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Use routing as a cost control layer
Claude Code Router shows a useful pattern: keep the coding interface you like, but send different kinds of work to different models. Use a strong default model for normal edits, a cheaper model for background chores, and a larger-context model only when the repo or prompt actually needs it.
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Separate thinking from execution
Reasoning-heavy planning and routine file edits are not the same job. Assign a stronger model to planning, architecture review, and hard debugging, then let a cheaper or faster model handle repetitive implementation steps. This keeps the expensive model focused where its judgment matters.
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Reserve long-context models for long-context problems
A million-token context window is useful when you need to reason across a large codebase, logs, docs, or several related files. It is wasteful for small fixes, tiny scripts, or isolated UI changes. Set a threshold for when long-context routing kicks in instead of making it the default.
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Treat usage reporting as untrusted until verified
The current rough edge is important: token and cost reporting inside the coding tool may be wrong when requests are routed externally. Check usage at the provider dashboard before assuming a setup is cheap. For a business workflow, document which command launches routed sessions and which launches the normal tool so costs stay intentional.
Why it matters
Small businesses do not need the most expensive AI setup. They need a reliable workflow that applies the right level of intelligence to each task. Model routing turns AI coding from a single subscription decision into an operating practice: spend more on planning and hard problems, spend less on routine execution, and verify the bill outside the tool.