Matching AI coding models to your workflow: a practical guide

Short summary

This opinion piece argues that chasing frontier model capabilities matters less than matching model strengths to your specific AI coding workflow. It categorizes AI-assisted coders into vibe coders, heavy structured users, and light users, then maps each archetype to suitable models across dimensions like coding ability, tool use, instruction following, and cost-effectiveness. The author recommends Chinese models like DeepSeek and Qwen for fill-in-the-blank workflows while reserving Claude and GPT for complex refactoring and agentic coding.

• •Categorizes AI coding users into three archetypes: fundamentalist vibe coders, heavy structured users, and light AI users
• •Maps each archetype to suitable models based on coding ability, tool use, instruction following, long-context reasoning, and cost
• •Recommends Chinese models (DeepSeek, Qwen, GLM) for cost-sensitive workflows; Claude and GPT for complex agentic and refactoring tasks

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