That's fair, we can disagree. I don't think I'm personally anthropomorphising llms (I think my mental model of how they work is rough but fairly accurate), but at a population level it might be something to be concerned about (see all the ai-psychosis talk)
What I was getting at with the "we" in the post is more how we talk and think about work like this. I think it is different in kind to previous projects I've done where a relied on google, stack overflow and elbow grease. Programming has always been "standing on the shoulders of giants" kind of work, but doing it with agents feels different from that. Maybe it was a poor stylistic choice, but I think we need a way to talk about it in an honest way.
This was a conscious choice, addressed in a footnote in the blog post:
> This is my first time writing up a project that I worked on using an AI agent. I kept writing “we” because the project felt like a collaboration.[...] On reading it back, saying we feels like an accountability dodge, because of course I’m fully and solely responsible for any errors in this write-up or code. But just using I/me also feels dishonest, because so much of the implementation here isn’t fully mine so I feel like I’m taking too much credit for my collaboration with the machines. I figure this is a new kind of pronouns debate we’ll be having for the foreseeable future.
Author here, this is good to know.! I tried to spotcheck the regions and countries, but wasn't familiar with all of them so didn't want to make assumptions (and didn't make time to research them thoroughly). Not sure if/how I could try to correct that.
> This is the kind of "lore" that's impossible to catch from raw data.
Agreed this project definitely banged up against those sorts of walls a few times. Still think it's worth trying, hopefully the information offered one can find outweighs any distortions it introduces. Maybe something that should have been explicitly acknowledged in the piece.
> I like the Essential Mix visualisation even more! It's such a shame most of the other ones appear dead due to API changes.
Thanks, happy to hear that. I keep meaning to go back to the essential mix one, get new data and apply some of the stuff I've learned since!
If you click a club its region and country should be in its detail panel underneath their logo. The region and country filters should show you just the clubs in the given region/country.
Demographic analysis would have been interesting I agree, but I didn't know of a good data source for that and it's hard to parse from line up data (especially in places one isn't familiar with)
What I was getting at with the "we" in the post is more how we talk and think about work like this. I think it is different in kind to previous projects I've done where a relied on google, stack overflow and elbow grease. Programming has always been "standing on the shoulders of giants" kind of work, but doing it with agents feels different from that. Maybe it was a poor stylistic choice, but I think we need a way to talk about it in an honest way.