How to Write AI Music Prompts — A Guide for Non-Musicians

You don't need to read music, play an instrument, or know what a chord is to make a song you actually like with AI. The difference between a generic result and the song you imagined is almost entirely in what you type into the box.

AI music tools have gone mainstream. In a 2025 LANDR survey of more than 1,200 music makers, 87% said they already use AI somewhere in their process. The tools are capable and widely adopted; for someone starting out, the barrier isn't skill anymore — it's knowing how to describe what you want.

And most beginners type too little.

The one-word trap

The most common beginner move is to type a single word — "pop," "sad," "lofi" — and hit generate. It's also the move that produces the most forgettable results.

In a cross-platform sample of about 650,000 AI music generations, the length of what people typed splits into two camps. About 41% of prompts ran past 1,000 characters — full lyrics or detailed direction. Only about 9% came in under 50 characters. There's very little in between. The people getting specific songs are writing paragraphs; the people getting wallpaper are writing tags.

You don't need 1,000 characters. You need more than one word. A good starting target is one or two complete sentences — the kind you'd use to describe a song to a friend who's about to play it for you.

Describe the scene, the mood, and the motion

A prompt the model can actually use names three things: the scene the song is for, the mood it carries, and what the music is doing. Genre on its own barely moves the result.

In the sample, mood and emotion words show up about as often as instrument names. People describe how a song should feel as much as what's in it — and feeling is the part the model can't guess from a genre label.

A reliable template:

[setting or occasion] + [mood] + [who's singing] + [what the song does]

So "pop" becomes:

An upbeat synth-pop song for a summer road trip, bright and carefree, a young female lead, building to a big sing-along chorus.

And "sad piano" becomes:

A slow, intimate piano ballad about missing someone, late-night and restrained, a soft male voice that stays quiet until the final chorus.

"Motion" is the part beginners skip. Does the song stay steady, build, or drop? "Builds to a big chorus," "stays mellow throughout," "drops hard after the first verse" — these tell the model the shape, not just the vibe.

The sound palette: name the voice, anchor a few instruments

After the scene, two things shape the sound most: the voice, and two or three anchor instruments.

Vocals are the default. In the sample, vocal descriptions outnumber requests for purely instrumental tracks by roughly 17.6 to 1 — if you don't want singing, write "instrumental," or you'll get a voice.

If you do want singing, describe the singer in three strokes: identity (young female, older male, a child), texture (raspy, breathy, smooth), and delivery (rapped, belted, whispered).

For instruments, two or three are enough — pile on ten and they blur together. Name the ones that define the song; the model fills in the rest. Among the instruments people did name, bass and guitar led — the foundation shapes the feel more than the solo.

Two palettes at the same tempo produce completely different songs:

a warm, slightly raspy male voice, fingerpicked acoustic guitar, soft upright bass

a bright female voice with light auto-tune, punchy 808 bass, glassy synth plucks

Structure tags are the cheapest control you're not using

If you've ever generated a song that felt like a two-minute loop — no build, no payoff, the same idea circling — this section is the fix.

The songs you love have parts, and you already know them by ear even if you've never used the names. The verse is the storytelling part: it moves things forward, usually a little quieter. The chorus is the part that keeps coming back — the bit you can hum after one listen, usually the biggest. A bridge shows up once near the end, changes the scenery, and makes the final chorus hit harder.

Structure tags let you hand the model that shape directly. Write the section name in square brackets, then a few plain words about how that part should feel:

[verse] quiet, just guitar and voice
[chorus] full band, big harmonies
[verse] add a steady drum beat
[bridge] strip back to piano
[chorus] biggest version, lift the energy

You don't have to write any lyrics to use them. Even bare tags — [intro] [verse] [chorus] [verse] [chorus] [outro] — turn a loop into a song with a recognizable shape.

And this isn't a niche trick. In the sample, [chorus] appears around 453,000 times and [verse] around 410,000 — six of the eight most common words in the entire dataset are section tags, not moods or genres. Most tutorials teach beginners to polish their mood words. The people who've made a lot of songs spend their words on structure.

Melody and voice, without the jargon

Structure tags stay simple because they just mark sections. The melody and the singing are worth steering too — and you can do it in plain words, no music terms needed. Just say what you want the tune to feel like:

• A chorus that sticks: "a catchy hook that lifts and rises at the end."
• Words you can follow: "clear, one note per syllable, easy to sing along." Or the R&B version where one word curls through several notes: "lots of vocal runs."
• Energy: "short, punchy notes." Calm: "smooth, flowing, connected notes."
• For rap: "a laid-back flow," or "a fast, tight flow."

Power users sometimes write these as bracketed tags — [soaring melody], [melismatic vocals], [staccato] — and they work on tools that support them. But you don't have to learn the vocabulary. Plain description gets you most of the way, and it's the same instinct as the rest of this guide: say what you want to hear.

The other dials: tempo, key, length

Tempo, key, and length are worth setting only when you have a specific reason. The rest of the time, your description already implies them.

• Tempo (BPM) is just how fast the song goes — beats per minute. Rough homes: a slow ballad sits around 60–80, most pop 100–130, house and EDM near 120–130, hip-hop 80–100, drum & bass 165 and up. Set a number when the song has to match something external — a video cut, a dance, a running pace. Otherwise "slow," "mid-tempo," or "driving" does the job.
• Key decides how high or low the song sits. Most non-musicians should leave it blank; the model picks something singable. Only set it if you're matching an existing track or a specific singer's range.
• Length matters when the song fills a slot — a 30-second clip, a 15-second intro. If you don't say, you'll usually get a full-length arrangement.
• Simple vs advanced mode is the one toggle worth understanding. Simple means you describe the song in plain words; advanced means you type the lyrics and structure tags yourself. In the sample, advanced edges out simple in real use — about 46% of generations versus 38%. Start simple, switch to advanced the moment you want to control the song's shape.

A starting prompt for six common styles

Here's that framework as prompts you can copy. Each row names a setting, a mood, a voice, and what the song does. Find the one closest to what you want and change the specifics to fit your song.

Notice that none of them is a single word.

What people actually make with this

You don't need a release plan to justify making a song. One AI tool, Suno, reportedly generates around 7 million songs a day. Most of it is everyday and personal — which is exactly where non-musicians have the advantage.

That long tail is the real story for hobbyists. The 0.6% of birthday songs and 0.4% of jingles aren't rounding errors — they're thousands of songs made for one specific person or purpose. A few of the most common:

• Content creators — background music for videos, podcasts, and streams, without borrowing someone else's copyrighted track.
• Song gifts — a track written for one person: a birthday, an anniversary, a wedding first dance, a farewell.
• Small businesses — a 20-second jingle, an ad bed, or in-store music on a loop.
• Just for you — a lullaby with your kid's name in it, or a rough week turned into three minutes of something.

None of these need to chart. They need to be about the right person or moment, and that's the one thing only you can put in the prompt.

The model supplies the craft. You supply the specifics. For the bigger picture of who's making AI music and how, see our breakdown of the data.

If there's one habit worth changing, it's the one-word prompt. A scene, a mood, a named voice, and a few section tags will get a non-musician most of the way to the song they're already hearing — no theory required.

And if even that feels like too much, you don't have to do it yourself. In Lacuna, you can describe the song to the agent in plain language and let it handle the prompt — it asks what you're going for, adjusts the scene, voice, structure, and tempo with you, and generates the track once it matches what you had in mind.