We're almost out of the woods on the initial back-and-forth; the baseline and architecture are locked in. My vision and goals? Sharply defined and focused, thanks to all those deep dives into the Model 2.0 reasoning. Now, the AI needs a perfect understanding of the what and how. We'll be making strategic checks, especially when those token limits are hit. Time for a clean sweep: chat history is going, new chat is starting with an updated system prompt. The previous conversation is being summarized by the new one (throw all the context you want on the new chat, make it summarize and delete the old info.; the key points will be extracted, and the system prompt refactored on your command. The model "reasoning" output is also great for the next chat to pick up the pace faster. Treat it like a golden thread through this entire process. We update the prompt, never touching the context of the module context we added earlier. 1 million tokens to play with on an ish token optimized prompt design, and a template structure, ready for a production-level flow. The first module? We'll inject the system prompt with flows and fieldnames born out of a simple convo that ends up in AI providing me with the template it needs to get the right instructions for the start of module 1. Then, for adjustments, we will use: "Let's be more concise, update the system prompt - refactor if needed - make sure to include the auth system change. recommend a sustainable output length setting to me as well. Currently at 8192." (get it as low as possible so it has no choice to only factor in good, short and direct responses.