Cody by Sourcegraph

Cody pairs Sourcegraph’s code intelligence with AI to search, explain, and generate code across entire repositories. It helps with refactors, tests, and doc generation while grounding answers in your code.

Pricing: Free and paid plans API: Yes Rating: 4.40 Updated: 2 days ago

Ideal for Creative directors, brand designers, growth marketers

Strength Rapid visual brainstorming with consistent styling.

Watch for Context, repositories, and requests vary by tier

Where Cody by Sourcegraph shines

Cody is built for teams working in big, messy codebases. It answers “where is this used?”, writes tests, explains legacy code, and proposes changes — all grounded by precise code search.

Repo-aware

Understands your codebase via semantic and structural search.

Productivity

Generates tests, docs, and refactor suggestions.

Integrations

Works in editors and with CI/CD workflows.

Repository-aware AI coding assistant

Cody, developed by Sourcegraph, differentiates itself by grounding outputs in actual codebases. It can answer questions about repositories, suggest changes across multiple files, and provide explanations tied to project context. Unlike generic assistants, Cody understands the developer’s real code, enabling large-scale refactoring and consistent documentation generation. This repository-first approach makes it a practical assistant for enterprise engineering teams.

Who benefits most

Engineering organizations managing large monorepos benefit from Cody’s repository awareness. Developers can query legacy code, understand architecture decisions, and generate migration plans with AI assistance. For teams with complex or older codebases, Cody saves hours of manual exploration and speeds onboarding of new engineers.

Critical review

Cody requires proper integration with Sourcegraph, which may not be feasible for smaller projects. It also demands trust, since repository access is sensitive. However, its grounding in actual code reduces hallucinations and improves reliability, making it a strong alternative to general-purpose coding assistants for serious engineering teams.