Pick a depth. Each prompt opens in your AI pre-loaded with the lesson. Click a row to preview the prompt.
You don't need a degree in music theory to make good AI music, but you do need vocabulary — the exact words that make prompts land. Genre names (shoegaze, phonk, boom bap, ambient techno). Structural terms (verse, chorus, bridge, drop, breakdown, coda). Instrument names (Rhodes, TR-808, koto, cello ensemble). Tempo ranges (75 BPM for a slow ballad, 174 BPM for drum and bass). Key relationships (A minor's a good default for melancholy, C major for anthemic). The rest — voice leading, secondary dominants, modal interchange — can wait. This task gives you the 40-word vocabulary that unlocks 80% of AI music prompt precision.
The 40-word music-theory-for-AI-prompting cheat sheet. Print it. Reference it every session for the next 30 days until it's second nature.
# The 40-word cheat sheet for AI music prompting.
STRUCTURE = [
"intro", "verse", "chorus", "bridge", "pre-chorus",
"drop", "breakdown", "buildup", "outro", "coda",
]
ARRANGEMENT = [
"sparse", "dense", "layered", "stripped-down",
"half-time", "double-time", "syncopated", "on-the-grid",
]
INSTRUMENT_KEYWORDS = [
"Rhodes electric piano", "vintage synth", "TR-808 kick",
"acoustic guitar fingerpicking", "cello ensemble", "orchestral strings",
"vocal chops", "sub bass", "field recording",
]
MOOD = [
"melancholic", "hopeful", "menacing", "playful",
"cinematic", "intimate", "anthemic", "washed-out",
]
TEMPO_HINTS = {
"slow ballad": "60-75 BPM",
"hip-hop": "80-100 BPM",
"pop": "100-130 BPM",
"house": "120-128 BPM",
"drum and bass":"170-180 BPM",
"hardcore": "180+ BPM",
}
# A good prompt uses 1 from each list:
example = "melancholic downtempo, 85 BPM, sparse arrangement, Rhodes electric piano over sub bass and vinyl crackle, verse-chorus-verse-bridge-chorus"
print(example)
python3 main.py