Table of contents
Integration with Sourcegraph
Cody AI is integrated with Sourcegraph, allowing it to leverage code intelligence features and provide enhanced code search capabilities.
Code Understanding
Cody AI has the ability to understand code in context, enabling it to offer more precise and relevant suggestions and solutions for code-related queries.
Collaboration Features
It offers collaboration tools where multiple developers can discuss and improve code together, enhancing team productivity.
Efficiency
By providing quick access to code information and suggestions, Cody AI can significantly enhance coding efficiency and productivity for developers.
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The latest comments about Cody AI on Reddit. This can help you find out how popualr the product is and what people think about it.
Sourcegraph Cody brings AI-driven code search and automation to large codebases. Cody can answer questions about your code, generate complex queries, and create PRs with ready-to-review changes. It integrates with your CI/CD pipeline and supports self-hosted setups for maximum security. With Cody, developer teams can onboard faster, enforce code standards, and reduce time spent digging through repositories, making... - Source: dev.to / 4 months ago
Cody by Sourcegraph for explaining large codebases. - Source: dev.to / 5 months ago
Cody: Sourcegraph’s AI coder that doesn’t get lost in monorepos. - Source: dev.to / 5 months ago
Cody is an enterprise-focused AI assistant that integrates with your IDE to provide intelligent code suggestions, architectural insights, and project-specific assistance. It connects with tools like Jira and Notion for enhanced workflow alignment. - Source: dev.to / 6 months ago
MCP hosts MCP hosts handle communication between the servers and client, for example, in the form of a chat application or IDE. Popular hosts include Claude Desktop, Zed, and Sourcegraph Cody. See MCP: Example clients for the complete list of supported hosts/clients. - Source: dev.to / 6 months ago
AI coding assistant Cody can be paired with PostgreSQL to simplify tasks like optimising queries and managing complex database operations such as table creation and data retrieval. - Source: dev.to / 6 months ago
AI is now changing how you can approach building UI elements. Instead of spending hours on repetitive tasks, you can use AI tools to develop and refine your UI components quickly. Introducing Cody, an AI tool that helps you create complex UI fast. - Source: dev.to / 7 months ago
This is particularly interesting, as Steve Yegge works on (and I think leads) Sourcegraph Cody[0], which is a competitor to Claude Code. Cody does use Claude Sonnet, so they do have some aligned interests, but it's still surprising to see Yegge speak so glowingly about another product that does what his product is supposed to do. [0] https://sourcegraph.com/cody. - Source: Hacker News / 7 months ago
Clear and comprehensive documentation is essential for every developer despite its tedious nature. It ensures code clarity, facilitates collaboration, and minimizes errors in software development. With Cody, an AI-powered coding assistant leveraging advanced large language AI models, developers can automate documentation tasks efficiently. - Source: dev.to / 7 months ago
Today, developers can access an impressive range of tools built on top of large language models (LLMs) that go beyond basic code autocompletion and provide powerful AI-assisted coding experience. Even though OpenAI’s GPT-4o is leading most of the benchmarks for coding, Anthropic Claude and Google’s Gemini are not far behind. In this article, we’ll go through the best LLMs available for software development and use... - Source: dev.to / 7 months ago
To start, create an account and install the Cody VSCode extension. For other IDEs, refer to the integration guides in the documentation. - Source: dev.to / 8 months ago
That is where Sourcegraph‘s Cody comes in. Cody is an AI assistant designed to streamline development tasks by helping you generate efficient queries, simplify aggregation creation, and manage key operations like indexing and replication. - Source: dev.to / 9 months ago
For those looking for a free coding assistant they can also use at work / in the enterprise, Cody has had a free tier for awhile: https://sourcegraph.com/cody - Works with local models - Context-aware chat with very nice ergonomics (we see consistently more chats per day than other coding assistants) - Used by both indie devs and devs at very large enterprises like Palo Alto Networks - Hooks nicely into code... - Source: Hacker News / 10 months ago
In this guide, you’ll learn how to build and customize UI elements, create style guides, and develop more complex UIs using AI. By the end, you'll see how tools like Cody reduce the time and effort involved in your UI development. - Source: dev.to / 10 months ago
I have explored both GitHub Copilot and Sourcegraph Cody and have seen that each tool has its strengths. After diving into both, I found Cody’s deeper context understanding, access to different LLMs, and a strong focus on security to be game-changers for projects of any size. If you’re curious, I’d recommend signing up for Cody and seeing how it fits into your workflow. However, if Copilot aligns better with your... - Source: dev.to / 10 months ago
This tutorial demonstrated how Cody can build a PoC app quickly and efficiently, from planning to execution, allowing you to focus on creating solutions that resonate with your target audience. To experience how Cody can enhance your development workflow, sign up for free today and take your projects to the next level. Additionally, don’t miss the chance to connect with experienced developers, collaborate on... - Source: dev.to / 10 months ago
+1 looking for an answer here as well. My guess is that the context limit for all the source code for some large projects will almost always exceed the LLM allowed token limits, so the AI editors generally need to implement some RAG like solution for these. Sourcegraph's cody[0] claims to be able to answer questions across your entire codebase. I haven't tested it extensively but I'm guessing it's competitive with... - Source: Hacker News / 11 months ago
Ya the one between your ears. Kidding! Maybe Sourcegraph Cody https://sourcegraph.com/cody, or possibly Github copilot. I think Cody might handle the multiple files better, and allows you to pick from multiple models. - Source: Hacker News / about 1 year ago
There is Cody (https://sourcegraph.com/cody). But their "applying code" feature is worse than Cursor. They put import lines on the bottom of the file, for example. Cursor's "applying code" is superb. Too bad it cannot be used with another IDE. - Source: Hacker News / about 1 year ago
Cody, developed by Sourcegraph, is an AI coding assistant that's designed to work with your entire project source code, not just the file you're currently editing. - Source: dev.to / about 1 year ago
I recently learned that Sourcegraph's AI coding assistant Cody can be used offline by connecting it to a local running Ollama server. - Source: dev.to / over 1 year ago
Cody, an AI-powered coding assistant developed by Sourcegraph, has garnered a mix of praise and constructive feedback from the developer community across several platforms. It is primarily positioned as a robust alternative to GitHub Copilot, emphasizing its unique capabilities aimed at enhancing coding efficiency and developer productivity.
One of Cody's most highlighted features is its ability to boost development productivity by providing intelligent, real-time code suggestions. Cody stands out as a significant tool for developers dealing with extensive codebases, as its powerful search functionalities allow users to quickly find functions, definitions, and references, effectively streamlining the process of understanding and navigating large projects. Cody leverages two sophisticated large language models (LLMs), OpenAI's GPT and Anthropic’s Claude, to provide deeper context understanding and insight within codebases.
Cody is particularly lauded for its integration capabilities with various development environments and tools such as IDEs, Jira, and Notion, which strengthen its utility in providing architectural insights and project-specific assistance. This adaptability is crucial for developer teams managing complex architectures, whether monolithic or microservices-based, and ensures seamless workflow integration.
Security is another key advantage of Cody, especially emphasized in enterprise environments where data privacy and secure handling of code are paramount. The availability of a self-hosted configuration aligns with the needs of enterprises seeking maximum control over their coding environment.
While Cody’s comprehensive capabilities receive broad recognition, some users have pointed out areas where it might fall short. For instance, its “applying code” feature has received critique, notably for its handling of import lines, which places them at the bottom of files—an arrangement some developers find counterintuitive. Comparisons with other AI tools like Cursor have highlighted Cody’s relative limitations in specific code manipulation scenarios.
Moreover, the context limits associated with large-scale codebases remain a critical challenge, as is the case with many AI-powered code assistants. Cody reportedly tackles this through refined algorithms to handle large datasets effectively, but this remains an area where continuous improvement is needed.
Cody’s open-source core and the availability of a free tier make it an accessible option for individuals and businesses alike. This accessibility extends to indie developers and large enterprises, evidenced by usage statistics from significant organizations like Palo Alto Networks. The community-driven approach provides opportunities for developers to contribute and collaborate, fostering a community of innovation around Cody.
In summary, Sourcegraph Cody commands a respected position in the realm of AI coding assistants. It is praised for its strong code search capabilities, integration versatility, and focus on enterprise security. While there are areas for enhancement, particularly in code application features, Cody’s offerings continue to appeal to a wide range of developers seeking effective tools for code navigation, insights, and productivity enhancements.
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