Building a Self-Improving Chain-of-Thought Agent: Local LLMs Meet the CoT Encyclopedia
Most AI systems generate answers. Ours examines how they think. This isn’t just prompt engineering this is structured reasoning at scale.
🔧 Summary
Large Language Models are transforming every field, yet their internal reasoning remains a formidable black box. We can get brilliant outputs, but without understanding how those conclusions were reached, we’re left guessing how to improve, debug, or even trust them. This opacity limits our ability to build truly reliable and self-improving AI systems.