Bottom line:Workout playlists perform better when music BPM is aligned with training phases, not full-session high intensity.

Why this approach works

Most weak AI playlists come from under-specified prompts. When the prompt lacks constraints, outputs drift toward generic popular songs.

A stronger method is to define scenario, exclusions, version preference, and strict output format before generation.

Then run a pilot set first, validate quickly, and expand only after direction is correct.

Execution workflow

1. Define scenario variables (time, context, energy curve).
2. Set constraints (language ratio, era, exclusions, version preference).
3. Force output format: one line per song, "Song - Artist" only.
4. Test with a small pilot list, then scale and import to Apple Music.

Copy-ready Prompt Template

Use this as a base and replace scenario variables:

请生成一个45分钟力量训练歌单，分三段：
- 热身10分钟：BPM 90-110
- 主训练25分钟：BPM 115-135
- 收操10分钟：BPM 80-100

约束：
1) 中文50%，英文50%
2) 避免情绪过度悲伤的歌曲
3) 不要同一歌手连续出现
4) 输出18首

输出格式：每行“歌名 - 歌手”，不要编号，不要解释。

Support Boundaries (important)

Playlist-link import supports Spotify, YouTube Music, Deezer, NetEase, QQ Music, KuGou, and Qishui/Douyin (douyin.com entry). Single-link conversion supports Spotify, YouTube Music, Deezer, and NetEase only; QQ Music, KuGou, and Apple Music links return unsupported.

Frequently Asked Questions

How many songs should I generate first?

Start with 15-20 as a pilot. Expand only after direction is validated.

Why enforce "Song - Artist" output?

It reduces ambiguity and improves import matching quality.

Should I optimize for one model only?

Not necessarily. Keep one master structure and tune model-specific phrasing.

Is small mismatch after import normal?

Yes. Cross-platform licensing/version differences are expected.

Continue Reading (AI Playlist Hub)

• AI Playlist to Apple Music (Main Guide)
• Text-to-Playlist Import Guide
• Playlist Sync Troubleshooting
• ClipTunes
• Song Link Converter