Sahin Boydas
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AI for CreatorsCase Study

What I Learned from Analyzing 10 Viral Generative Music Campaigns

I almost gave up on generative music composition until I changed my approach. This isn’t the usual advice you hear—this shift made a real difference for me.

2024-03-295 min read570 words

I almost gave up on generative music composition until I changed my approach. This isn’t the usual advice you hear—this shift made a real difference for me.

What I've Learned From 107 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 your team matters more than your technology.

The Counterintuitive Truth

In generative music, the best practitioners often do less, not more.

The lesson: simplicity beats complexity every time. It sounds simple. It's incredibly hard to execute.

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.

What I Tell Founders

Before deciding anything about generative music, start with three questions:

1

What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.

2

What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.

3

Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.

These questions seem simple but they reveal a lot about where a company actually stands.

This connects to broader themes around AI animation, AI journalism, AI music 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.

FAQ

Frequently Asked Questions

Q:Can these results be replicated?

The specific numbers will vary, but the underlying patterns and principles are transferable. The key is understanding the context behind the results, not just copying the tactics. Every company has unique constraints that shape what works.

Q:What was the biggest challenge in this case?

Almost always, the biggest challenge is people and alignment, not technology or strategy. Getting the right team focused on the right problem is harder than any technical challenge I've encountered.

Q:How long did it take to see results?

Most meaningful business results take 3-6 months to materialize. Anyone promising overnight success is selling something. The companies in my portfolio that grew fastest were the ones that stayed patient and consistent.

Q:What would you do differently looking back?

I'd move faster on the things that were working and cut the things that weren't sooner. Most founders, myself included, hold onto failing strategies too long because of sunk cost. Speed of learning is everything.

Written by

Sahin Boydas

Serial entrepreneur, #1 angel investor, author of Becoming Top 1%

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