Claude Code users burn weekly limits faster with Fable 5.2 and Opus 5.5

The author argues that user complaints about rapid AI subscription limit exhaustion stem primarily from inefficient model mixes rather than broken meters or tightened limits. By running expensive frontier models like Anthropic's Claude Fable 5.2 on every turn instead of routing simpler tasks to cheaper models, users quickly burn through model-specific caps. The article suggests adopting a structured model handoff where high-cost models handle complex planning and debugging, while cheaper models manage implementation and background tasks. Open article →