AI Coding Rate Limits are RIDICULOUS Now - Here's How You Keep Scaling Anyway

This post addresses the practical challenge of LLM rate limits in agentic coding workflows. It introduces a strategy of model mixing and provider selection, demonstrating that not all coding tasks require the most powerful (and expensive) models. The author presents a comparative analysis of building applications using different model combinations (GPT-6 Astra + GLM 5.3 Flash vs. Claude Fable 5.1 vs. open models) to illustrate cost savings and quality equivalence. The core contribution is the practical application of this model-agnostic approach within an 'AI Software Factory' framework, leveraging tools like Archon for workflow orchestration and Neon's AI Gateway for accessing diverse open models.