Not trying to rain on this parade. But it would be nice to know how much of this a person sat down and made. The captions all have the "X, not Y" tic, every component cites source by line number, and the site went from a post every few months to six in a week in four languages. Which all point to heavy LLM usage. It's not a crime. I'd probably use the robot to help build the thing too. It's just feels a bit icky on a Show HN.
Most of the frontend was built using LLMs, just like the frontend for almost all my projects over the past year.
LLMs handle this task much better and faster than I do.
I read the library's code and articles about its architecture, then visualized the concepts using GPT and local models.
I was pleased with the result and decided to publish it.
Honestly, I see no point in creating such visualizations manually these days - a model can do it much faster and better.
As for the articles, I write them entirely myself.
There are more of them now because I built a bot that takes posts from my Telegram channel, translates them into three languages, and publishes them to the site.
"The Grid. A digital frontier. I tried to picture clusters of information as they moved through the computer. What did they look like? Ships? Motorcycles? Were the circuits like freeways? I kept dreaming of a world I thought I'd never see."
There's a console and you can track your command! Very cool. Not sure if 3D is needed but very cool nonetheless, It might be that some things are missing (I don't know redis internals though) like some encoding step when getting data back to client, managing client connections and their state (multi, watch) etc.
Which is modeled in Unity which you can walk around in VR...for kicks maybe though could unlock something in the mind...spatial computing is an interesting field.
that could be "new" technique to use agents in software development: instead of tiresome prompting/reviewing large swathes of text - pointing to specific area in a map, just like in a strategic videogame
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[ 4.7 ms ] story [ 26.0 ms ] threadEach component links to the source code, and you can open the console to enter your own commands and watch the execution flow
LLMs handle this task much better and faster than I do. I read the library's code and articles about its architecture, then visualized the concepts using GPT and local models.
I was pleased with the result and decided to publish it. Honestly, I see no point in creating such visualizations manually these days - a model can do it much faster and better.
As for the articles, I write them entirely myself. There are more of them now because I built a bot that takes posts from my Telegram channel, translates them into three languages, and publishes them to the site.
https://news.ycombinator.com/item?id=49063754
https://laurentiugabriel.github.io/blog/articles/how-i-use-l...