# I route Claude Code steps by decision type, not difficulty > Source: > Published: 2026-10-07 04:05:32+00:00 In my Claude Code sessions, 69% of the output came from the top models (Opus, Fable), including reading a changelog, applying an edit I'd already decided on, and running tests. "Hard task → strong model" didn't fix it. Difficulty is the wrong signal: once a refactor is decided, applying it needs no judgment, however complex the code. What worked was routing by the kind of decision a step needs: I built this as **advisor-mode** in a plugin called **maddog**. Your main session splits the goal and sends each piece to a subagent (a separate Claude instance with its own context) on the right model. Only a short result comes back, and the main session checks it before accepting. Merges and pushes need your go-ahead. That's a rule the agents follow, backed by a hook in subagents, not a hard lock. My numbers, from my own 49 advisor-mode sessions against 30 sessions without it over the same weeks (output tokens, not cost or quality): In my use, small changes cost more to dispatch than to just do, and Haiku fails on tasks that only look mechanical. The plugin also has **section-by-section**, which reviews a skill or agent file with you one section at a time. Video (~100 s): [https://youtu.be/b_mFbVY5jzk](https://youtu.be/b_mFbVY5jzk) **Try it:** in Claude Code, run `/plugin` and search "maddog" on the Discover tab, then start with `/maddog:advisor-mode `. Run the main session on Sonnet or above. MIT, repo: [https://github.com/Harish-here/maddog](https://github.com/Harish-here/maddog) Do you route work across models, or run everything on one?