Beyond Babel, Python all around the world, one function at a time

synapz is a research prototype exploring how large language models can adapt teaching content to different cognitive styles. built over a 48-hour sprint with a strict $50 api budget, this project implements a scientific framework to test whether adaptive teaching produces measurably better results than static approaches.

synapz is a research prototype exploring how large language models can adapt teaching content to different cognitive styles. built over a 48-hour sprint with a strict $50 api budget, this project implements a scientific framework to test whether adaptive teaching produces measurably better results than static approaches.

Cognitive maps as excel files

🤖 Official code for "The LLM Team Composition Paradox." This research challenges the "complexity = better" assumption by proving the optimal LLM agent team (single, homogeneous, or diverse) is contingent on the problem type, implementing a Hierarchical OODA-Belbin framework.