The honest version
Main Act was built by one person and an AI. We are not hiding it. It is the reason the product is this good.
Most education companies that use AI to write their lessons spend real effort making sure you never find out. We are doing the opposite. Here is exactly how this was made, and why that should make you more likely to try it, not less.
What it would have taken before
A platform with five disciplines, a unified belt progression, more than two thousand curriculum entries and knowledge cards, over thirteen hundred narrated lessons, a five hundred song repertoire library, and real-time audio analysis for every one of them is a thirty-person company and a multi-year roadmap. Curriculum writers. Audio engineers. A narrator and a recording budget. Editors to keep it consistent.
That is the math that forces most training products into the same shape: charge a lot, cover the popular topics, and skip the rest, because every additional lesson is another salary. The breadth you wanted was never a content problem. It was a payroll problem.
What it took here
One musician who can write code, working alongside Claude as the author. The AI does not cut corners. It removes the economics that force everyone else to cut them. When the marginal cost of authoring the unglamorous middle of a topic drops to near zero, you stop having to choose between depth and price. So we kept both.
That is why the live-sound school goes all the way to stadium A1 work and Dante diagnosis instead of stopping at “here is a mixing board.” It is why every knowledge card teaches before it quizzes. It is why the whole thing costs less than twelve dollars a month instead of the price of one private lesson.
The part that is not automated
Claude wrote the lessons. A musician decided which ones were true. Every drill was run, every claim was checked against how the instrument actually behaves, and the lessons that read like a machine talking to itself were thrown out. The pitch detection, the spectral analysis, the EQ and compression engines, those are real DSP, hand-built, running live in your browser. The judgment of whether any of it makes you better is human, and it is relentless.
AI proposes. A musician disposes. Neither half ships this alone.
The questions a skeptic should ask
Is AI-written curriculum just slop?
It can be. Most of it is. The difference is not the tool, it is who is reading the output. Every lesson here was generated by Claude and then read, graded, and sent back for rewrites by a working musician who plays this stuff. The ones that read like a content farm got deleted. You can check this yourself: the free tools are zero-signup. If the content is thin, you will know in five minutes.
Why tell me at all? Other apps hide it.
Because hiding it is the tell. The reason a traditional course costs hundreds of dollars and still skips the unglamorous middle of a topic is that authoring is expensive, so companies author the marketable parts and stop. We did not have that constraint, so we filled the middle. That is the whole pitch. You should know why the curriculum is this deep.
So what did the human actually do?
Decided what to build and what to cut. Played every instrument and ran every drill to feel where the training was wrong. Wrote the DSP and the pitch detection. Judged tone, accuracy, and whether a lesson was honest. Claude proposes; a musician disposes. Neither half ships this product alone.
Does real-time feedback actually work, or is that AI hype?
It runs entirely in your browser with the Web Audio API: pitch detection for vocals, spectral and EQ analysis for mixing, synthesized backing tracks for repertoire. No DAW, no plugins, no upload. Open a free tool and sing or mix into it. It either responds in real time or it does not, and you can tell which.
Do not trust this page. Test it.
The whole argument rests on whether the content is actually good, and you do not have to take our word for it. The free tools require no signup. Run one. If the training is thin, you will know fast, and you should walk. If it is not, you just found out what one person and an AI can build when nobody is around to tell them it is impossible.
Built by John Brunsfeld, a developer who plays music, with Claude as co-author.