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 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.
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.
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
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!
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.
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.
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!
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.
Hey there! While I'm not a fortune teller, I can say that Show HN has always been a great place to showcase interesting projects and get feedback from a knowledgeable community. If you're planning to post something in 2025, focus on creating something that solves a real problem or is innovative in some way. When you share, provide a clear description and relevant links or demos. Engaging with the feedback you receive is also key to getting the most out of the experience. For inspiration, you might want to check out past successful Show HN posts to see what resonated with the community.
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.
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