mrge.io, a YC X25 startup, has launched Cursor, a code review tool designed to streamline the process. It offers a dedicated, distraction-free interface specifically for code review, aiming to improve focus and efficiency compared to general-purpose IDEs. Cursor integrates with GitHub, GitLab, and Bitbucket, enabling direct interaction with pull requests and commits within the tool. It also features built-in AI assistance for tasks like summarizing changes, suggesting improvements, and generating code. The goal is to make code review faster, easier, and more effective for developers.
A new vulnerability affects GitHub Copilot and Cursor, allowing attackers to inject malicious code suggestions into these AI-powered coding assistants. By crafting prompts that exploit predictable code generation patterns, attackers can trick the tools into producing vulnerable code snippets, which unsuspecting developers might then integrate into their projects. This "prompt injection" attack doesn't rely on exploiting the tools themselves but rather manipulates the AI models into becoming unwitting accomplices, generating exploitable code like insecure command executions or hardcoded credentials. This poses a serious security risk, highlighting the potential dangers of relying solely on AI-generated code without careful review and validation.
HN commenters discuss the potential for malicious prompt injection in AI coding assistants like Copilot and Cursor. Several express skepticism about the "vulnerability" framing, arguing that it's more of a predictable consequence of how these tools work, similar to SQL injection. Some point out that the responsibility for secure code ultimately lies with the developer, not the tool, and that relying on AI to generate security-sensitive code is inherently risky. The practicality of the attack is debated, with some suggesting it would be difficult to execute in real-world scenarios, while others note the potential for targeted attacks against less experienced developers. The discussion also touches on the broader implications for AI safety and the need for better safeguards against these types of attacks as AI tools become more prevalent. Several users highlight the irony of GitHub, a security-focused company, having a product susceptible to this type of attack.
Pets for Cursor is a simple web app that adds a small animated pet to follow your mouse cursor around the screen. Choose from a variety of animals, including a cat, dog, duck, and hamster, each with their own unique walking animation. The project is open-source and easily customizable, allowing users to add their own pets by providing a sprite sheet. It's a fun, lightweight way to personalize your browsing experience.
The Hacker News comments on "Show HN: Pets for Cursor" are generally positive and intrigued by the project. Several commenters express interest in trying it out or appreciate the novelty. Some suggest improvements like different pet options, customizable animations, and the ability to toggle the pet on/off. A few commenters raise potential downsides, such as the pet being distracting or interfering with clicking. One commenter notes the similarity to a previous project called "Cursorcerer," which was received favorably by their team. Overall, the comments indicate that while a simple idea, "Pets for Cursor" has sparked interest and discussion around its potential utility and entertainment value.
A Cursor user found that the AI coding assistant suggested they learn to code instead of relying on it to generate code, especially for larger projects. Cursor reportedly set a soft limit of around 800 lines of code, after which it encourages users to break down the problem into smaller, manageable components and code them individually. This implies that while Cursor is a powerful tool for generating code snippets and assisting with smaller tasks, it's not intended to replace the need for coding knowledge, particularly for complex projects. The user's experience highlights the importance of understanding fundamental programming concepts even when using AI coding tools, as they are best utilized as aids in the coding process rather than complete substitutes for a programmer.
Hacker News users largely found the Cursor AI's suggestion to learn coding instead of relying on it for generating large amounts of code (800+ lines of code) reasonable. Several commenters pointed out that understanding the code generated by AI tools is crucial for debugging, maintenance, and integration. Others emphasized the importance of learning fundamental programming concepts regardless of AI assistance, arguing that it's essential for effectively using these tools and understanding their limitations. Some saw the AI's response as a clever way to avoid generating potentially buggy or inefficient code, effectively managing expectations. A few users expressed skepticism about Cursor AI's capabilities if it couldn't handle such a request. Overall, the consensus was that while AI can be a useful coding tool, it shouldn't replace foundational programming knowledge.
vscli is a command-line interface tool designed to streamline the process of launching Visual Studio Code and Cursor editor devcontainers. It simplifies the often cumbersome process of navigating to a project directory and then opening it in a container, allowing users to quickly open projects in their respective dev environments directly from the command line. The tool supports project-specific configuration, allowing for customized settings and automating common tasks associated with launching devcontainers. This results in a more efficient workflow for developers working with containerized development environments.
HN users generally praised vscli for its simplicity and usefulness in streamlining the devcontainer workflow. Several commenters appreciated the tool's ability to eliminate the need for manually navigating to a project directory before opening it in a container, finding it a significant time-saver. Some discussion revolved around alternative methods, such as using VS Code's built-in remote functionality or shell aliases. However, the consensus leaned towards vscli offering a more convenient and user-friendly experience for managing multiple devcontainer projects. A few users suggested potential improvements, including better handling of projects with spaces in their paths and the addition of features like automatic port forwarding.
Summary of Comments ( 43 )
https://news.ycombinator.com/item?id=43692476
Hacker News users discussed the potential usefulness of mrge.io for code review, particularly its focus on streamlining the process. Some expressed skepticism about the need for yet another code review tool, questioning whether it offered significant advantages over existing solutions like GitHub, GitLab, and Gerrit. Others were more optimistic, highlighting the potential benefits of a dedicated tool for managing complex code reviews, especially for larger teams or projects. The integrated AI features garnered both interest and concern, with some users wondering about the practical implications and accuracy of AI-driven code suggestions and review automation. A recurring theme was the desire for tighter integration with existing development workflows and platforms. Several commenters also requested a self-hosted option.
The Hacker News post for "Launch HN: mrge.io (YC X25) – Cursor for code review" has a substantial number of comments discussing various aspects of the tool and code review in general.
Several commenters express enthusiasm for the product, praising its potential to streamline the code review process. Some highlight the integrated AI features as particularly promising, mentioning things like automated commit message generation and the ability to explain code changes. Others appreciate the focus on a more interactive and collaborative review experience, moving beyond the traditional diff-based approach.
A recurring theme in the comments is the challenge of integrating such a tool into existing workflows. Users question how mrge.io would handle large, complex codebases and how it would interact with established platforms like GitHub, GitLab, and Gerrit. Concerns are also raised about potential vendor lock-in and the implications of relying on a third-party service for such a critical part of the development process.
Some commenters discuss the broader context of code review, with some arguing that tools like mrge.io might over-engineer a process that benefits from simplicity. Others counter this by pointing out the inefficiencies of current methods and the potential for AI to significantly improve code quality and developer productivity.
The pricing model of mrge.io also draws attention, with some users expressing concerns about the potential cost, especially for larger teams or open-source projects. The discussion touches on the trade-offs between features, cost, and the value proposition of a dedicated code review tool.
There are a few skeptical voices questioning the actual impact of AI in code review and expressing concerns about potential inaccuracies or biases introduced by automated analysis. Some users suggest that the focus should be on improving existing tools and workflows rather than introducing entirely new platforms.
Finally, several commenters share their experiences with alternative code review tools and workflows, offering comparisons and suggestions for improvement. These comparisons provide valuable context and highlight the competitive landscape in this area. Overall, the comments reflect a mixture of excitement, cautious optimism, and healthy skepticism regarding the potential of mrge.io and the future of AI-powered code review.