A Smooth Sea Never Made a Skillful Sailor

In my last post I compared Codex, Claude, and GLM 5.2 and landed on two $20 monthly plans as the setup that gets the work done. Two weeks in, I changed that setup: Claude moved to the $200 annual plan, which is essentially the $20 monthly plan at a discount, and Ollama moved to the $20 Pro plan. Same shape, better price. This post is a follow-up on two other fronts. First, the workflow itself has firmed up: GLM 5.2 does the assessment and planning on less critical projects, Fable 5 does the assessment on complex or mission-critical projects and validates GLM 5.2's findings, and Sonnet 5 handles general-purpose coding once Fable 5 has set the plan. Second, I ran the experiment I suspected would go badly and paid for AI by the token, once through an OpenAI API key with the GPT-5.6 Terra model and once through Ollama top-up credits. The numbers are worth sharing because the gap is not small. It is the difference between 3-4 days of work and 30 minutes. The Workflow: Who Assesses,...

The question I keep getting asked is which AI coding assistant I actually use day to day. The honest answer is that I use more than one, and the reason is that none of them is uniformly the best. Each one has a lane where it clearly wins, and each one has a failure mode that pushes me back to the others. This post is a practical comparison of three tools I have spent real time with: Codex, Claude, and GLM 5.2. I am not interested in benchmark scores or leaderboard positioning. I care about how these tools behave across the full lifecycle of a project: initial scaffolding, iterative refinement, design polish, and long-running reliability. The short version: GLM 5.2 has replaced Codex as my daily driver for implementation work. Codex failed the wife test, which is what pushed me to switch. Claude is strong on design and polish but showed a huge regression after two weeks of use. GLM 5.2 is great at identifying tiny lingering issues and regressions, but the last 24 hours of work showed...