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Sourcegraph Cody
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Sourcegraph Cody

Cody is an AI-powered code assistant by Sourcegraph that understands your entire codebase to deliver intelligent code generation, contextual answers, and real-time development support.

Last Update: 2026-02-25

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Tool Information

Cody is an advanced AI coding assistant built on Sourcegraph’s code graph technology and large language models to provide deep, context-aware programming support. Unlike generic AI chatbots, Cody analyzes your entire codebase—including repositories, dependencies, and external knowledge sources—to generate highly relevant code suggestions and accurate technical answers. This contextual awareness enables developers to receive responses aligned with their project’s architecture, coding standards, and existing patterns.

One of Cody’s core capabilities is its interactive chatbot interface that allows developers to ask questions directly about their code. It can explain complex logic, identify dependencies, and suggest improvements based on full-project visibility. The “Fixup” feature enables rapid refactoring and code modifications using natural language instructions, while “Recipes” allow automatic generation of unit tests, documentation, and other supporting code assets. Experimental autocomplete functionality further enhances real-time productivity by offering intelligent code completions as developers type.

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Cody integrates seamlessly into development workflows through VS Code, JetBrains IDEs, the standalone Cody app, or enterprise Sourcegraph deployments. Developers can chat with Cody inside their editor or via the Sourcegraph sidebar, making it a flexible AI programming companion for individual developers and engineering teams. By reducing repetitive tasks, accelerating debugging, and delivering context-aware insights, Cody improves software development efficiency and helps teams ship higher-quality code faster.

F.A.Q (20)

Sourcegraph Cody, referred to as Cody, is an AI code assistant designed to assist developers in their coding processes. It provides support in writing codes and answering coding queries by perusing the developers' code base and additional coding graph resources.

Cody utilizes Sourcegraph's code graph and Large Language Models (LLMs) to enhance its tasks of providing assistance for coding queries and suggesting modifications. The code graph informs it about the coding structure and interconnections, and the LLMs equip it with extensive linguistic understanding to analyze, understand, and communicate around coding contexts and terminologies.

Cody differs from other AI chatbots as it has the capability to understand the codebase of your project. It understands and follows coding standards and architecture which sets it apart from other chatbots. Rather than operating based on generic programming principles, it takes a more personalized approach for each project.

Cody interacts with the code by understanding natural language instructions provided by the developer. It will then perform the required edits in response to the instructions. Examples of fixup responses include factoring out common helper functions, using imported CSS module's class names or extracting a list item to a separate React component.

Yes, Cody can generate unit tests and documentation. This is done with full awareness of the entire codebase which enables contextually relevant and comprehensive outputs. Developers can select a particular code and ask Cody to generate unit tests or documentation based on the selected code.

Experimental completions in Cody refers to the feature where Cody provides suggestions while the developer is still coding. This is possible due to Cody's ability to understand and interpret the code that is being written.

Cody is highly versatile and can be used in several ways. It can be used via the Cody app, as an editor extension within VS Code and JetBrains, or by connecting it to a Sourcegraph enterprise instance. Developers can communicate with Cody directly within the editor or through the Sourcegraph sidebar.

Cody can be integrated with various platforms including VS Code, JetBrains, and Sourcegraph.com. Developers can use the Cody app or connect it with an existing Sourcegraph enterprise instance.

When Cody provides incorrect answers, developers have the option of providing feedback, helping to improve the system's accuracy. All feedback helps Cody to improve its understanding and be more precise for future queries and fixes.

Cody enhances developer productivity by reducing toil and engaging in tedious tasks. By providing insightful coding assistance and answering coding queries based on its extensive knowledge base, developers save precious time that can be invested in more meaningful and complex tasks.

Cody reads through the entire codebase of the project, external resources like open-source code, StackOverflow questions and other related information to offer suggestions and answers. This leads to more informed assistance based on prior knowledge.

Cody understands and follows the coding standards and architecture specific to your project. How this works is it reads through your entire code base and therefore knows your project-specific conventions, codes and architecture.

Yes, Cody can generate code. When asked a certain question or provided natural language instructions, Cody can write the appropriate code in response. The AI relies on the understanding of your project’s specifics, language models and code graph data to generate the code.

Developers can provide fixup instructions to Cody via natural language commands. Once the applicable code is selected, developers can use the command 'Cody: Fixup' and provide their specific instructions. For example, 'Factor out any common helper functions' or 'Use the imported CSS module's class names', and Cody will make the needed corrections.

Yes, Cody can be used in JetBrains. Cody is available as an editor extension and can be connected to a Sourcegraph enterprise instance, the Cody app, or Sourcegraph.com.

A Sourcegraph enterprise instance is essential for running Cody. Developers can connect Cody to a Sourcegraph enterprise instance to enable Cody's capabilities within their coding environment, making it seamless and efficient to interact with. Moreover, doing so expands Cody’s comprehension by adding in the instance’s specific code graph data.

Cody aids with coding queries by analyzing the codebase and related resources, detecting possible issues or queries developers might have. It then suggests solutions based on its extensive knowledge base and its understanding of the code graph. Moreover, when developers ask specific questions or provide instructions, Cody provides appropriate code or implimentations.

Yes, Cody works in real-time. As you code, Cody is constantly analysing and interpreting your actions. This capacity allows Cody to provide suggestions and fixes while you are still coding.

Cody accepts feedback in terms of correctness of its responses. If Cody provides an incorrect answer or solution, developers have the option to share feedback and highlight the discrepancies, thereby improving Cody's learning and precision for future references.

Sourcegraph's code graph is an extensive record of the code's structure and relation. It provides a graphical representation of how different aspects of the codebase interact and communicate with each other. Cody uses this code graph to understand the codebase and provide better and more contextual support to developers.

Pros and Cons

Pros

  • Chatbot knows your code
  • Interactive code writing and refactoring
  • Generates unit tests and documentation
  • Assistive code suggestions
  • App for code local on device
  • VS Code and JetBrains extensions
  • Integrated with Sourcegraph enterprise instance
  • Chat interface in editor or sidebar
  • Feedback for response improvement
  • Generates code answering queries
  • Follows your coding standards
  • Uses your project's architecture
  • Considers codebase context
  • Translates natural-language instructions
  • Improves variable names
  • Translates code to different languages
  • Summarizes recent code changes
  • Detects code smells
  • Generates release notes
  • Enterprise and open source enabling
  • Troubleshooting guide available
  • Configurable code graph context

Cons

  • Requires feedback for accuracy
  • Limited editor extensions
  • JetBrains extension is experimental
  • Limited to Sourcegraph enterprise
  • Requires full codebase access
  • Dependency on open-source data
  • Limited to pre-defined recipes
  • Depends on existing coding conventions
  • Context dependent fixup instructions
  • Relies on Sourcegraph's code graph

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Applicable Tasks

AI code assistant context-aware coding tool codebase analysis AI intelligent code completion automated unit test generator code refactoring assistant developer productivity platform VS Code AI extension JetBrains AI plugin Sourcegraph integration tool

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