The origin of the Thinking Patterns platform. We begin by cataloging complex mental models, strategic AI reasoning pathways, and cognitive frameworks into a structured, queryable format.

Building the web application where users can explore, visualize, and interact with different thinking patterns. This acts as the visual front-end for the underlying logic engine.

• Developing a highly interactive, node-based visualization interface.
• Implementing advanced semantic search for discovering relevant models.
• Building user workspaces for saving and combining reasoning pathways.

To make Thinking Patterns accessible to developers everywhere, we architect a suite of modular npm packages. This allows seamless integration of our AI reasoning structures directly into any JavaScript/TypeScript codebase.

We initially designed the packages from ClaudeCode using Qwen, but AI models ultimately failed to reliably handle the logic up to this phase. Our 1st attempt failed in just 1 day. Acknowledging this as a research failure, we are continuously learning how LLMs operate and are preparing a 2nd attempt using a hybrid approach of AI alongside manual engineering.

• Documented our failed 1st attempt to contribute to open knowledge in AI research.
• Learning the deeper operational mechanics and logic boundaries of LLMs.
• Initiating Attempt #2: Combining automated AI assistance with rigorous manual engineering for absolute accuracy.

The simultaneous launch of the interactive web platform and the official publishing of the npm packages. Empowering developers to build smarter AI applications instantly.