use Claude Code on the web?

Claude Code on the web is currently offered as a research preview for specific paid tiers. Access is available to Claude Pro users, Claude Max users and premium seat holders on both Team and Enterprise plans. If you are on a free plan, you will not see the full Claude Code web experience.

Within those eligible plans, access is flexible across devices. You can trigger and monitor Claude Code web tasks from the main claude.ai interface as well as from the Claude iOS app. That means you can check on long-running refactors or test suites from your phone while away from your desk.

This preview phase also lets Anthropic refine the experience based on feedback from serious engineering teams. Because these tiers are more likely to be used for real production code, Anthropic can iterate on performance, safety and usability with concrete professional workloads.

Getting started with Claude Code on the web

To start using Claude Code in the browser, you first head to the dedicated endpoint at claude.ai/code. From there, the onboarding flow guides you through the necessary integration steps so Claude can safely work with your repositories.

The first practical step is connecting your GitHub account. Once authorized, you install the Claude GitHub app on the repositories you want Claude to work with. This grants the system permission to clone, create branches and open pull requests on your behalf, all routed through secure infrastructure.

After GitHub is connected, you choose a default environment for Claude Code. That environment controls details like network access policies, preinstalled dependencies and environment variables. You can create multiple environments if you need different configurations for different repositories or security postures.

With that in place, you send your first coding task. You describe what you want Claude to do—fix a set of bugs, implement a feature, upgrade a dependency, add tests, and so on—and Claude Code will clone the repo into a managed VM, set up the environment, run the requested workflow and report back with changes.

Before anything merges, you review changes using an integrated diff view. The interface shows file-by-file modifications, lets you comment on specific lines, iterate with Claude on further fixes and, once satisfied, create a pull request straight from the web UI.

How the Claude Code web environment works

When you trigger a task in Claude Code on the web, Anthropic spins up an isolated virtual machine dedicated to that session. The system clones your GitHub repository into that VM, using secure, scoped credentials to ensure that only permitted operations are allowed.

Next, Claude prepares a secure cloud environment tailored to your code. That includes checking out the default branch (or a specific branch you mention), installing dependencies as configured, setting up necessary tooling and respecting any Claude-specific configuration files such as CLAUDE.md.

Network access is configured according to your chosen policy. By default, internet access is limited to a curated allowlist of domains, including Anthropic services, common code hosting providers, container registries, cloud platforms and package registries. You can tighten this to no network or adjust to more permissive policies where appropriate.

Once the environment is ready, Claude Code executes the requested tasks. It analyzes the code, applies changes, runs tests and validates its own work. Throughout the process, you can chat with Claude in the web interface, nudge it in a different direction or request alternative approaches.

When the work is done, Claude notifies you and pushes the changes to a branch on GitHub. From there you can open or finalize a pull request, run additional CI pipelines and follow your usual review process. The session itself can remain available for further iterations, including moving back to your terminal if you prefer to continue locally.

Reviewing code changes with the diff view

Claude Code’s diff view is designed to keep you in the loop on exactly what the agent changed. Instead of forcing you to jump straight into GitHub to inspect diffs, the Claude app shows a side panel with the list of modified files and inline changes in each one.

Each time Claude updates a file, you see simple diff statistics, such as lines added and removed (for example, “+12 -1”). Clicking on that indicator opens a detailed diff viewer, letting you skim or deeply inspect every line that was touched.

From within this diff interface you can leave comments on specific changes. If something looks off, you ask Claude to adjust it; if a refactor is only halfway there, you can ask it to complete the job or revert part of the modification. The conversation stays attached to the same session.

This loop enables several rounds of refinement before you ever create a pull request. Instead of spamming your GitHub with draft PRs or temporary branches, you iterate in the Claude UI until the change set feels solid, then ship a single, well‑formed PR for human review.

Moving tasks between web and terminal

One of Claude Code’s most powerful features is the ability to move tasks between your local terminal and the web environment. That way you can kick off heavy work in the cloud, continue iterating locally or do the reverse depending on where it makes more sense to run things.

From the terminal to the web, you can send background tasks with a simple prefix. Starting a message with the ampersand character tells Claude Code to create a new web session based on your current terminal context. The task then runs in the cloud while you keep working locally, and you can check its progress via a /tasks command or by opening it in the Claude web or iOS app.

You can also launch a fresh web session directly from the CLI. Dedicated flags let you spin up remote work on a repository without first chatting locally, which is useful if you already know the task is better handled by a cloud environment with stronger resources or different tooling.

Plan Mode is a useful pattern here. You can collaborate with Claude locally in a read‑only mode where it only inspects files and proposes a detailed plan. Once you are happy with the approach, you hand that plan off to a remote web session so the agent can execute it autonomously at scale.

Because each &-prefixed command creates its own independent web session, you can run several tasks in parallel. All of them are visible via the /tasks overview, and once any particular session finishes, you can either open a PR from the web interface or teleport the entire session back into your terminal for further local work.

Teleporting web sessions back to the CLI

Moving work from the web to your local machine is handled through a “teleport” mechanism. This lets you pull an existing Claude Code web session, with all its history and branch state, into your terminal so you can continue exactly where you left off.

Inside Claude Code, the /teleport (or /tp) command shows an interactive selector of your active web sessions. You pick the one you want, and if you have uncommitted local changes, Claude prompts you to stash them first to avoid conflicts. Once everything is clean, it syncs the relevant branch and loads the conversation.

You can also use a command-line flag for teleporting. Running claude –teleport opens a similar interactive selector, while claude –teleport <session-id> jumps straight into a specific remote session. In both cases, Claude ensures you are in the correct repository locally before pulling the remote branch.

The /tasks command doubles as a session manager. From there, you can list ongoing background tasks and press the appropriate key to teleport into a chosen one. This workflow is especially handy if you have many long-running web sessions and need to switch among them quickly.

Behind the scenes, teleport validates several requirements before attaching your terminal to a remote session. It checks that you are authenticated with the same account, that the right repo is present locally and that the branch state matches expectations. If something is off, you get a clear error or a prompt with instructions to fix the mismatch.

Sharing Claude Code sessions

Claude Code allows you to share sessions with teammates, but the options differ slightly by account type. You can toggle the visibility of each session and then send a link; recipients will see the latest state when they open it, though their view does not live‑update in real time.

On Enterprise and Teams accounts, visibility options are Private and Team. A Team-visible session can be accessed by other members of your Claude organization, and repository access is checked based on the GitHub account linked to each viewer. Your display name is visible to anyone with access, and sessions created via the Claude Slack integration are shared with Team visibility by default.

On Max and Pro accounts, the options are Private and Public. Public sessions can be viewed by any signed-in user on claude.ai, so they are useful for demos, tutorials or collaborative debugging with external partners, as long as you are careful with sensitive content.

Because sessions may contain code and credentials from private GitHub repositories, you should always review content before sharing. Repository access checks are not automatically enabled for public sharing, so it is your responsibility to ensure no sensitive secrets or proprietary information leak unintentionally.

Session-sharing behavior can be tuned from the Claude Code settings panel. You can require repository access verification for shared sessions and optionally hide your name from shared views, striking the right balance between collaboration and privacy.

Cloud environment images and tooling

The cloud side of Claude Code relies on a universal base image maintained by Anthropic. This image is preloaded with common toolchains, runtimes and developer utilities so most projects work out of the box without custom provisioning scripts.

Popular programming languages and runtimes come preinstalled. You can expect up‑to‑date versions of Python (with pip, poetry and common scientific libraries), Node.js (with npm, yarn, pnpm and bun), Ruby (with multiple 3.x versions via rbenv), PHP, Java (OpenJDK with Maven and Gradle), Go, Rust (with cargo) and C++ compilers like GCC and Clang.

Databases are also included in the universal image. At the time of writing, this includes PostgreSQL 16 and Redis 7.0, which cover a large proportion of typical application stacks used in web and backend development.

You can inspect what is installed in your environment directly from Claude Code. Asking it to run an introspection command will list available languages, versions, package managers and development tools, helping you understand which parts of your stack are ready to go and which might require additional installation steps.

On top of the global image, you can define specific environment configurations tailored to each project. These configurations control the name of the environment, network access level and any extra environment variables needed for your application, such as feature flags or non-sensitive configuration values.

Environment setup and dependency management

When a web session starts, Claude Code follows a predictable environment-setup sequence. It clones your repository, runs any configured initialization hooks and checks out the default branch unless you explicitly request another one in your prompt.

Network configuration is applied next, according to the access policy you chose. You might run with default limited access, full access for certain tasks or no network for maximized isolation. These policies determine which domains the environment can reach to download dependencies or contact external services.

Claude Code then executes the task while obeying the context defined in your CLAUDE.md file. This file can describe how your project is structured, how to run tests, which directories to ignore, how agents should behave in different situations and any special instructions relevant to your codebase.

To streamline dependency installation, you can configure SessionStart hooks. In your repository, a .claude/settings.json file can specify scripts to run when a session begins. For example, you might point to scripts/install_pkgs.sh to run the appropriate package manager commands for your stack.

Those installation scripts need to be executable and can distinguish between local and remote environments. By checking the CLAUDE_CODE_REMOTE environment variable, your hook can decide whether to install packages in the web environment, the local environment or both, depending on your workflow.

SessionStart hooks can also persist environment variables for subsequent shell commands. They do this by writing to the path defined in CLAUDE_ENV_FILE, giving you a simple way to inject dynamic variables into the session’s shell context without hard‑coding them into your repo.

Network access model and security

Security is a major design focus for Claude Code, especially for the web variant that clones and manipulates live repositories. Anthropic uses a combination of network proxies, credential isolation and sandboxing to keep your code and secrets protected.

All GitHub operations in the cloud pass through a dedicated proxy layer. Within the sandbox, the git client uses a scoped credential; the proxy then validates and translates that into your actual GitHub authentication behind the scenes. This approach keeps your real tokens out of the VM while still enabling seamless git clone, fetch, push and PR operations.

Push operations are restricted to the current working branch for safety. That prevents rogue pushes to unrelated branches or unauthorized changes to protected branches, adding an extra guardrail on top of GitHub’s own protections.

Every web session is also behind an HTTP/HTTPS network proxy. All outgoing internet traffic goes through this proxy, which enforces rate limiting, abuse prevention and content filtering. This setup reduces the risk of the environment being used to make malicious or abusive requests.

By default, network access is limited to a curated allowlist of domains. This includes Anthropic’s own services, major code-hosting platforms like GitHub, GitLab and Bitbucket, container registries such as Docker Hub and GHCR, major cloud providers, common package registries for languages like JavaScript, Python, Ruby, Rust and Go, Linux distribution servers, development tooling sites and monitoring platforms like Datadog or Sentry.

You are encouraged to follow best practices when customizing network access. That means granting only the minimum necessary privileges, auditing allowed domains on a regular basis and preferring HTTPS endpoints whenever possible to keep traffic encrypted and tamper‑resistant.

Isolation, credentials and safety guarantees

Each Claude Code web session runs inside its own isolated virtual machine. This VM is managed by Anthropic and torn down when no longer needed, keeping sessions separate from each other and limiting the blast radius of any potential issue.

Network access controls are enforced at the environment level. You can disable internet connectivity entirely for particularly sensitive projects, rely on the default limited-access mode or configure a more permissive policy when required by your stack, always understanding the trade‑offs involved.

Sensitive credentials like signing keys or direct git credentials are never placed inside the Claude sandbox. Authentication is handled by secure proxies and scoped tokens that keep your long-lived secrets out of the runtime environment, reducing the risk of exfiltration.

Code analysis and modifications happen inside these isolated VMs before any changes reach your repositories. Only after Claude has made its edits and you have the opportunity to review diffs are branches pushed back to GitHub, giving you a clear checkpoint for human oversight.

Pricing, rate limits and current limitations

Claude Code on the web shares the same rate limits as the rest of the Claude and Claude Code usage on your account. If you run many heavy tasks in parallel, you will consume your quota faster; if you schedule work more sequentially, you can stretch your limits further. Planning how many parallel web sessions to run is part of effective usage.

There are also some practical limitations to keep in mind. For instance, you can only move sessions from web to local when you are authenticated with the same account on both sides, which is important for teams who juggle multiple identities or organizations.

At the moment, Claude Code on the web only supports code hosted on GitHub. Repositories on GitLab, Bitbucket or other version-control platforms cannot yet be used with the managed cloud sessions, which may be a deciding factor for some organizations until support broadens.

Anthropic continues to evolve the product, but these constraints are worth understanding up front. They shape how you design your workflows, especially in multi-repo environments, and may influence whether you lean more on local CLI sessions or on the web experience for certain projects.

Best practices for using Claude Code effectively

To get the most out of Claude Code, it helps to invest in good project-level configuration. Setting up hooks such as SessionStart for dependency installation and environment setup ensures that every new session—local or remote—starts from a consistent, working baseline.

Documentation files like CLAUDE.md and AGENTS.md are especially valuable. In CLAUDE.md you can spell out requirements, how to run tests, where the main entry points live, which directories are off-limits and any business rules Claude should respect. If you maintain an AGENTS.md with general guidelines, you can reference it from CLAUDE.md to keep a single source of truth.

On the network and security side, applying the principle of least privilege is crucial. Only allow the domains and access levels that your code genuinely needs, and revisit those settings periodically as your infrastructure evolves or as you retire dependencies.

Finally, keep a human-in-the-loop mindset. Claude Code can handle a surprising amount of engineering work, but human review is still important: read diffs carefully, run critical tests yourself and make sure the changes align with your architectural and product goals before merging anything into main.

Seen as a whole, Claude Code is one of the most advanced AI coding agents available today, combining a powerful CLI experience with a secure, GitHub-integrated web environment that can read, write, test and ship code at scale while keeping you firmly in control of the final result.