Cody is an AI code assistant that is designed to help developers write code and find answers to their coding questions. It utilizes Sourcegraph's code graph and Large Language Models (LLMs) to provide assistance. Experimental completions: Cody can provide suggestions as you code.Cody can be used in various ways, such as through the Cody app, as an editor extension for VS Code and JetBrains, or by connecting it to a Sourcegraph enterprise instance. Developers can chat with Cody in the editor or the Sourcegraph sidebar to ask questions or provide fixup instructions. Cody will provide responses based on the code files it has read, and if it gives incorrect answers, feedback can be shared to help improve its accuracy.Overall, Cody aims to reduce toil and enhance developers' productivity by providing reliable code assistance and answering coding queries based on its extensive knowledge base.

Key features

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Sourcegraph

Agentic Batch Changes: An AI agent designed for large-scale code changes, allowing users to describe changes in plain language and apply them across multiple repositories.
Deep Search: A natural language AI search tool that provides comprehensive answers and insights from complex codebases, enhancing understanding and onboarding.
Code Search: A powerful search feature that enables users to find precise matches across extensive codebases, supporting various search methods including keyword and regex.
Code Insights: A feature that transforms code into a queryable database, allowing for customizable visual dashboards to track metrics and progress in real-time.
MCP (Model Context Protocol): Provides AI agents with precise, cross-repository code intelligence, facilitating effective search, navigation, and historical context retrieval.

Useful for

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Sourcegraph

Enables large-scale code changes across multiple repositories efficiently, reducing manual effort and time.
Provides complete context for AI agents, improving accuracy and reducing errors during code modifications.
Facilitates tracking and management of changes through a structured process, ensuring consistency and oversight.
Supports various types of code migrations and modernizations, allowing teams to adapt to evolving technology stacks.
Enhances collaboration among engineering teams by providing a unified view of code changes and their impacts across the codebase.

Use cases

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Sourcegraph

Large-Scale Code Changes: Utilize the Agentic Batch Changes feature to describe and execute large-scale code modifications across multiple repositories simultaneously, such as upgrading Node.js versions or migrating TypeScript versions.
Cross-Repository Code Context: Leverage Sourcegraph MCP to provide AI agents with precise, cross-repository code intelligence, enabling them to understand and apply changes effectively.
Automated Code Migrations: Automate the migration of configurations, libraries, and dependencies across all repositories, ensuring consistency and reducing manual effort.
CI Integration and Monitoring: Integrate with Continuous Integration (CI) systems to monitor code changes, verify successful migrations, and track failures in real-time.
Comprehensive Code Insights: Use Code Insights to track code health, migrations, and security vulnerabilities, providing teams with actionable metrics and visualizations for better decision-making.

Price

PatchedFree

Sourcegraph

Enterprise Plan: Starting at $16K, includes credits for AI features and scales with team size.
Features: Search and navigation across the entire codebase, AI-powered Deep Search, Batch Changes, Insights, Monitoring, and full MCP Server access.
Deployment Options: Single-tenant cloud and self-hosted options available.
Support: 24×5 support with upgrade options and a customer success manager available optionally.
Credits: Includes credits per user with no monthly expiry and rollover on renewal.

Patched vs Sourcegraph: Which is better?

Patched vs Sourcegraph: Which is better?