Basing rollouts on add-to-cart rate is generally not a great idea, particularly for experiments on product pages. There are a variety of reasons why shoppers add products to carts that may only be loosely based on intent to purchase. In my years of ecommerce A/B testing, I've seen plenty of tests that improve conversion rate and/or revenue per visitor but negatively impact add-to-cart rates.

This is much different than honey bees and other types of wasps who are much less likely to attack just by being near them.

Why wouldn't consumer AI be a natural home for Apple?

Apple is constantly under blast for being slow to AI but if you look at the current state of AI, it feels like something Apple would never release -- the quality just isn't there. I don't necessarily think Apple only dipping their toes into AI is that poor of a decision right now. They still have the ability to blow the roof off the market with agents and device integration whenever the tech is far enough along to be trustworthy to the average consumer.

Compare that to the approach you're using (which is what I'm also doing), and you're able have have AI stay much closer to what you're looking for, be less prone to damaging hallucinations, and also guide it to a foundation that's stable. The downside is that it's a lot more work. You might multiply your productivity by some single digit.

To me, that 2nd approach is much more reasonable than trying to 100x your productivity but actually end up getting less done because you end up stuck in a rabbit hole you don't know you're in and you'll never refine your way out of it.

One of their pitfalls is charging by the row. If you're cost-conscious, you really need to watch what data you're syncing and you need to pare it down quite a bit during the 2-week period they give you when setting up a new connector. If you do all that though, you can get a lot of mileage out of the free plan for some use cases.

This is a huge fail for Gemini. Google, of all companies, should know the incentives to distort information aggregators for monetary gain (just look at how bad search results are these days). It's 100% expected that people will try to game LLMs the same way. It's entirely dependent on the LLMs to counteract this.

You don't need NPM, Github, Vite, React, etc. to do any of that. I'd also say the vast amount of documentation, sites like Codecademy, seemingly infinite amount of Youtube videos, etc. accelerates learning light years beyond what we had with GW-Basic, assuming you even had this reference guide!

Obviously, this would be much different putting a $1,000+ business SaaS subscription on a credit card vs. a $10/month consumer product.

I never knew this! I have heard about companies banning you if you request a CB, which would be really bad for things like Google, Uber, etc.

I usually end up having to dispute a charge only once a year or so. It has surprised me over the past few years how lacking AMEX seems to be in its "investigation". It at least used to take a few days and they'd sometimes ask for documentation. The last one I did got turned around in maybe an hour.

The gap between Dookie and American Idiot seems significantly longer to me than the gap between American Idiot and today, yet it's half as long :/

That was probably 10+ years ago and I suspect data analysis by the leagues is much stronger now. Still an insane line that needs to be walked between the leagues getting revenue from the sportsbooks and gambling not impacting that play.