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Well, the model can suggest patterns, but everyone is responsible for what they post.

That is true and I agree. I guess in this case the "success" I meant was hitting and staying on the front page so that more people can see your project.

That's my second try, my first post actually got shadowbanned, so I had to change the domain (it was originally GitHub) and the title wording for this one.

There are still a lot of random factors on HN, so nothing can predict things perfectly, but I like that the model gives you feedback based on real data behind it.


Haven't used anything - I'm as impressed as you are.

That what surprised me too, also Saturday turns out working just fine. My explanation would be that on weekends there is less competition for the attention. Even with less people on the platform, it's still easier to get noticed.

Ha-ha, all good - I can see your comment.

It was my own fault to be fair, should have been more up on the guidelines.

I used a dataset from HuggingАace to analyse all Show HN posts for the past 3 years. Here is what influences if the post gets on the front page.

- Niche technical topics have the highest viral rates (Rust, Postgress, Lua, etc) - Open source tools are the top performing category with 13.9% viral rate - "I built" outperforms "We built" - Sunday noon UTC has the highest chances to hit the front page - Titles with a parenthetical work much better that those without.

More insights in the blog article.


I guess because tokens is the only metric that ""reflects" how high your AI adoption is. So especially in tech industry, if a company pushes for AI adoption, the token usage is the only proxy metric you have.

Agree that it's absurd though.


We at Metabase asked 338 teams in our community about how they build and use their data stacks, from tool choices to AI adoption, and built a community resource for data stack decisions in 2025.

Some of our findings: - Postgres wins it all: #1 transactional DB and #1 analytics storage - 50% of teams skip warehouses/lakes - Data teams stay small: most are just 1-3 people, even at big companies - AI trust is shaky: average confidence only 5.5/10

There’s much more to see. Check it out and let us know what you think.


I’m surprised that Clickhouse is not more prominent in OLAP tech. Such a versatile DB.


"Just use postgres" :)


Feels like a useful tool for anyone learning analytics or just needing sample data to test with.


Are you affiliated with metabase? https://news.ycombinator.com/item?id=44107584


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