I agree with you on all your points but I came to the conclusion that I would _not_ start a new app in Rails for those reasons.
I've spent my whole career on Rails and I think it's amazing when starting small but mature applications are a nightmare to refactor. Every monolith Rails app feels like it hits tech bankruptcy after ~5 years.
"tech bankruptcy"! this is a VERY strong sentiment. First of all, I've never seen a rails-based company which has it problems from tech department, and not from product market fit or whatever, and that's in a 18 year carreer. I'm singlehandedly refactoring right now a 10-yearish rails app which had a period of neglect and bad contractors who broke every single test, and it is still very much manageable.
> I've never seen a rails-based company which has it problems from tech department
I've been using Rails since 1.0, owe much of my career to it, and still think it's an incredible framework that I love using.
But I have seen plenty of startups—mostly filled with junior developers—who don't have the maturity and experience to avoid some really bad ideas absolutely wall themselves into a corner. Thankfully the worst of this was in the Ruby 1.8 and Rails 2.3 era, but it still happens today.
A lot of the issue is the tendency that Ruby libraries have toward exposing internal details that end up getting relied upon (Hyrum's law in action).
With a sufficient number of users of an API,
it does not matter what you promise in the contract:
all observable behaviors of your system
will be depended on by somebody.
(There's something about the way people manage to phrase these that I really enjoy. Something about the succinct and clear expression of an idea that's otherwise really fuzzy in my head.)
It's interesting to think about the implementation being necessarily coupled with the interface. In some context that's obvious, but the idea that another implementation can't be freely swapped in -- because nuanced behavior (sometimes called a bug) in the original implementation is still expected -- is one I hadn't, as such, thought much about before.
I agree it's a strong sentiment. But development seems to slow to a crawl at around that time from what I've seen. And then it seems like keeping the app going needs extremely strong developers around it, which not every company can afford. It's just bad value; you have to pay a lot to continue to develop at a normal pace.
I think the fact that we are trying to shove typing onto Ruby with Sorbet and RBS are a sign that maybe it's not the best programming language once you reach critical mass.
It's possible the grass is greener and this is what happens to every tech department... but I'm not totally convinced. I always hit a point with Rails apps where I can see the refactorings I'd like to make but I know it's not worth the pain of the inevitable `NoMethodError` at run-time in production. And that's _with_ a giant test suite.
I think the context here is super important: I run an agency, and a lot of our clients are small startups or solopreneurs. The most important factors in determining their tech stack are (in some order):
* Time from idea to deployed solution
* Ease of pivot
* Ease of finding other devs who can take over
If I were a staff engineer at a large company with an existing tech stack tasked with spinning up some new internal microservice, I'm probably not choosing Rails.
But if I'm truly greenfield on a strict budget, still searching for product market fit? If that application ever truly outgrows rails (and it can become wildly successful without doing so --- look at stripe, instacart, github, shopify) then we've already won by surviving long enough for rails to be the problem.
Over a decade ago when Rails was the shiny new thing I wrote an online ordering system that batched received orders then sent out orders to suppliers for whatever the customers ordered. It was easy enough to get the app setup and it didn't often need any new features but I remember really struggling to get it up to date and working with each new rails version. My memory is clouded by both time and my inexperience at the time but even though the app was "done" it never actually felt finished because I felt the need to continually update to the new version of rails just in case I did want to take advantage of of the new features in newer versions rails.
Anyway over 10 years later now and I find myself writing an API and my initial thinking was to return to rails but then I remembered the bad experience (which was probably my own fault I acknowledge).
Now I find myself writing this API in Rust because the ethos that an app can actually be done is attractive to me. It's taking me longer to write but hopefully I've made a good decision!
I guess my post wasn't a critique of the blog post, it was a somewhat related story. I do actually agree with the blog post about not rewriting something that works. In my case it's a totally new project but it was my previous experience with Rails that made me not want to try it again for this particular project.
The API I'm working on is pretty simple and I want to finish it and forget about it so in my circumstances it seems that rust is a better choice.
Rails, ironically, doesn’t keep you in the rails. I’ve seen a couple of the things you’re talking about, and it’s really just mediocre devs in bad (but common) situations.
If someone gives you a paint-by my-numbers page, and you just scrawl all over it… is that the “fault” of the page?
Could it be that Kagi benefits from being niche, though? Google search gets gamed because it’s the most popular and therefore gaming it gives the best return. I wonder if Kagi would have the same issues if it was the top dog.
I think they absolutely benefit from being niche, but there are a few other things they have going for them that won't go away if they become popular:
* They're not ad funded. Sergey Brin and Larry Page called this out in 1998 and it is just as true as ever: you need the economics to align. Kagi wins if people keep paying for it. Google wins if you click on Search ads or if you visit a page filled with their non-Search ads.
* Partially because of the economic alignment, Kagi has robust features for customizing your search results. The classic example is that you can block Pinterest, but it also allows gentler up- and down-weights. I have Wikipedia get a boost whenever its results are relevant, which is by itself a huge improvement over Google lately. Meanwhile, I don't see Fandom wikis unless there's absolutely nothing else.
I hope to see more innovation from Kagi in the customization side of things, because I think that's what's going to make the biggest difference in preventing SEO gaming. If users can react instantly to block your site because it's filled with garbage, then it won't matter as much if you find a brief exploit that gets you into the first page of the natural search results. On Google Fandom is impossible to avoid. On Kagi it just takes one click.
Mirroring what you're saying: I've worked with a company who has a "Salesforce Product Manager". A whole person dedicated to managing their Salesforce integration. I haven't used it myself, but seeing that role exists makes Salesforce sound both complicated and expensive.
Eh, maybe. I wouldn't completely judge a workplace by these people. I've kind of come around to enjoy working with "weirdos" like this because their personal quirks have no actual affect on how they work. It can make them more interesting if anything.
I think the actual awful part of people like that are when they get in a position of power and preach their weirdness as The One True Way(tm). Which, unfortunately, a lot of them do. I think this stems from them having success in life without realizing it's selection bias. The result is that their own decisions are biased towards their quirks and they become pretty insufferable about it.
But, to your point and to completely contradict mine, I would bet those "One True Way" people probably are the norm at Palantir, judging by the onboarding book choices.
Are the book choices bad? I looked them up after first hearing about them through this article, and at least the Interviewing Users one sounded useful, and Principles seems to have a ton of good reviews. For the uninformed like me, could you give some color to those books?
I don't think ESPN does anything that takes significant resources. That's all handled by SportsRadar or ... there's another big provider but their name alludes me. They basically firehose you all the game information as structured data and you can use it programmatically however you'd like.
Definitely. I have no experience in live game statistics, but from my sports content experience I bet there's data scientists and applications behind the scenes that specifically pull this data to be read on-air.
Back when I worked on it, before AI, you have all the information from a game in an API and you just fill in the template with it.
Now, I imagine they take that raw API call and just use a prompt like, "write a summary article for a game using this data" and it spits it out. And I assume the prompt is more thought out than that (or not? It is ESPN after all).
I don't ever remember "retiring_players" being part of an API response, though, ;P
edit: Oh and yes, the play by play recap is documented EXTREMELY well. You would be surprised. The more popular sports like Gridiron Football and Basketball would literally have player locations by the second. This data all comes from feeds like SportsRadar.
They probably wouldn't pipe the fine tuned stuff like that in to a prompt, but you still have a decent summary like how many 3-pointers someone had and where they shot them from.
It's pretty funny to me that this is used as a hit-piece against AI generated content. Here's an open-secret for everyone: web-based sports content companies have been automatically generating content articles for at least a decade; way before LLMs became popular.
It is and was mostly done for search ranking. The more seemingly applicable content, the better your SEO.
This situation has probably happened several times before AI but has gone unnoticed or noticed to little fanfare. It's more indicative of ESPN not having its finger to the pulse and ensuring that one of the copywriters manually updated this particular article. It's not too surprising to me. They've always been known to favour quantity over quality.
source: I worked as a developer on the tech side of a company with this kind of content
the depression shouldn't arise from the generation, but from the consumption, for it is the latter that ultimately drives the former; that, in turn, can generate a reflection on what I myself consume.
I don't think people do actually consume it. In my experience this content was purely for SEO or maybe just a headline that people read quickly to keep up-to-date. The actual article content is rarely seen by a human.
Yes, but not for these articles. Here's a example situation where having good SEO with filler content that makes sense: Lebron James retires.
If you are faster and have the best SEO at that point in time then that means everyone trying to read about Lebron James retiring is going to search it in Google and is going to read your article first, and you're getting the ad revenue. It's a 90/10 situation. The "top" website in the rankings is going to get 90% of the clicks.
You can only be the "top" if your SEO to that point is also the "best". And to have that you need to have all this generated content.
But sports reporting has pretty much always been this way.
Unless anything extraordinary happens, every post game interview features the same questions with the same answers and every article about the game looks the same with only the names of the participating players and their stats changing.
Well, previously you needed an intern working maybe an hour (of they actually wrote good content, obviously more), that intern needs food, air conditioning / heating, so I'm not sure which consumes less energy. Now you have it in a minute and for a predictable low fee.
There are basically two types of content when it comes to these sports recap articles. I'm also excluding opinions/editorials because those are completely different.
1. low profile, not-so-popular content. eg. A Canadian Football League preseason game between the Toronto Argonauts and BC Lions
This was still generated using a template. No human intervention except maybe double-checking it before publishing it. This was before AI, too.
Often it was there for SEO or just updating people via a headline
2. High profile content, eg. Jeremy Lin puts up 38 pts in a game
This is often one of:
- pre-written, especially if we expected to happen that day
- withheld from publishing if there was auto-generated content but something crazy happened that game and then quickly re-written and released. Usually this would still at least be pre-written before the game ended and details that needed to wait for the game to end were filled in seconds before/after the game ended.
There's just as much labour put into it now as before. AI is now generating the low profile template instead of the madlibs we did before. The value add is that it's probably a better read, so you actually get user engagement, and better SEO than before.
And this same issue highlighted in the OP article would also happen without AI.
> This was still generated using a template. No human intervention except maybe double-checking it before publishing it. This was before AI, too.
Odd question but is that why the banal reporting on so many websites is such utter shit? Like in all dimensions, it gets facts wrong, it's usually rife with spelling and grammatical errors... when I spend too much time online I start feeling like the sole person on the planet who gives a shit about writing correctly.
Low quality news sites usually have a target that they need to reach in the form of X articles per day. When you're in that position, at best you can spend a couple of hours on any individual story before you have to turn your attention to the next one.
Good news take time and journalists often don't have that luxury.
Probably money in, money out. I think the content you're looking at _is_ underpaid interns. As another comment mention, sports data is actually very structured these days and its easy to automatically generate articles with it. Actual news, probably not so much.
The efficiency gains are undeniable, and AI can scale in ways that were unimaginable before. Less grunt work, more room for innovation—hopefully, we can reinvest that time and energy wisely.
> ensuring that one of the copywriters manually updated this particular article.
Clearly it was never "there" yet though previously, and obviously still isn't when this article is what's generated. You can tell that a lot of sports articles are essentially "fill in the blank", which is why they get the AP stories up right away, and then have their actual beat reporters come out with something later that night, or early next morning.
Beat reporters will also write during the game, and if I’m remembering correctly, will work on differing versions of the ultimate winner at the same time.
Absolutely correct! In the old days it was mostly video replay and witty banter describing what you were watching, which was fun to watch. Now it's become something I couldn't care less about, which is less video and someone telling me what I should think about what I just watched.
I'm OK with didactic commentators if the person talking to me is an expert and giving me new information.
Broadcast media outlets fail at that. I don't know much about sports but even I can tell that people on TV are speaking in vague generalities so they can never be proven wrong. I get told that the team that lost "didn't want to win" as if people getting paid millions a year to win at sports aren't motivated.
When people are afraid of being proven wrong above all else, they avoid making any substantive claims. If someone isn't afraid of that, they'll make more interesting predictions I can't get elsewhere, and eventually it'll be a more enjoyable product because I can make fun of that person for being wrong.
I can't help but wonder if gambling isn't part of the reason for all the opinions these commentators are having. You're right, expert info is important.
If I was into online sports betting, I would want all the info I could get. Since I'm not, what I want is video replay of what I missed, that's where ESPN lost me.
What web have you been browsing in the past 5+ years? It's not only sports "content". Any kind of content is drowned into low quality SEO pages. Auto generated or not, it's as useless. LLMs just generate it cheaper.
What a weird and rude way to call this out. The parent wasn’t talking about non-sports content and never suggested that sports writing was the only type of content plagued by SEO spam.
to me it doesn't appear particularly against or in favour of. Seemingly, LLMs don't avoid completely some of the mistakes that were already being made. Just as with any technology, the questions should be: by how much the two errors differ? Does the cost justify this margin?
Maybe hit-piece was a strong word; but I do think it's saying this happened _because_ of AI when to me it's been an issue for a long time. ESPN was always pretty egregious when it came to penny-pinching on content and ignoring less popular sports. Ask ice hockey fans how they feel about ESPN.
Not by people in the know, no. But I'd say 80% of "normal" people reading sports websites probably had no idea until now, and the only difference is that (gen)AI is suddenly a "feature" to be boasted about to customers to make shareholders happy. And suddenly all of these normal people are starting to have opinions on it.
Much like when food ingredients are slowly made worse over time, consumers can't necessarily put their finger on how and why somethinng is worse, but they tend to notice that it's worse.
I think people have noticed if not explicitly. They end up going toward platforms that have real humans on them (social media, message boards, substack) and not really understanding it's because they read a bunch of algorithmically generated noise on "traditional" published websites and moved on.
I don't think people did notice. Our view counts for sports articles were always very low, except the very high profile articles. And those ones would always be done by a copywriter and properly edited.
You're missing the entire point. LLMs are super overhyped and this is the 9000th example of how garbage LLM generated "content" is. It doesn't matter that garbage was being generated before. If LLMs were only being sold as "it might be better than the spam generator you're using today" we wouldn't have the current bubble where people are losing their jobs because C-suite clowns believe the hype.
As a Canadian, I agree with the premise that I'd rather see Japan gain power over China due to how they wield that power; but man, you have quite a pessimistic view when it comes to describing US allies.
Also, if Japan truly was a US puppet, would they be "allowed" to have a auto industry at all?
I've spent my whole career on Rails and I think it's amazing when starting small but mature applications are a nightmare to refactor. Every monolith Rails app feels like it hits tech bankruptcy after ~5 years.