We trained nothing

The claim, in full: songcode has no audio model. We trained nothing. A general-purpose language model writes code, and your browser plays that code with synths and drum machine samples.

Each sentence there is doing a job. This post goes through them.

No audio model

Services like Suno and Udio run models that generate sound directly. To learn what a hi-hat or a human voice is, a model of that kind studies a very large number of recordings. Which recordings, and on what terms, is the argument the music industry has been having in court since 2024.

songcode has no model of that kind. No recording goes in when you generate, and none comes out until your own browser renders one.

We trained nothing

songcode does not train or fine-tune any model. It sends text to a language model made by Anthropic or OpenAI and gets text back.

Where the sound comes from

Two sources, both in your browser.

Synthesis. Oscillators, filters, envelopes, FM, reverb, delay. This is arithmetic. A sawtooth wave is a formula. songcode’s own drum kits and instrument patches are built this way, with no recordings in them.

Samples of single sounds. A TR-909 kick drum. A clave. A piano note. A marimba bar. These are short recordings of instruments. Most come from the sample library that ships with Strudel, the open source engine songcode runs on. An acoustic drum kit, a kalimba and a marimba come from VCSL, a CC0 sample library. We say “synths and drum machine samples” and never “fully synthesized”, because the second one would be false.

Where the claim stops

Four places.

The language models have training data of their own. Anthropic and OpenAI train their models on very large amounts of data. We do not train those models and we cannot audit what went into them. songcode uses them for text only: text in, text out. What they know about techno they presumably learned the way they learned everything else: from writing. Music theory, synthesis manuals, forum threads, and code, including code the live coding community has published over the years. When a model writes a convincing acid line, it is working from how people have described and notated the form in text.

Those companies have copyright disputes of their own. Music publishers including Concord and Universal sued Anthropic in October 2023 over song lyrics, and that case is still running. In November 2025 a Munich court ruled for the German collecting society GEMA against OpenAI, also over lyrics, and that ruling is under appeal. Lyrics are text, and songcode writes none. You should still know who is upstream of us.

A language model can write notes. It cannot reproduce a recorded song, a voice or a performance. Its output is text, and the engine has oscillators and short samples to play that text with. Notes are different. A model that knows a famous riff as a sequence of pitches could type it out, the same way a person at a keyboard could. Compositions are protected whoever types them, so prompting for someone’s melody is on you. What songcode adds is visibility: every note in a track is on your screen, in plain text, where you can check it.

Strudel’s library includes a few drum breaks. Almost everything in it is a single hit or a single note. The exception is a small set of break loops: short stretches of drumming sampled from commercial records. songcode’s model is not told they exist, and when a genre calls for a breakbeat the model writes it hit by hit on a drum kit. The engine will still play one of those loops if you type its name into the code yourself.

What a style prompt gets you

Ask for dub techno and you get a muffled kick, one chord stab and a lot of filtered delay. That is the genre as people describe it, and genre conventions belong to nobody.

Type an artist’s name into a prompt and the model answers with what has been written about that artist’s sound: the tempo, the drum machine, the kind of chords. It works from description. It has no recording to imitate, and there is no voice cloning because there are no voices.

Why we bother saying it this carefully

“Ethical AI music” has become a slogan, and slogans get vague. Every service in this field now describes its training data in reassuring words. Some of those descriptions are specific and checkable. Some are a single sentence.

Ours is checkable. Open a track and read it. The file contains note names, drum hits, filter values and effect settings. That file is the entire output of the AI.

We put the other services’ descriptions side by side, in their own words, in the AI music map.

Sources

Checked 11 November 2026.

• Music Business Worldwide on the music publishers’ case against Anthropic and the Chartlex litigation tracker for case status.
• Reed Smith on the GEMA rulings in Munich, including the OpenAI appeal.
• Strudel, the engine and its sample library.