TIP•RED•EYE

R.I.P. paying full Opus prices for every single AI task. A properly routed open-source Claude stack can replace $200+ a month in frontier model spend. It is not as easy as just swapping the model name and hoping for the same output. But if you start today, you can have GLM 5.2 wired into Claude Code, a local model running on your machine with zero token cost, and your first autonomous loop built, verified, and running unsupervised by end of this week. I usually charge $99 for access to this playbook but today, it's free. Like this post + comment 'STACK' and I'll DM you the full guide for free. The guide covers three things. How to set up local models on your hardware in 15 minutes using Ollama, which model runs best at your RAM level, and the decision engine that tells you which of your tasks belong on local, which go to a cheap API like GLM 5.2 at $1.40 per million tokens, and which 20% actually justify Opus. How to wire GLM 5.2 into Claude Code in under 5 minutes by editing one JSON config file so the same harness, skills, and workflows you already have run on a 5x cheaper engine for 80% of your tasks. How to stop prompting and start building loops. The 4-condition test that tells you which tasks are ready to loop, the four blocks every loop needs, and the copy-paste prompt that builds your first loop orchestration skill with training mode, memory, and a verification step included. (Must be following, or I can't message.) Taking this down in 48 hours.