State of Show HN: 2025 | Hacker News Reader

State of Show HN: 2025

blog.sturdystatistics.com

134 pointskianN34 comments

The advent of coding agents killed Hacker News to some degree for me. Before I could always come here to get a pause from the hype, scandal and bait. Top comments were usually insightful; I really had this feeling to learn while browsing the feed. Today every brainfart about AI makes it to the frontpage. I know this sounds very dismissive, but most pieces really have no substance at all.

The good content is still there buts it drowns in noise and I'm not very good at filtering it out. I even suspect Hacker News is one of the prime advertisement targets of coding agent companies.

I would love to see if this is just my perception or if it can be found in the data.

Personally I don't care about what news articles end up on the front page - it's AI now, but there have been other trends in the past that did the same.

The bigger problem is the effect that it's had on "Show HN" postings, which in the past were things you could depend on were built by the person submitting it. That's why those posts tended to be more strongly moderated, because they often were seen as attacks on the person's art. Now I feel like most of the credibility has left the room on those posts.

Don't get me wrong - I have no problem with "vibe coding". I do plenty of it myself these days, for commercial purposes. But I feel it cheapens and waters down someone presenting work as their own.

A project was one of the easiest ways to evaluate a stranger. It was a great bullshit detector. If they can make something like this then they are probably someone with ability and experience and so the rest of what they have to say is probably worth listening to. But I also agree with the parent. HN seems to be flooded with hustle and rubbish since AI has taken off. It's eternal LLMber.

The phrase "eternal LLMber" saddens and scares me in equal measure.

As good poetry should.

I wonder if the marketing/hustlebros who only value our art as a "get rich quick scheme" (IE: the people pushing "Learn to 'code' (I hate the term 'coding')and half the new faces from india) learnt about Show HN and decided to ruin something good by making a linkedin post about "how great of a marketing avenue" we are and the vibecoded slop pushers listened in full force because they know nothing about our industry and thus don't know how valuable a non-salesy place to talk trade is

I agree... I wrote an essay about this: https://joinkith.com/#the-internet-is-dead

tl;dr of the essay, we need to move back to human-to-human recommendations and trust systems, and people are already doing that a lot of ways by retreating to DMs (iMessage, email, in-person conversations) and personal recommendations rather than relying on Google + the algorithm. What this means for public forums I don't know. I think they're gone and will never come back, probably.

I'm just going to wait it out, as these trends come and go; before AI it was Rust, before Rust it was IoT, before IoT it was big data, crypto was weaved through it, etc.

I'm sure someone's done the numbers on HN trending topics over time aaand yup http://varianceexplained.org/r/hn-trends//.

Ive had 2 posts take off (>300 points) in the past 2 months. One was a project that garnered a bunch of points initially (https://news.ycombinator.com/item?id=46793693).

The other was more interesting. It was a "rise from the dead" post (https://news.ycombinator.com/item?id=46466027), meaning I posted it on Jan 2 (Friday), and then on Jan 5 (Monday) I started to get emails from readers giving me feedback about the post. I had not expected that level of response...

From this experience, I learned nothing about how either the algorithm works or when the best time post is. IMO just being part of the community and showing your work frequently is the best strategy here.

Launch early, launch often - or something like that.

It's hard to tell now, but most likely your second post got "second chanced". That's where they go through things that they think might be popular and put them back on the front page, usually a couple days after they were initially posted.

I found the development of my Triclock[1] interesting. Stayed in Show HN for 3 days, never reached the frontpage, 65 upvotes. So a popular 3 day evergreen. All other of my Show HN were Crash & Burn or Burn & Shine

[1] https://news.ycombinator.com/item?id=46975399

Yeah Show HN has a pretty interesting distribution compared to standard posts due to the long-term visibility on the Show page. The odds of a Show HN post breaking 10 points is significantly higher than an average post, but of the posts that clear 10 points, I recall the likelihood of breaking 100 points to be similar to a regular post.

As a sidenote: That clock is so cool: I was just mesmerized for multiple minutes!

Cool. I think it would be nice to normalize against users (or active users).

2016-era HN had its share of negativism, but it also had a lot less people - the light green from those charts is misleading.

I totally agree that the metric is imperfect for a long term analysis. I was initially leaning toward a quantile based approach to really focus in on topic trends over time, but when I was initially exploring the data, the relative challenge of having a Show HN become popular in 2025 compared to previous years caught my curiosity, and for this decade I felt a static cutoff provided a simple and easy to understand threshold.

I do think as a metric for total reach, a static cutoff actually works reasonably well. I think some form of square root normalization over total users is probably the best balance.

Pre-2020 had far more informative posts and discussions. While we still have decent conversations post-covid, the quality has slid downhill somewhat.

I think that's indicative of the Internet as a whole for a vast array of reasons, and even so, HN still maintains a far higher bar for discussion.

Every few years I get to thinking I want to do some research on this and then maybe make a combo karma age filter, and then I go read some posts from 2017 and I think “it was better, but I don’t know if it was that much better.”

Excepting the last year - things see dark for a lot of users here in the last year.

Fair point. Rose-tinted glasses and all.

Very nice analysis

Do you have any insights into the Clawd spam ravaging /new and /show?

I'm in there, being part of a (down) "voting ring" (not coordinated)

Thank you! I currently don’t have much insight to this current trend. At the time of this analysis I hadn’t even heard of Clawd but that would definitely be worth my revisiting.

I was planning on doing this yearly but the Clawd excitement is definitely worth diving into.

It could be interesting to simply plot the /show frequence vs account age at the time. I suspect an change in patterns has occurred recently.

the signal-to-noise ratio has definitely gotten worse. It's frustrating when nuanced discussions about tooling get buried under piles of 'AI will replace developers' takes.

My project[1] got some love on HN though never made it to frontage about a year ago. It also got unexpectedly popular on twitter. Its simple project and not particularly great ui either but somehow it clicked. My other projects which i thought were more useful never got any traction. It seems novel idea was what caught people's attention. one year later though it hardly gets any traffic. Also with improved LLM's it has become trivial to replicate them.

[1]https://news.ycombinator.com/item?id=42207002

Great. Do you have any details on how you produced this? The "reproducible code" isn't really reproducible. The "hierarchical topic model" that you mentioned - which model was used?

The code provided is to reproduce the analytical results from the annotated data; my impression is that you're more interested in the details of the annotation process than running into an issue with that code?

My company's core technology extends topic models to enable arbitrary hierarchical graphs, with additional branches beyond the topic and word branch. We expose those annotations in a SQL interface. It's an alternative/complementary approach to embeddings/LLMs for working with text data. In this case, the hierarchy broke submissions down into paragraphs added a layer to pool them into submissions, and added one more layer to pool them by year (on the topic branch).

Our word branch is a bit more complicated, but we have some extended documentation on our website if you are interested in digging a bit deeper. Always happy to chat more about the technical details of our topic models if you have any questions!

Overview of Our Technology: https://blog.sturdystatistics.com/posts/technology/

Technical Docs: https://docs.sturdystatistics.com

ha, great way to plug your tech. upvoting

So the analysis from the last image is not available - not even for money, right?

We are going to publish that publicly next time we have a free day, though its publication will likely render the analysis redundant :)

You already posted the answer. Just a bit of review of that picture and the answer is right there. ;)

Haha that’s true, but the timezone is left as an exercise for the reader for now

Another recent article on this topic https://www.arthurcnops.blog/death-of-show-hn/

I am not a blind AI fanboy but I am more bullish than some people here, for two reasons:

1. We might be drowning under the "top of the iceberg" at the moment (quickly generated AI slop) but there's a silent crowd of builders doing long-term work (still with the help of AI) that will only surface after months of work. I expect more of the bottom of the iceberg to show up over time.

2. A lot of the most interesting work in science was done out of sheer curiosity, not given a specific problem to solve. The current generation of AI is good -- and getting better -- at the latter, but genuinely incapable of doing the former in a remotely meaningful way.

In other words, I'm long on truly human-driven innovation.

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