At Continue, we've always believed that developers should be amplified, not automated. A key aspect of this philosophy is providing choices that let you customize your AI code assistant to fit your specific needs, workflows, and preferences.
The AI-native development landscape constantly evolves with new models, MCP servers, assistant rules, etc. emerging daily. Continue's open architecture connects this ecosystem, ensuring your custom code assistants always leverage the best available resources rather than locking you into yesterday's technology.
The Continue Hub makes it even easier to customize with a registry for defining, managing, and sharing building blocks (e.g. models, rules, MCP servers, etc). These building blocks can be combined into custom AI code assistants, which you can use with our open-source VS Code and JetBrains extensions (https://github.com/continuedev/continue).
Here are a few examples of different custom AI code assistants that we’ve built to show how it works:
A custom assistant that specializes in helping with data load tool (dlt) using their MCP: https://www.loom.com/share/baf843d860f44a91b8c580063fcfbf4a?...
A custom assistant that specializes in helping with Dioxus using only models from Mistral: https://www.loom.com/share/87583774753045b1b3c12327e662ea38?...
A custom assistant that specializes in helping with LanceDB using the best LLMs from any vendor via their public APIs (Anthropic, Voyage AI, etc): https://www.loom.com/share/3059a35f8b6f436699ab9c1d1421fc8d?...
Over the last 18+ months since our Show HN, our community has rapidly grown to 25k+ GitHub stars, 12.5k+ Discord members, and hundreds of thousands of users. This happened because developers want to understand how their tools work, figure out how to better use them, and shape them to fit their development practices / environments. Continue does not constrain their creativity like the vertically integrated, proprietary black box AI code assistants that lack transparency and offer limited customizability.
Before Continue Hub, developers faced specific technical challenges when building custom AI assistants. They manually maintained separate configuration files for different models, wrestled with breaking API changes from providers, and built redundant context retrieval systems from scratch. We've seen teams spend weeks setting up systems that should take hours. Many developers abandoned the effort entirely, finding it impossible to keep up with the rapidly evolving ecosystem of models and tools.
Our open-source IDE extensions now read a standardized configuration format that fully specifies an AI code assistant's capabilities—from models and context providers to prompts and rules. Continue Hub hosts these configurations, syncs them with your IDE, and adds versioning, permissions, and sharing. Assistants are composed of atomic "blocks" that use a common yaml format, all managed through our registry with both free solo and paid team plans.
We're releasing Continue 1.0 today, which includes both Continue Hub and the first major release of our Apache 2.0 licensed VS Code and JetBrains extensions. While the Hub currently only supports our IDE extensions, we've designed the underlying architecture to support other tools in the future (https://blog.continue.dev/continue-1-0). The config format is intentionally tool-agnostic—if you're interested in integrating with it or have ideas for improvement, we'd love to hear your thoughts!
by Andrey
Azimov