I (think I) agree with the author, but I want to point out that his core grievance has little to do with AI software factories.

> The product changes are primarily additive... I think the reasons for this is that it's lot easier to add new capabilities, than rethink existing capabilities.

This is perhaps the biggest difficulty in Product, and the core of the Innovator's Dilemma. Changes or removals, fundamentally, fuck with how somebody uses your product. It is very, very rare to ship a feature - something that inspired somebody in Product, got all the internal stakeholders to sign off, including getting leadership to fund it - and have nobody use it, so that it isn't controversial to remove it; even then, removing it competes with resources for adding something else, so it's still controversial to remove it. When somebody uses something that you fucked with, you risk them churning, that simple.

Coming up with good features to add is not hard. Everybody and their grandma has ideas. A simple spreadsheet can count which ones are most popular and are proposed most often. This should not, in and of itself, dictate what you build next, and bad Product leadership looks like following mass diktat.

Good Product leadership is not afraid of the consequences of fucking with the user. Good Product leadership has both the courage to reformulate the offering and gets the reformation right, because they intuitively understand the user, the domain, and where they sit in it, better than anyone else. They ship stuff that fucks with you because they understand the difference between the bad kind of being fucked with, and the good kind. And if you churn, then you churn. So be it. You can't actually make everyone happy all the time, so focus on making happy the people who get it, and accept losing the rest. That's also easier to say when you have $100k in ARR with $1k ACV, compared to $5m in ARR with $2.5m ACV.

Good Product leadership is rare because good leadership is rare. AI has nothing to do with it.

Good Product leadership is rare because Product rarely uses their own product.

I can count on one hand the number of PMs in my career who understood the platforms they worked on outside of their extremely narrow domain - and even then that narrow specificity was often a distorted lens that came from the customer interviews they did that they remembered or found evocative. And this just gets worse the further up the chain you go.

Engineering knows that the best way to improve a product is to dogfood it. Nothing beats regular lived experience long enough for the human brain to start its pattern recognition. But nobody wants to eat their own dogfood, they want the kibble from another brand that has all the shiny marketing attached.

If I had my way, I'd stick PMs into shadowing sessions with Support on the regular for sentiment analysis. No relying on Support management to relay upwards trends - there's far too few Support managers worth their salt.