Continue.dev
Open-source AI coding assistant for your IDE
The verdict
Continue.dev distinguishes itself as an open-source AI coding assistant that integrates directly into existing IDEs like VS Code and JetBrains, rather than being a standalone editor. Its core strength lies in its configurability, allowing users to connect to a wide array of local and cloud-based LLMs, including OpenAI, Anthropic, and self-hosted models, which offers significant flexibility and cost control. The tool supports multi-file edits and provides intelligent code generation, refactoring, and debugging assistance through a chat interface, but its agentic capabilities are more user-driven and less autonomous than some dedicated AI IDEs. While the integration into familiar environments is a major plus for workflow, the overall polish and seamlessness of its predictions can sometimes lag behind proprietary, tightly integrated solutions, requiring more explicit user interaction to guide the AI. Its commitment to an open-source model, however, ensures broad accessibility and community-driven development, making it a powerful option for developers prioritizing customization and privacy.
What works
- ✓Continue.dev integrates directly into popular IDEs such as VS Code and JetBrains, allowing developers to use AI assistance without leaving their familiar development environment.
- ✓It offers extensive flexibility by supporting integration with a wide range of local and cloud-based LLMs, including custom models, providing users with choice and control over their AI backend.
- ✓The open-source nature of Continue.dev significantly reduces cost barriers and allows for community contributions and transparency in its development.
- ✓Its multi-file editing capabilities and context-aware suggestions extend beyond single-file modifications, enabling more complex project-wide refactoring and code generation tasks.
What doesn't
- ✕The polish and seamlessness of AI predictions and suggestions can sometimes feel less integrated compared to fully proprietary AI-first IDEs, occasionally requiring more explicit prompting.
- ✕While it offers agentic workflows, these are often more user-initiated and guided rather than fully autonomous, which may require more manual intervention than some competitors.
- ✕Setting up and configuring certain local or custom LLMs can involve a steeper learning curve, potentially posing a barrier for less technical users.
If Continue.dev isn't it
Alternatives worth a look
GitHub Copilot
The default AI pair programmer
Copilot is the safe choice, and that is not an insult. It lives inside the editor you already use, the enterprise controls are the most mature in the category, and the free tier covers light use. Agent mode has closed much of the gap to Cursor, though it still feels a step behind on complex multi-file work. If your company already lives on GitHub, the integration story is unbeatable; if you want the bleeding edge, look elsewhere.
Cursor
The AI-first code editor
Cursor remains the editor to beat. Its agent mode plans and executes multi-file changes with a reliability competitors still chase, and tab completion predicts intent so well it changes how you type. The fork-of-VS-Code foundation means zero relearning. At $20 a month the value question is real for hobbyists, but for anyone coding daily it pays for itself within a week. The polish is what separates it: features ship fast and rarely break.
Aider
AI pair programming in your terminal
Aider stands out as an AI code editor that prioritizes a terminal-native, multi-file editing experience, making it particularly appealing for developers who prefer command-line workflows. Unlike many GUI-centric tools, Aider integrates directly into your shell, allowing for natural language interactions to modify existing code, add new features, or refactor. Its strength lies in its ability to manage multiple files within a project context, enabling more complex, agentic changes than single-file completions. While it offers excellent prediction quality for focused tasks, the lack of a visual interface can be a barrier for some users, and its effectiveness is heavily dependent on the clarity and specificity of user prompts. It's a powerful tool for those comfortable with the terminal, offering a solid AI-driven workflow that extends beyond simple auto-completion.