I wanted to share a project I've been refining, called llmunix-starter. I've always been fascinated by the idea of AI systems that can adapt and build what they need, rather than relying on a fixed set of pre-built tools. This is my attempt at exploring that.
The template is basically an "empty factory." When you give it a complex goal through Claude Code on the web (which is great for this because it can run for hours), it doesn't look for existing agents. Instead, it writes the markdown definitions for a new, custom team of specialists on the fly.
For example, we tested it on a university bioengineering problem and it created a VisionaryAgent, a MathematicianAgent, and a QuantumEngineerAgent from scratch. The cool part was when we gave it a totally different problem (geological surveying), it queried its "memory" of the first project and adapted the successful patterns, reusing about 90% of the core logic.
I think it's particularly useful for those weird, messy problems where a generic agent just wouldn't have the context—like refactoring a legacy codebase or exploring a niche scientific field.
The template is basically an "empty factory." When you give it a complex goal through Claude Code on the web (which is great for this because it can run for hours), it doesn't look for existing agents. Instead, it writes the markdown definitions for a new, custom team of specialists on the fly.
For example, we tested it on a university bioengineering problem and it created a VisionaryAgent, a MathematicianAgent, and a QuantumEngineerAgent from scratch. The cool part was when we gave it a totally different problem (geological surveying), it queried its "memory" of the first project and adapted the successful patterns, reusing about 90% of the core logic.
I think it's particularly useful for those weird, messy problems where a generic agent just wouldn't have the context—like refactoring a legacy codebase or exploring a niche scientific field.
Thanks for taking a look!!