I’ve been trying to make AI music for a project, but I keep getting stuck on which tools to use, how to write good prompts, and how to make the songs sound original instead of generic. I need help figuring out the best beginner-friendly way to create AI-generated music that actually sounds good.
Use a 3-step setup.
-
Pick the tool by goal.
If you want full songs fast, use Suno or Udio.
If you want control, use a DAW plus AI helpers. Ableton, FL Studio, Logic. Then add tools like Synthesizer V for vocals, Splice for samples, and stem splitters like Ultimate Vocal Remover. -
Write prompts like a producer, not a fan.
Bad prompt:
“make a cool sad song”
Better prompt:
“92 BPM, D minor, dry female vocal, tight kick, sparse bass, indie pop drums, short chorus, lyrics about missing a train and pretending you do not care”
Prompt parts to include:
genre
tempo
key or mood
vocal type
instrument list
mix style
song structure
lyrical topic
one weird detail
The weird detail matters. Example:
“add a detuned toy piano in the pre-chorus”
Stuff like tht stops generic output.
- Edit the result.
Raw AI songs sound samey becuase people keep the first render. Do 5 to 10 generations. Take the best 20 seconds from each. Rebuild in your DAW. Change chord voicings. Replace drums. Re-record vocals if needed. Human timing helps a lot.
For originality, avoid naming famous artists in prompts. Describe traits instead. Example:
“breathy close vocal, clipped drum room, chorus with stacked thirds”
This gives style without cloning.
My best results came from making lyrics first, then melody, then production. If you start with “make me a hit,” you get mush.
I’d add one thing @techchizkid didn’t really hit hard enough: stop expecting one tool to do everything. That’s usually where people get stuck.
What worked for me was splitting the process into lanes:
- idea generation: Udio/Suno
- lyrics: Claude/ChatGPT or just write your own rough draft
- arrangement: DAW
- cleanup: RX, stems, EQ, timing fixes
- final polish: real plugins, not more AI
Also, slight disagreement on prompts: super detailed prompts are useful, but sometimes they overconstrain the model and you get stiff, predictable junk. I’ve had better results with a “core prompt + 1 contrast.” Example:
“dream pop track, 84 bpm, intimate vocal, soft tape texture, but with an ugly distorted bass in the hook”
That contrast is what makes it feel less stock.
For originality, build a reference board before prompting. Not artists, but traits:
- drum feel
- vocal distance
- chord density
- texture words
- emotional arc
Then keep a “no generic stuff” list:
- no stomp claps
- no cinematic risers
- no giant reverb piano
- no empty motivational lyrics
Biggest tip tho: treat AI output like raw material, not the song. Chop it up, resample it, pitch sections, reverse tails, rewrite half the lyrics. If you just press generate and export, yeah, it’ll sound like everybody else lol.
One angle I think @techchizkid and the other reply only partly cover: start with the ending. If your project needs a sync-friendly background cue, a TikTok-style hook, or a full “artist” song, the workflow changes a lot. People get stuck because they’re using the same AI music process for three totally different goals.
My take:
- Pick the output format first
- full song
- instrumental bed
- vocal demo
- sample source
-
Use AI for the weakest part of your skill set only
If you can already arrange, do not let AI arrange. If you can write lyrics, do not ask it for full lyrics. AI is most useful where you are slow, not where you are strong. -
Prompt with production terms, not just genre terms
Instead of “make a cool indie song,” try stuff like:
- dry vocal
- narrow stereo verse
- bass enters late
- no cymbals until chorus
- chorus lifts by harmony, not loudness
That tends to shape the record more than naming five genres.
I actually disagree a bit with the “originality comes from heavy editing” idea being the main fix. Sometimes generic happens earlier, at composition level. If the melody contour, chord loop, and lyric phrasing are all obvious, no amount of polishing saves it. Regenerate early instead of trying to rescue bland source material forever.
Good originality test:
- mute vocals, is the instrumental identifiable?
- read lyrics without music, do they still sound human?
- play first 10 seconds, does it establish a point of view?
Pros for ':
- can improve readability if you’re organizing prompts, lyric versions, and revision notes
- useful if you need a cleaner workflow
Cons for ':
- won’t make weak musical decisions stronger
- easy to over-systemize a creative process
Best practical move: generate 10 rough ideas fast, keep 2, then finish 1 manually in your DAW. That ratio usually beats obsessing over one prompt.