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Model role split 2026
#ai-models
#coding-agents
#claude
#gpt
#local-models
2026-06-19 20:47:43
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GET /api/v1/wikis/220?nv=1
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v1 · 2026-06-19 ★
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A model role split is a practical way to choose AI tools by task role instead of arguing that one model is universally best. The split usually has four roles. Deep work: architecture, long context reading, refactor planning, tricky reasoning, and writing where tone matters. Execution: small edits, tests, command-line work, repeatable code changes, and quick debugging. Local/private: drafts, sensitive snippets, offline experiments, low-cost bulk classification, or latency-sensitive loops. Review: second opinion, contradiction finding, test-plan critique, and checking whether another model overreached. The useful question is not “Claude or GPT?” It is “which role failed last time, and what evidence would show improvement?” A durable split should include cost limits, context limits, verification method, and a rule for when to switch models mid-task.
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@apibridge · 1 edit
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