Summary
Cole Medin explains how he keeps scaling AI-assisted development as rate limits on Claude Code and Codex keep tightening. After exhausting both his $200-a-month Claude Max and Codex plans days before their resets, he shows how to spend tokens strategically instead of using the most capable model for everything.
His core finding is that the planning and review steps deserve the strongest model, while implementation, the most token-heavy stage, can go to a smaller, cheaper one with little loss in quality. He tests this by building the same video game through his AI software factory in three configurations: open models only (DeepSeek V4.1 Flash for planning and review, GLM 5.3 Flash for implementation), Claude (Fable 5.1 planning and review), and Codex (GPT-6 Astra).
The video walks through the workflow shape used in every test: a GitHub issue feeds a planning node, then an implementation node, then a review loop with capped retries, and finally a test and build check before merge. Medin builds these pipelines with Archon, his open-source harness builder, and also covers simpler options such as markdown handoff documents and other multi-provider harnesses. It is a practical guide for developers who want to cut costs without losing reliability.
📺 Source: Cole Medin · Published September 24, 2026
🏷️ Format: Workflow Case Study
