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Posted by david927 11/9/2025

Ask HN: What Are You Working On? (Nov 2025)

What are you working on? Any new ideas that you're thinking about?
464 points | 1369 commentspage 81
gianlucas90 11/10/2025|
a website blocker that uses AI to help you against procrasticantion, you can try it for free: https://tasksentry.app
wibbily 11/9/2025||
I just finished a little webtoy. It's like a comic strip time machine - you can see a virtual newspaper comics page for any date in the last seventy years.

https://lmao.center/funnies

V happy with how the CSS came out, except I spent a lot of time on an "ink bleed" newsprint effect that (oops) only looks good on HiDPI monitors... lessons learned I suppose

analog8374 11/10/2025||
Hypertufa plant enclosures
fabmilo 11/10/2025||
VAE for real time video generation, WAN 2.1 / Matrix Game 2.0
earsay 11/10/2025||
I am building a mobile podcasting app that uses ML to auto-skip ads
hsolive 11/14/2025||
My first coding project: built a PDF tool to save paper on expense reports

TL;DR: Expense reports were killing me (and trees). Built my first coding project – a PDF merger that fits multiple receipts per page. Planned to charge "one bike tire

worth" to recoup costs, but decided to make it free after learning so much from the community. [https://ahay.app/](https://ahay.app/)

danielfalbo 11/10/2025||
I'm implementing a btree for educational purposes =) https://github.com/danielfalbo/btree/pull/1
sourcecodeplz 11/11/2025||
A Chrome extension to replace the default new tab page.
balksi 11/11/2025||
I am working on yet another news aggregator: newsmuncher.com

So far i've got the scraping and embeddings / similarity clustering down (to build timelines of news stories), lots of data cleaning and UI refinement required. I find it hard to make choices, maybe I need a cofounder who can pair up with me. Looking to either monetize news data or build a news analysis / intelligence platform.

bthallplz 11/11/2025|
May I ask what techniques either you're using or would recommend for similarity clustering? I looked into topic modeling, but it seemed a long way off from reliably bundling together stories like on Techmeme.

(I'm working on basic blog and video aggregators like Planet Python.)

balksi 11/11/2025||
For similarity it is important to consider the dimensionality of your embeddings. The larger the text you wish to compare the bigger each embedding should be (to my limited understanding).

So a paragraph might be good as a 384-dim vector but if you have 1,000 words then you might want a 768-dim embedding (if not higher). Embedding models have slightly better/worse accuracy based on the training data they're fed, but higher dimensionality definitely gives better results - to a great extent. If you have an extensively long piece of text, it's easier to chunk it into pieces and create separate embeddings. You do have to manually stitch them back together and do some cleanup when displaying results but it works.

Once you have embeddings for all your data the rest is just cosine similarity, play around with the min_similarity. You will need to build good indexes on postgres but it is basically all you need.

alexander2002 11/15/2025|
building demos at muxo.ai. Some rough demo can be found at founderos.muxo.ai
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