Kilo Code for JetBrains

Product Introduction

1. Definition: Kilo Code for JetBrains is a fully native, open-source AI coding agent plugin designed specifically for the JetBrains IDE ecosystem (IntelliJ IDEA, PyCharm, WebStorm, etc.). It operates as a model-agnostic platform that integrates directly into the IDE's interface and workflow.
2. Core Value Proposition: It exists to provide developers with a high-performance, vendor-agnostic AI coding assistant that leverages the full power of JetBrains' native tooling and split-mode architecture. Its primary value is enabling sophisticated agentic workflows—like autonomous code generation, debugging, and planning—across 500+ AI models without locking users into a single provider's ecosystem or interface.

Main Features

1. Native JetBrains Plugin Architecture: Unlike agents that use the generic Agent Communication Protocol (ACP), Kilo Code is built from the ground up as a native JetBrains plugin. This provides deeper IDE integration, a custom UI tailored to Kilo's features, and superior responsiveness. It works seamlessly across both Community and Ultimate editions of JetBrains IDEs, installed directly from the official Plugin Marketplace.
2. Split-Mode & Remote Development Optimization: The plugin is architected explicitly for JetBrains' split-mode, allowing the IDE backend (compiler, project files, terminal) to run on a remote machine or server while the UI (including Kilo's interface) remains local. This enables developers to leverage powerful remote compute for coding tasks while maintaining a low-latency local interface, a critical feature for cloud development, secure environments, or resource-intensive projects.
3. Multi-Agent Workflow Engine: Kilo Code moves beyond simple chat by providing distinct, purpose-built agents for different stages of development. It features specialized agents for "Ask" (code understanding), "Plan" (implementation strategy), "Code" (multi-file execution), and "Debug" (systematic fault diagnosis). This structured approach allows for more complex, context-aware task execution compared to single-prompt interfaces.
4. Model-Agnostic Platform with 500+ Models: The core of Kilo is its gateway that supports over 500 hosted large language models (LLMs). Users can route requests across leading model families (like OpenAI GPT, Anthropic Claude, Meta Llama), bring their own API keys (BYOK) for direct provider access, or connect to local models via endpoints like Ollama and LM Studio, all within the same JetBrains workflow.
5. Enterprise-Grade Governance & Team Controls: For organizations, Kilo provides centralized management through the Kilo platform. This includes unified billing, detailed usage analytics, role-based access control (RBAC), SSO/SCIM integration, model policy controls (restricting which models teams can use), and comprehensive audit logs, enabling safe and scalable adoption across engineering teams.

Problems Solved

1. Pain Point: Vendor lock-in and limited model choice within integrated development environments. Many AI coding tools are tied to a single provider's models (e.g., GitHub Copilot, JetBrains AI Assistant), restricting developers from using specialized or cost-effective alternatives.
2. Target Audience: Professional software developers and engineering teams who use JetBrains IDEs for local or remote development, particularly those in polyglot environments (Java, Python, JavaScript, Go, C#, etc.). It appeals to developers who require advanced, agentic AI assistance beyond autocomplete, and to platform/engineering leaders who need centralized governance over AI tool usage.
3. Use Cases:
   • Remote & Secure Development: A developer working on a proprietary codebase in a secure, remote environment can use split-mode to keep the code on a secure server while using Kilo's AI agent locally for feature implementation and debugging.
   • Complex Refactoring: A senior engineer can use the "Plan" agent to analyze the impact of a major architectural change across a monolithic codebase before executing the changes with the "Code" agent.
   • Cross-Platform Team Standardization: An engineering organization can standardize on Kilo to provide consistent AI assistant capabilities, model policies, and cost controls for teams using a mix of JetBrains IDEs, VS Code, and CLI-based development.

Unique Advantages

1. Differentiation: Unlike JetBrains AI Assistant (focused on chat/completions) or Junie (first-party autonomous tasks), Kilo Code is an open-source, third-party platform that prioritizes model freedom and customizable agent workflows. Unlike GitHub Copilot, it is not limited to GitHub-managed models and offers more advanced, multi-step agentic capabilities. Its avoidance of ACP allows for a richer, product-specific user interface.
2. Key Innovation: Its architecture designed for JetBrains split-mode from inception is a significant technical differentiator. While other plugins may support remote development, Kilo's foundational design for this paradigm ensures optimal performance and integration. Secondly, its orchestration of specialized, sequential agents (Ask, Plan, Code, Debug) represents an innovative approach to structuring AI-powered development tasks, moving beyond a monolithic chat interface to a more structured and effective workflow.

Frequently Asked Questions (FAQ)

1. Is Kilo Code for JetBrains really free? Yes, the Kilo Code JetBrains plugin itself is free and open-source (MIT-licensed). You incur costs based on your AI model usage. You can use it for free with your own API keys (BYOK) or pay transparent, pass-through rates for models accessed via Kilo Gateway, with no markup on token usage.
2. How does Kilo Code handle remote development and JetBrains Gateway? Kilo Code is uniquely architected for JetBrains split-mode, which is the foundation for remote development via JetBrains Gateway. The plugin interface runs locally, while its backend components communicate efficiently with the IDE backend running on your remote machine (VM, server, or container), providing a seamless AI coding experience in remote environments.
3. Can I use Kilo Code alongside JetBrains AI Assistant or GitHub Copilot? Yes, Kilo Code can be installed and run concurrently with other AI plugins like JetBrains AI Assistant and GitHub Copilot. This allows developers to compare outputs, use different tools for specific tasks, or adopt Kilo gradually without disrupting existing workflows.
4. What kind of AI models can I use with the Kilo Code plugin? The plugin supports over 500 models through several access methods: hosted models via Kilo Gateway (OpenAI, Anthropic, Meta, etc.), bring-your-own-key (BYOK) for direct provider access, and local models via compatible endpoints like Ollama, LM Studio, or any OpenAI-compatible API server.
5. Is Kilo Code suitable for enterprise software development teams? Absolutely. Kilo provides enterprise-grade features through the Kilo platform, including centralized billing, usage dashboards, model policy controls, Single Sign-On (SSO), SCIM provisioning for user management, and detailed audit logs. This allows large organizations to govern AI usage, control costs, and maintain security and compliance standards.