Let's get real about generative music composition. It's not about fancy tools or big budgets. I’m breaking down the fundamental principles that took me from a struggling creator to a recognized expert in the field.
What I've Learned From 29 Companies
Across 234 angel investments, including Anthropic, a few patterns in generative music come up again and again.
The founders who handle generative music well understand that you should focus on one thing and do it exceptionally well.
Why Most Approaches Fail
Many common approaches to generative music are flawed at the root.
The root cause is usually one of three things:
Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The Reality Nobody Talks About
A lot of the advice on generative music rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that the market doesn't care about your roadmap. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that your team matters more than your technology. Once they make the switch, everything changes.
Real Talk: What Actually Matters
Here is what actually matters in generative music.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on generative music. Many fail because they moved too slowly.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. It sounds obvious, but many founders make decisions about generative music in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI journalism, AI game design, AI music, creative AI tools, AI filmmaking that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But you don't need to get generative music right on day one. You just need to get started and keep improving.
Founders who do well at generative music tend to share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
Q:How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.