Gary K

How much better do the models have to get before you'll stop reading the code?

I've been getting a TON done with Fable today and I'm not hitting rate limits. Wanted to share some tips on how I'm doing that 1. I only use Fable on "high" effort for now. xhigh is token hungry. max/extra is a furnace with worse outputs than lower options imo 2. I taught Claude Code how to use Codex as a fallback for lots of implementation tasks. GPT-5.5 is incredibly steerable, and Fable can learn how to steer it 3. I wrote up a big section in my CLAUDE[.]md on how to prioritize different models for different work when orchestrating workflows and subagents 4. Things that are unnecessarily token hungry (computer use, codebase analysis, etc), I do with other models and report results back to Fable

I just paid $321 for a coding session where Fable 5 refused to do the work. Here is where the work actually went: Fable 5: $78 Opus 4.8: $242 75% of the session got routed to Opus because the new classifiers kept flagging routine coding work as cybersecurity risk. The model I chose did a quarter of the job. The fallback did the rest. Anthropic said a small fraction of tasks would fall back. My receipts say otherwise.

Fable 5 is back.