Flip Your AI Dev Workflow: Generate the Prompt First, Then the Code (4 Phases)
Instead of telling AI to write code directly, have it translate a vague goal into an executable prompt structure first, then use that structure to drive code generation. Phase 1 Intent → Phase 2 Structuring → Phase 3 Tool-Level → Phase 4 Implementation.
Instead of asking AI to write code → ask it to generate the prompt structure first, then drive code from the structure (4 phases: intent capture → prompt structuring → tool-level prompts → implementation)
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The author's testing shows that treating the prompt as an intermediate translation layer is more reliable than prompting for code directly. The full prompt system runs about 50k tokens — drop it into Claude and let it run end to end. The answer to "why do two models give wildly different results from the same prompt" is this: the model isn't dumb, the human-machine interface is fuzzy. Recommended learning for mid-to-senior AI engineers.
4 phase 完整輸出：Phase 1 簡短意圖 / Phase 2 5 段結構（subtask + constraints + success + tool-use + checkpoints）/ Phase 3 N 個 executable prompts / Phase 4 由 Phase 3 驅動的 code + human checkpoint
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