u/siloteam

I very much wonder what Tim would have thought about AI and the way music is being made today.
When Tim started producing, one of the coolest things was that technology allowed him to basically draw out all these different instruments and sounds. And back then, not every musician was as hyped about that as I was. Some dismissed producers like him with the whole “he can’t even play an instrument” argument.

Which, by the way, turned out to be completely untrue in Tim’s case. He was a great pianist and guitarist. But it makes me wonder about the shift we’re going through now.

AI is starting to change how music is made. The same is happening with video, and even songwriting. In some ways, it feels like another massive change in what it means to “make” something. I genuinely wonder what Tim’s take would have been.

I’m having an ongoing debate with another startup founder, and I’d love to hear from experienced engineers because I suspect one of us is fundamentally misunderstanding software engineering.

He’s building a web app for hospitality bookings. I’m building a family organizer app for iOS and Android.
We’re both growing quickly, shipping constantly, and dealing with real users. The big difference is how we think about AI coding.

His view is that AI is getting good enough that he wants to eventually remove almost his entire engineering team. His thinking is that AI can build the product, and then an experienced engineer can step in for the final stretch to review, polish, and make sure everything works.

My view is almost the opposite.

I see AI as an incredible force multiplier for engineers, not a replacement for them. I absolutely think it changes hiring. Junior engineers probably aren’t as valuable as they were a few years ago, and there’s definitely a real cost to carrying an in-house engineering team.

But I struggle to believe we’re at the point where you can replace engineers altogether.

My biggest fears is ending up with a codebase that grows into an unmaintainable mess as the business scales. It’s easy to generate features. It’s much harder to maintain architecture, ensure consistency, manage technical debt, debug complex production issues, and keep a product healthy over the long term.

My friend thinks those problems are becoming much smaller because AI is getting better so quickly. I think we’re underestimating how much engineering happens before and during building a feature, not just after it’s finished.

I could be wrong. That’s why I’m posting.