Cody by Sourcegraph Review 2026

AI coding assistant with full codebase context that answers questions, generates code, and performs refactoring across large repositories.

Cody is an AI coding assistant built by Sourcegraph that differentiates itself through deep codebase understanding powered by Sourcegraph's code intelligence platform. While most AI coding tools only see the currently open file, Cody has context awareness across your entire codebase — it understands code structure, dependencies, and patterns across thousands of files and multiple repositories. This deep context allows Cody to provide more accurate code generation, answer complex questions about how systems work, and perform refactoring that accounts for all the places a change needs to propagate. Cody supports multiple LLM backends including Claude (Anthropic), GPT-4, and others, allowing users to choose the best model for their needs. The assistant is available as extensions for VS Code, JetBrains IDEs, and Neovim, integrating directly into developer workflows. Cody's key features include intelligent code completion, natural language code generation, codebase Q&A, and automated unit test generation. The platform's context engine uses Sourcegraph's code search and navigation to retrieve the most relevant code context for each query, going beyond simple RAG to understand code semantics, call graphs, and type hierarchies. For enterprises, Cody connects to Sourcegraph's code intelligence platform which indexes code across all repositories (GitHub, GitLab, Bitbucket, etc.), providing organization-wide code understanding. Cody supports custom commands that allow teams to create reusable AI workflows for their specific development processes. The platform includes guardrails for enterprise deployments, including attribution checking to identify if generated code matches open-source code, and admin controls for model selection and usage policies.