TL;DR
Be specific: instead of 'rock song', use 'gritty garage rock, raw vocals, lo-fi warmth, 70s fuzz guitar, intimate and defiant'
Generic Suno output happens when prompts lack specificity. The AI defaults to safe, middle-of-the-road choices when it does not have clear direction. The fix is adding unique combinations of descriptors that push Suno away from its defaults. Here is how to make your AI music sound distinctive.
[subgenre], [unusual mood combo], [specific instrument texture], [vocal character], [era reference], [production quality]
art pop, bittersweet euphoria, glitchy synths, vulnerable female vocals, late-night atmosphere, crisp yet warm
desert rock, hypnotic and heavy, fuzz bass, shouted vocals, 70s analog warmth, spacious mix
dark synthwave, nostalgic menace, analog arpeggios, vocoder vocals, VHS aesthetic, punchy drums
appalachian folk, haunted and hopeful, fingerpicked banjo, weathered male voice, front-porch recording, intimate
| Problem | Fix |
|---|---|
Sounds like everything else |
Add era + texture: '90s warmth', 'tape saturation', 'vinyl crackle' |
No personality |
Add unusual mood combos: 'melancholic yet defiant', 'joyful darkness' |
Forgettable melody |
Add: 'memorable hooks', 'unexpected chord changes', 'distinctive riff' |
Bland vocals |
Specify character: 'weathered', 'vulnerable', 'confident', 'whispery' |
Generic production |
Add texture: 'lo-fi warmth', 'crisp and punchy', 'spacious reverb' |
You are likely using the same general descriptors repeatedly. Suno learns patterns and defaults to safe choices. Break the pattern by adding unexpected combinations, era references, and specific texture descriptors. Each prompt should have at least one unusual element.
Layer specificity: instead of 'sad rock', try 'melancholic grunge, 90s Seattle sound, raw and vulnerable, distorted guitars, intimate vocal delivery, lo-fi cassette warmth'. Each additional specific descriptor narrows Suno away from generic defaults.
Single-word genres, common mood words (happy, sad, energetic), and missing production descriptors. A generic prompt: 'upbeat pop song'. A specific prompt: 'synth-pop, 80s nostalgia, shimmering arpeggios, breathy female vocals, gated reverb drums, neon-lit atmosphere'.
Suno does not support negative prompts directly. Instead, use specific positive descriptors that imply what you want. Rather than 'no autotune', specify 'raw natural vocals'. Rather than 'not generic', specify the exact unique qualities you want.
Generate at least 3-5 versions of each prompt before deciding it does not work. Suno has randomness built in. A great prompt might produce one mediocre and two excellent outputs. Save your best results and refine from there.
HookGenius generates optimized prompts and lyrics automatically.