Stories with Tag Coding Agent

• Show HN: Plandex v2 – open source AI coding agent for large projects and tasks

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  Posted: 2025-04-16 21:26:42

  Verbose tl;dr

  Plandex v2 is an open-source AI coding agent designed for complex, large-scale projects. It leverages large language models (LLMs) to autonomously plan and execute coding tasks, breaking them down into smaller, manageable sub-tasks. Plandex uses a hierarchical planning approach, refining plans iteratively and adapting to unexpected issues or changes in requirements. The system also features error detection and debugging capabilities, automatically retrying failed tasks and adjusting its approach based on previous attempts. This allows for more robust and reliable autonomous coding, particularly for projects exceeding the typical context window limitations of LLMs. Plandex v2 aims to be a flexible tool adaptable to various programming languages and project types.

  Plandex version 2 is an open-source, AI-powered coding agent designed specifically for tackling complex, large-scale software projects and intricate coding tasks. It moves beyond the capabilities of simpler AI coding assistants by offering a structured, planned approach to code generation. Instead of just generating code snippets on demand, Plandex v2 employs a hierarchical planning system that breaks down large objectives into smaller, manageable sub-tasks. This hierarchical structure allows for more organized and maintainable code generation, as well as better control over the development process.

  The system operates by first allowing the user to define a high-level goal or objective. Plandex v2 then utilizes its AI capabilities to decompose this goal into a series of progressively finer-grained sub-tasks, creating a detailed plan of action. Each sub-task is then addressed individually, with the AI generating the necessary code for each. This step-by-step approach mimics the way human developers typically approach large projects, resulting in a more logical and comprehensible codebase.

  Furthermore, Plandex v2 integrates with large language models (LLMs), leveraging their power for code generation and refinement. This integration allows it to produce high-quality, contextually relevant code. The open-source nature of the project encourages community contribution and customization, enabling developers to adapt and extend the system to fit their specific needs and workflows. It also fosters transparency and allows for peer review of the system's functionality. Plandex v2 aims to significantly improve the efficiency and scalability of software development by providing a structured, AI-driven approach to project management and code creation. The project is available on GitHub and encourages contributions and experimentation from the wider developer community.

  • AI
  • Coding Agent
  • Open Source
  • Large Projects
  • Software Development
  • Code Generation
  • Plandex
  • Automation
  • productivity
  • GitHub
  • developer tools
  • AI Assistant

  Summary of Comments ( 51 )
  https://news.ycombinator.com/item?id=43710576

  Verbose tl;dr

  Hacker News users discussed Plandex v2's potential and limitations. Some expressed excitement about its ability to manage large projects and integrate with different tools, while others questioned its practical application and scalability. Concerns were raised about the complexity of prompts, the potential for hallucination, and the lack of clear examples demonstrating its capabilities on truly large projects. Several commenters highlighted the need for more robust evaluation metrics beyond simple code generation. The closed-source nature of the underlying model and reliance on GPT-4 also drew skepticism. Overall, the reaction was a mix of cautious optimism and pragmatic doubt, with a desire to see more concrete evidence of Plandex's effectiveness on complex, real-world projects.

  The Hacker News post for Plandex v2 has a moderate number of comments discussing various aspects of the project. Several commenters express interest and excitement about the potential of Plandex, particularly its focus on managing larger projects and more complex tasks compared to other AI coding assistants.

  One compelling line of discussion revolves around the practical applications of Plandex. Users question how it handles dependencies, integrations with existing workflows, and the level of human oversight required. Some express skepticism about the feasibility of fully automating complex software projects, emphasizing the importance of human judgment and domain expertise.

  Another key theme is the comparison of Plandex to other AI coding tools, such as GitHub Copilot and ChatGPT. Commenters debate the relative strengths and weaknesses of each, considering factors like code quality, context awareness, and the ability to handle different programming languages and paradigms. Some suggest that Plandex's project management capabilities might offer a significant advantage over existing tools focused primarily on code generation.

  There's also discussion about the open-source nature of Plandex. Several commenters praise the decision to make the project open source, emphasizing the benefits for community development, transparency, and extensibility. They anticipate contributions from other developers and the emergence of new features and integrations.

  Concerns are raised about the potential downsides of AI-driven coding, including the risk of generating buggy or insecure code, the ethical implications of automated software development, and the potential impact on the job market for software engineers.

  Finally, some commenters request more specific details about the technical implementation of Plandex, such as the underlying AI models used, the training data, and the methods for managing project complexity. They express a desire for clearer documentation and examples to better understand the capabilities and limitations of the tool.

• JetBrains IDEs Go AI: Coding Agent, Smarter Assistance, Free Tier

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  Posted: 2025-04-16 12:32:34

  Verbose tl;dr

  JetBrains is integrating AI into its IDEs with a new "AI Assistant" offering features like code generation, documentation assistance, commit message composition, and more. This assistant leverages a large language model and connects to various services including local and cloud-based ones. A new free tier provides limited usage of the AI Assistant, while paid subscriptions offer expanded access. This initial release marks the beginning of JetBrains' exploration into AI-powered development, with more features and refinements planned for the future.

  In a groundbreaking announcement on April 16, 2025, JetBrains unveiled a transformative integration of artificial intelligence into its suite of Integrated Development Environments (IDEs), promising to revolutionize the software development process. This ambitious initiative, dubbed "JetBrains AI," introduces a multifaceted approach to enhancing developer productivity and streamlining coding workflows through the power of AI. The centerpiece of this new paradigm is the "Coding Agent," an intelligent AI assistant deeply embedded within the IDE that goes far beyond simple code completion. This agent acts as a virtual pair programmer, capable of understanding the context of a project and proactively offering sophisticated suggestions, including generating entire code blocks, refactoring existing code for optimization and clarity, and even identifying and resolving potential bugs before they manifest. It promises not only to accelerate the coding process but also to elevate code quality and maintainability.

  Beyond the Coding Agent, JetBrains has infused AI into other aspects of the IDE experience, creating a more intuitive and intelligent development environment. Code completion becomes significantly more contextually aware, offering highly relevant suggestions and reducing the need for manual typing. The IDE's search functionality receives a boost in intelligence, allowing developers to locate specific files, classes, or methods with greater speed and precision, even with ambiguous queries. Furthermore, AI-powered code analysis tools provide deeper insights into code structure and potential vulnerabilities, empowering developers to proactively address potential issues and improve overall software quality.

  Perhaps equally significant is the announcement of a new free tier for JetBrains AI services. This democratizes access to these powerful AI capabilities, making them available to a wider range of developers, including students, hobbyists, and those working on open-source projects. The specifics of this free tier, such as usage limits or feature restrictions, are not explicitly detailed in the announcement but represent a commitment to making AI-assisted development more accessible.

  This comprehensive integration of AI across JetBrains IDEs represents a significant leap forward in software development tooling, promising to empower developers with unprecedented levels of productivity and efficiency. The Coding Agent, enhanced code completion and search, and deeper code analysis are all poised to reshape the way software is built, while the introduction of a free tier ensures that these advancements are accessible to a broader audience. This announcement signals a bold new era for JetBrains and the developer community as a whole, ushering in a future where AI plays an integral role in the creation of software.

  • jetbrains
  • IDE
  • AI
  • artificial intelligence
  • Coding Agent
  • Code Assistance
  • Intelligent Code Completion
  • productivity
  • Software Development
  • programming
  • Free Tier
  • developer tools
  • Code Generation

  Summary of Comments ( 33 )
  https://news.ycombinator.com/item?id=43704579

  Verbose tl;dr

  Hacker News users generally expressed skepticism and concern about JetBrains' AI features. Many questioned the value proposition of a "coding agent" compared to existing copilot-style tools, particularly given the potential performance impact on already resource-intensive IDEs. Some were wary of vendor lock-in and the potential for JetBrains to exploit user code for training their models, despite reassurances about privacy. Others saw the AI features as gimmicky and distracting, preferring improvements to core IDE functionality. A few commenters expressed cautious optimism, hoping the AI could assist with boilerplate and repetitive tasks, but the overall sentiment was one of reserved judgment.

  The Hacker News post discussing JetBrains' blog post about AI features in their IDEs generated a significant number of comments, many of which expressed skepticism and concern.

  A recurring theme was the worry about the potential for AI assistance to create a generation of developers who lack fundamental understanding of the code they produce. Commenters envisioned a scenario where developers become overly reliant on AI generated code, leading to a decline in problem-solving skills and a deeper comprehension of underlying principles. This dependence, they argued, could be detrimental in the long run, especially when faced with debugging complex issues or needing to optimize performance. One commenter likened it to using a calculator without understanding basic arithmetic.

  Several commenters also questioned the practicality and usefulness of the AI features, particularly for experienced developers. They argued that while code generation might be helpful for boilerplate or repetitive tasks, it's unlikely to be beneficial for more complex or nuanced coding scenarios. Some suggested that the AI might even hinder productivity by generating suboptimal code or requiring extensive modification. The sentiment was that experienced developers already possess efficient workflows and ingrained knowledge, making the AI assistance feel redundant or even disruptive.

  Another concern raised was the potential "hallucinations" or inaccuracies produced by AI code generation. Commenters pointed out that relying on AI-generated code without thorough verification could introduce bugs and security vulnerabilities. They emphasized the importance of careful review and testing, which could negate any time savings gained from using the AI features in the first place.

  Some commenters also expressed apprehension about the implications for the job market. While acknowledging that AI assistance could potentially increase productivity, they also worried that it could lead to a decrease in demand for developers, especially entry-level positions.

  There was a more optimistic viewpoint from some, who saw the AI features as potentially valuable tools for learning and experimentation. They suggested that the AI could help beginners grasp new concepts and explore different coding approaches more easily. However, even these more positive comments often came with caveats about the importance of understanding the underlying principles and not solely relying on the AI.

  Finally, a few commenters expressed frustration with the marketing language used by JetBrains, finding it overly hyped and vague. They desired more concrete details about the specific capabilities and limitations of the AI features, rather than broad promises of increased productivity and smarter assistance. They also questioned the long-term pricing strategy and the potential for vendor lock-in with these new AI-powered tools.