When do companies ever try to understand their customers? They know what works for who, and continue to rehash that for that specific age of the generation.
The article even states this. "Monster Green shoppers are likely younger (Gen-Z/Millennial/Gen-X) male, lower income & Caucasian (skews Hispanic)."
When you've moved from that generational age, your no longer their audience and they don't care if you buy or not; but it's not like they cared in the first place.
I worked through this for a tax company. They had a huge pile of artifacts from tax questions worked up for clients. What we did is we "reverse engineered" the process of the questions that would lead to that tax memo and the research steps to find the sources and conclusions. It worked well and we were able to replicate the process which the SME's created these memos.
For a given tax question, could you come up with the same memo quoting the same sources and same conclusion?
You would think this would be obvious to everyone. Clearly Apple is prepping for a digital overlay on the real world. Also less UI interaction, more voice/AI interaction.
Just run the qtap agent on whatever Linux machine has apps running on it and it will see everything through the kernel vs eBPF.
You can customize config and/or integrate with existing observability pipelines, but initially you just need to turn it on for it to work. No app instrumentation required.
It does mention that, it calls that out specifically.
As you grow, it’s tempting to fix every issue using the ‘cowboy’ method. It’s fast. It’s efficient. It leads to good results. But the number of things that need a cowboy fix grow exponentially, and cowboy fixes only ever fix that one thing, while system fixes fix future issues too. As you adapt from cowboy to drone, it’s easy to skew too much to one side or the other. No matter how good your systems are, sometimes stuff just needs to get done pronto. But sometimes you need to take a step back and trust that the system you built will do its job, and trying to jump in to speed things up will only make everything worse.
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You introduce a point I have not seen discussed before which is that these type of content distribution platforms go through a process to find their global minima.
Twitter at the beginning you didn't know what it was going to be or what worked. Same with facebook and instagram. As time goes on these sites small features bring out their emergent properties of what 'works' there.
And once it has been 'figured out', it is not as fun. You know what you can expect there and people go there but it is no longer a dynamic feeling. Like watching the NBA today, it has been 'figured out'.
I think that may be what is the factor in the longevity of these platforms, once it is 'figured out', if what it is, appeals to enough of a large base.
Tik tok may have gone further because it never really was 'figured out' in that larger way. The algorithm really could give you wildly different content and different 'trends' would show up so it never reached that static boring point.
For these 'on the decline' sites you can almost predict exactly what you will see there and exactly what the discussions are. It is not longer an exciting TV show.
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At the least OpenAI is worth what the market is willing to pay for it.