How to Use Agentic Coding with Claude in CodeGPT + VS Code

TL;DR

• Anthropic's Claude Sonnet and Opus models are the current industry leaders for agentic coding, moving beyond simple assistants to function as true virtual collaborators.

• CodeGPT is a powerful VS Code extension
  that lets you integrate these premium models using your own API key, providing a cost-effective path to unlimited, high-level interactions.

• By leveraging CodeGPT's tools like Codebase Indexing and the Deep Graph MCP, you can give Sonnet 4 a complete understanding of your project, enabling it to autonomously plan and execute complex, multi-file tasks.

• This combination transforms the developer workflow from manual coding to high-level project management, with the AI handling everything from bug fixes to test generation.

• We'll walk through a practical setup guide and discuss the tradeoffs, costs, and legal considerations to help you confidently adopt this new era of AI-powered development.

Elevating Your Workflow

Welcome to the new era of software development. If you've been in the industry for more than a year, you've likely seen the rapid evolution of AI coding assistants. We've gone from simple autocomplete to tools that can generate entire functions. But what if you could have a partner, a true AI Agent for Coding, that doesn't just respond to a single prompt but can autonomously understand your entire project, fix bugs across multiple files, and even write its own tests?  

For developers, this isn't a distant fantasy—it's a reality, and it's being powered by Anthropic's most advanced large language models (LLMs): the Claude 4 Opus series. However, to get the most out of these sophisticated models, you need the right tool. In our experience, there is no better environment than the CodeGPT VsCode extension. This article will serve as your comprehensive, first-person guide to integrating Sonnet and Opus 4 models with CodeGPT to create an agentic coding workflow that feels like a cheat code for productivity.

This post is for the professional developer, the engineering manager, or the startup founder who has a technical understanding of the craft but wants to leverage the cutting-edge of AI to move faster. We will avoid marketing fluff and get straight to the practical, tactical steps needed to make this a reality for you and your team.

Step 1: Setting the Foundation — The BYOK Approach

Before we can unleash a powerful AI Coding assistant, we need to set up the environment. The beauty of CodeGPT is its "Bring Your Own Key" (BYOK) model, which gives you full control and ownership of your interactions. This approach is superior to many bundled services for three key reasons:

1. Unlimited Interactions: With your own API key, you bypass rate limits and can have unlimited conversations with the model.

2. Cost Control: You pay for what you use on Anthropic's platform, giving you transparency and control over your budget.

3. Model Choice: CodeGPT allows you to hot-swap between models from different providers (like Anthropic, OpenAI, and Gemini), but we’ll focus on Anthropic's flagship Sonnet 4 model because of its superior performance in agentic tasks. 

To get started, we'll need to do the following

1. Create an Anthropic Account: If you don't already have one, create a developer account on Anthropic’s platform. You'll need to add a minimum of $5 in credits to your account to use the API.

2. Get Your Claude API Key: From your Anthropic dashboard, generate a new API key.

3. Install CodeGPT in VS Code: Open Visual Studio Code, navigate to the Extensions marketplace, and search for "CodeGPT." Install the extension.

4. Connect Your Key: The CodeGPT extension, upon first use, will prompt you to connect to a provider. Select Anthropic and paste your API key when prompted. The CodeGPT extension will now be able to authenticate with Anthropic and access the full power of its models.

Step 2: The Agentic Leap — From Prompting to Planning

A common mistake is treating an advanced model like Claude 4 like a glorified autocomplete. The real power of the Claude and Opus 4 (or 4.1) series lies in its agentic behavior—its ability to understand context, make a plan, and execute a series of steps autonomously. The CodeGPT extension is built to facilitate this workflow.  

Here’s how we turn a simple request into an agentic task:

1. Initial Research & Idea Validation: This is the most crucial step. Before you ask the model to write a single line of code, you need to give it the necessary context. CodeGPT has a feature called "Codebase Indexing" which is designed for this.  

To set this up, you can:

• Use the Codebase Indexing feature directly within the CodeGPT extension.  

   

• For a more advanced workflow, you can install the "Deep Graph MCP" (Multi-Context Provider). This tool, which connects to CodeGPT Studio to manage your codebase graph, gives the agent an even deeper understanding of your project.

  Once your codebase is indexed, you can ask sophisticated questions like:

• "Show me the authentication logic."

• "What would be affected if I modify the UserService?"

• "Show all API endpoints in this project."

This initial step transforms the model from a stateless chatbot to an informed collaborator. It’s the difference between asking a junior developer a question and asking a senior developer who has already read the entire codebase.

2. Triggering Extended Thinking: Once the agent has the context, you can give it a high-level task. For example, "Fix the bug in the user login flow." To ensure Claude 4 doesn't jump to a simple, incorrect solution, you can use specific prompting techniques. Anthropic's best practices suggest using words like think or think harder to trigger an extended thinking mode, which allocates additional computational time for the model to thoroughly evaluate alternatives. We’ve found this to be a game-changer.  

3. Implementing the Solution: After the agent has a solid plan, you can instruct it to implement the solution. This is where the model's parallel tool use and ability to manage multiple files comes into play. It will execute its plan, write the necessary code, and even suggest commits and pull requests. This moves the developer’s role from writing the code to approving the plan and reviewing the final output.  

A First-Person Vignette: The Opus 4.1 Cheat Code

When our team was working on a tricky legacy codebase in early 2025, we were staring down a backlog of UI bugs. The codebase, a labyrinth of interconnected React components and a bespoke CSS-in-JS solution, was a nightmare to debug. We had already tried a few other AI coding assistants, but they would frequently hallucinate APIs or suggest fixes that didn't account for the cross-file dependencies. It was a chore.

Using Claude 4.1 Opus and, following the methodology above, we paired it with CodeGPT and the Deep Graph MCP. The process felt different immediately. We fed it a bug report that included a screenshot of a broken UI component and an instruction to “think hard” about a fix. The model took a moment, then came back with a detailed, multi-step plan.  

What happened next was remarkable. It didn't just suggest a code block; it autonomously started inspecting files using read-only commands, identifying the root cause of the bug in a third-party library, and proposing a multi-file patch. We were able to approve its tool calls and, within minutes, it had pushed a working fix. For a bug that would have taken a seasoned engineer an hour of manual tracing and debugging, the AI Agent For Coding had taken less than five minutes. It truly felt like a "cheat code" for our productivity. This experience validated the model's claim of a 72.5% score on SWE-Bench Verified , a benchmark for real-world bug-fixing tasks.

How much does using Claude 4 Opus with CodeGPT cost?

This is a key question for any developer or team. Since you use CodeGPT's BYOK model, the cost is tied directly to Anthropic's API pricing, not a separate subscription for the model itself. The Opus models are premium offerings, with the current pricing for Claude 4 Opus at approximately $15 per million input tokens and $75 per million output tokens. While this is a higher rate than the faster Haiku or Sonnet models, the cost is justified for high-stakes, complex tasks where its superior performance and reliability are required. For example, an advanced debugging task might cost a few dollars in API calls, but it could save you an hour of a highly-paid engineer's time.

The free tier of CodeGPT allows for up to 30 interactions per month. However, by using your own Anthropic API key, you get to have "unlimited interactions" with the model.

What about legal implications and intellectual property?

The legal landscape for AI-generated code is still evolving, but a few key principles are emerging. The U.S. Copyright Office has stated that copyright protection only applies to works with a human author, meaning code generated entirely by AI may not be eligible for copyright protection. However, if a human has "creative control over the work's expression," such as by providing specific prompts or editing the output, the human's contributions may be copyrightable. The risk of hallucinations is also a factor, as a model could generate code that infringes on a third party's intellectual property.  

For developers, this means a few things:

• You should always review and edit the code generated by the AI.

• You must be candid about the AI's contributions if you ever need to register a copyright.

Be mindful of what you're inputting into the model. Using your own API key with a reputable provider like Anthropic, which does not use your data for training by default, helps protect your company's intellectual property and client information.

How do I use an AI agent to build a minimum viable product (MVP)?

Using AI For coding to build an MVP is a fantastic use case, but it requires a structured approach. A good MVP development firm will tell you that the process should always start with a well-defined problem and a testable hypothesis.

Define Your Hypothesis: Don’t start with "I want to build an AI app." Start with a hypothesis like, "If we use an AI model to scan resumes, recruiters will shortlist candidates 30% faster".

• Identify Minimum Functionality: Focus on one key AI-driven feature that proves your hypothesis. You can use rule-based or semi-automated systems to mimic the AI for an early prototype.

• Choose the Right Model: With CodeGPT's BYOK approach, you have the flexibility to use a range of models. Start with a more cost-effective model like Sonnet for initial testing and prototyping, then upgrade to Claude Opus 4 or 4.1 when you need to handle more complex, multi-step tasks.

• Rapid Prototyping: Leverage the agentic capabilities of Sonnet to generate full applications in a single interaction. Our team has seen it generate 500-1,000 lines of an interactive website in under a minute, which can dramatically accelerate the initial development stages and get you to a user-testable MVP faster.

Conclusion

The combination of Anthropic's Claude Sonnet 4 and Opus and the CodeGPT VS Code extension is a paradigm shift for professional developers. By moving from simple prompts to a sophisticated, agentic workflow, you can transform your productivity and free yourself from the tedious aspects of software engineering. Claude's models are not just a tool; it's a collaborator that can plan, execute, and validate, allowing you to focus on the higher-level strategic and architectural challenges of your projects. If you are serious about leveraging the full power of AI for coding, this is the stack you need to be using today.

Start building your next project with Claude Sonnet and the complex task with Opus 4 and CodeGPT and experience the future of software development for yourself.