From Idea to Master

A repeatable pipeline delivers more reliably than any single trick.

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The problem

AI music work tends to stall in two places: not knowing where to start and not knowing when it is finished. A clear pipeline solves both by splitting creation into checkable stages, each with a defined exit.

The pipeline

Seven stages: brief, prompt, generate candidates, select, edit, mix and master, deliver. Each has an output and a checkpoint. The brief states deliverable, style, length, use and rights requirements. Generate widely and edit little at the candidate stage, then rank by structure and texture. Edit only what must be fixed. Export to the delivery standard.

Practice

Store each stage's output as a file instead of leaving it inside a tool. Put a continue-or-return decision between stages: wrong structure goes back to generation, wrong timbre is solved in editing. Set a time box so the candidate stage does not become endless sampling. Before delivery, run the checklist: form, artefacts, loudness, mono, metadata, rights notes.

What to listen for

In the ballade, the traces polishing leaves; in the drum material, how the raw generation differs from the final; in the quartet, why structure needs managing. A pipeline is worth it when every delivery can be explained.

Sources

• 音乐制作的阶段划分，依制作实践公开资料核对，未抄原文
• 交付前的检查项，依母带与发行通识核对，未抄文本

Used for fact-checking only; all prose is original.