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This is an interesting idea, but like most things it's just going to age. checking nownownow.com for people in the UK with one, the first 2 I picked were updated in 2021 the next 2023. Then I had two that were this month and last.

TBH linking to a twitter or equivalent social media might be better. Or make now now now a more automatic system.



I don't think that's necessarily a bad thing, unless the content of the page was something like "eating a sandwich" which, afaict, is not the purpose. The article author wrote:

> So in 2015, I made a /now page on my website, saying what I’d tell a friend I hadn’t seen in a year.

So the 2021 pages are probably a little out of date, but I think the 2023 and more recent ones should be fine. I think /now is less a Twitter clone and more like an 'About Me' with only the most recent interesting thing you want to say.


Yup. The majority of people on the planet already have a "now" page, and that is their social media profile.


> The majority of people on the planet already have a "now" page, and that is their social media profile.

You might be right but the people who have personal websites/blogs with enough passion to add a now page are likely to be in the opposite camp, the minority who dislike social media


> are likely to be in the opposite camp

Why do you think so?


Just an observation from following many blogs


I think it’s a question of timescale.

Twitter, etc.: hours - days

Now page: months - years

About page: decades


I think I looked at about 6 from the UK and 4 of them had huge headshots at the top which pushed all the information below the fold. Think maybe only two of them were actually had "now" kind of information as well.


To be fair, pretty much nothing has changed in my life in the last 3 years either.


>This is an interesting idea, but like most things it's just going to age.

You can use an LLM to extract and summarize data from your social media.


This is like a second law of thermodynamics for communication. You take something that's already pretty low signal and then extract whatever from it and republish some slop you generate from that using a model. Models are then trained on published media and thus the circle continues, with everything trending to sludge over time.




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