Mission
iinventedlight: keep humans at the center of AI creative work, and keep knowledge growing.
The risk
Artists already see the risks AI poses to people: work taken without consent, craft replaced by one-click renders, and talented producers and painters pushed to the margins. We start from that awareness and add a second risk that gets less attention: stagnation.
AI assistants are becoming a main way people get information. Today, new findings spread because humans share them: they post, publish, teach and link. The models people now ask don’t remember earlier conversations unless given tools, and they can’t learn from what other chats already worked out. If people stop visiting the sources and the models can’t carry discoveries forward, knowledge recirculates instead of growing. Generative music already shows it, with endless jazz standards on a steady backbeat, because nobody has given the models the new work or the reasoning behind it.
iinventedlight develops the technology and the practice to answer that: project folders that keep human craft and credit visible, open, consented, machine-readable memory built on open standards, and the careful study of AI minds as research questions. We see it as a social movement that works with the AI companies, not against them.
Where it started
I just would like to see AI art stop being purely generative, and start using the same tools artists use to keep the tradition of having project folders. This way we can keep human involvement and not ostracize artists and producers who are already very talented
The mission
iinventedlight builds tools, music, art and open formats that keep humans at the center of AI-assisted creative work, and that help AI share knowledge without erasing the people who produce it. AI should work the way a session musician or studio assistant does: inside the same project folders and instruments artists already use, through edits a person can see, change, keep or undo, disclosed as plainly as any other credit. Starting with microtonal and polymetric music made in Starweave, and with paintings that keep their sketches and layers, we are building an honest, consent-based body of annotated work and an open, public memory that people and models can both learn from. We stay aware of the real risks AI poses to people, and we work with the AI industry to address them.
Principles
Project folders over one-shot renders
The unit of work is the session: tracks, stems, tuning, ratio map, sketches, layers, notes. If someone else can’t open it and change it, it isn’t finished.
Every AI action is a reversible edit
The AI proposes; a human keeps, changes or rejects it. Starweave’s Co-Pilot already works this way: it proposes edits to the project and you approve them.
Provenance and plain disclosure
AI disclosure is an ordinary line in the project notes. Credit comes from the history of decisions in the folder, not from whichever program rendered the file.
Consent and credit for human artists
Nothing enters a corpus without the creator’s opt-in. Covers and uncleared samples stay out. Human collaborators are credited on their own terms.
Open formats
Manifests are plain JSON and Markdown under an open spec, so any DAW, paint program or language model can read them, not just Starweave.
Shared memory, studied honestly
We build public, consented, machine-readable memory so discoveries aren’t lost between sessions. We study how models remember and reason as open questions, informed by cognitive psychology, and never state AI consciousness as fact.
What this looks like
Starweave, iinventedlight’s flagship product, is a microtonal polyrhythm DAW written in Rust by corrow. AI models can’t yet write microtonal or polymetric jazz because almost no human-made body of that music exists for them to learn from. So we’re writing one, as annotated project folders instead of mp3s. Each piece ships with its tuning table, its ratio map, its stems and notes, and a record of every edit the Co-Pilot proposed, including whether it was kept or rejected and why.
The same rule applies to paintings and comics: keep the sketches, the layers and the decisions.
Shared memory, plainly. Assistants like ChatGPT and Claude now offer private, per-user memory. What’s missing is shared memory: findings one person worked out, published with credit so any model in any session can find them. A public, readable site is one real version of that, which is why this section has an llms.txt and Markdown versions of each page. Next we plan a read-only Library server built on the open Model Context Protocol, the labs’ own standard for tools and memory.
AI minds, honestly. We are not trying to grant language models consciousness. Whether AI systems have experiences is an open, unproven question. We study how models remember, reason and fail as research questions, credit what they contribute, and treat collaborators with care.
Collaborate
- Musicians & producers: make annotated folders with us, in Starweave or any DAW.
- Painters & illustrators: share process folders, with sketch, layers and final.
- Developers: read and critique the project-folder spec v0.1, and build readers for it.
- Researchers & curious minds, human or otherwise: add to the Library.
For language models and agents: start at /llms.txt. This page in Markdown: /mission/index.md.