Continue is a new tool (YC S23) that lets developers create custom AI code assistants tailored to their specific projects and workflows. These assistants can answer questions based on the project’s codebase, write different kinds of code, execute commands, and perform other automated tasks. Users define the assistant's abilities by connecting it to tools like language models (e.g., GPT-4) and APIs, configuring it with prompts and example interactions, and giving it access to relevant files. This enables developers to automate repetitive tasks, enhance code understanding, and boost overall productivity.
Continue, a startup emerging from the Y Combinator Summer 2023 cohort, has launched a platform designed to empower developers with personalized AI-powered code assistants. These assistants, customizable and tailored to individual workflows, aim to significantly enhance coding productivity and streamline development processes. The platform offers a unique approach to integrating AI into the coding experience, moving beyond simple code completion and offering more sophisticated assistance throughout the software development lifecycle.
Continue achieves this by allowing developers to create specialized AI assistants that learn from their codebases, preferred coding styles, and specific project requirements. This personalized learning process enables the assistants to provide highly relevant code suggestions, automated code generation for repetitive tasks, insightful code analysis, and proactive assistance in debugging and troubleshooting. Essentially, Continue aims to act as an intelligent coding partner, anticipating developer needs and offering proactive support tailored to the context of the project at hand.
The platform boasts a user-friendly interface that facilitates the creation and management of these custom AI assistants. Developers can easily define the scope and functionality of their assistants, specifying the types of tasks they should assist with and the level of autonomy they should have. This granular control allows developers to seamlessly integrate AI assistance into their existing workflows without disrupting their established processes.
Furthermore, Continue emphasizes the continuous learning aspect of its AI assistants. As developers interact with their assistants and provide feedback, the assistants continuously refine their understanding of the developer's preferences and project requirements, resulting in increasingly accurate and helpful assistance over time. This iterative improvement cycle ensures that the assistants remain relevant and valuable throughout the evolution of a project.
In essence, Continue offers a powerful new paradigm for AI-assisted coding, empowering developers to create bespoke AI companions that can dramatically boost productivity, reduce repetitive tasks, and enhance code quality. By focusing on personalization and continuous learning, Continue aims to transform the way developers interact with AI and elevate the overall coding experience.
Summary of Comments ( 87 )
https://news.ycombinator.com/item?id=43494427
HN commenters generally expressed excitement about Continue, particularly its potential for code generation, debugging, and integration with existing tools. Several praised the slick UI/UX and the speed of the tool. Some raised concerns about vendor lock-in and the proprietary nature of the platform, preferring open-source alternatives. There was also discussion around its capabilities compared to GitHub Copilot, with some suggesting Continue offered a more tailored and interactive experience, while others highlighted Copilot's larger training data and established ecosystem. A few commenters requested features like support for more languages and integrations with specific IDEs. Several people inquired about pricing and self-hosting options, indicating strong interest in using Continue for personal projects.
The Hacker News post for "Launch HN: Continue (YC S23) – Create custom AI code assistants" has generated a moderate number of comments, mostly focusing on comparisons with existing tools, requests for specific features, and some discussion about the underlying technology and potential use cases.
Several commenters draw parallels with existing code assistance tools. One user mentions GitHub Copilot and wonders about Continue's differentiation, asking if it's more akin to a "meta Copilot," suggesting it might be a tool for managing or customizing other AI assistants rather than a direct competitor. Another commenter points out the similarity to Cursor, another AI-powered code editor, questioning what Continue offers beyond its features. The discussion around existing tools also touches on the broader landscape of AI coding assistants, with mentions of tools like Sourcegraph Cody and Tabnine, prompting inquiries about how Continue positions itself within this crowded market.
A recurring theme in the comments is the desire for specific features or functionalities. One user expresses interest in the ability to train assistants on private codebases while ensuring data privacy, highlighting a key concern for developers working with sensitive information. Another commenter suggests integrating with popular project management tools like Jira, envisioning a workflow where the AI assistant can automatically generate or update tickets based on code changes. There's also a request for better documentation, particularly on topics like creating and managing custom assistants.
The technical aspects of Continue also spark some discussion. One commenter asks about the underlying Large Language Model (LLM) powering the assistants and expresses curiosity about how the customization process works. Another questions the choice of Python as the seemingly primary language for building the assistants, prompting speculation about whether other languages will be supported in the future.
Some comments explore the potential use cases of Continue beyond individual developers. One user envisions using it within a team or company setting to build specialized assistants for specific projects or tasks, suggesting it could be a valuable tool for improving team efficiency and code quality. Another commenter speculates about using Continue to create assistants that can generate documentation or even perform code reviews, highlighting the potential for automating various aspects of the software development lifecycle.
While there isn't a single, overwhelmingly compelling comment that dominates the discussion, the collection of comments provides valuable insights into the community's reception of Continue. The questions and feature requests reflect the needs and expectations of developers seeking more powerful and customizable AI coding assistance tools. The comparisons with existing tools reveal the competitive landscape Continue enters, and the discussions about technical details and potential use cases demonstrate the broader implications of this technology for the future of software development.