91–100 of 132 posts
How many errors does that contain - anyone knows stats for that? I see "AI summaries" on github all the time. It's like a wall of text and seems to be designed to be super-verbose but without seemingly being very informative.
This is an interesting threads. There are many instances of "this is bad, doesn't work, don't like it", and many instances of "it works reasonably well here, look: ". Seems like a consistent pattern.
HN is super susceptible to propaganda in the AI age unfortunately; I think at this point a lot of the comments and posts on here are from bots as well
I tried a few different repositories (both my own and various other people’s projects). They all yield the same: No repositories found No repositories matching "https://git.sr.ht/~whynothugo/ImapGoose" were found. Probably broken/down right now?
deepwiki doesn't spider. Repos are indexed upon request. The request dialog accepts a non-github URL.
Earlier quoted context omitted.
> people can look at the same thing and reach diametrically opposed conclusions. It's very peculiar and I've never experienced anything like it in my career until recently React vs other frameworks (or no framework). Object oriented vs functional. There's loads of examples of this that predate AI.
I dont think it's quite the same. The cases you mention are more like two alternative but roughly functionally equivalent things. People still argue and use both, but the argument is different. Even if people don't explicitly acknowledge it, at some level they understand it's a difference in taste. This feels to me more like the horses vs cars thing, computers vs... something (no computers?), crypto vs "dollar-pegged…
React vs no framework is at least in the same ballpark as AI vs no AI. Some people are determined to prove to the world that React/AI/functional programming solves everything. Some people are determined to prove the opposite. Most people just quietly use them without feeling like they need to prove anything.
1. On (https://github.com/voodooEntity/gits) -> https://deepwiki.com/voodooEntity/gits
This is a longterm golang project i work on and it has a very very detailed documentation already.
While going through the AI docs of deepwiki, i could see how it profitted from my existing documentation, most stuff is just different words same content. What i liked about it was the visualisations (even if some of them are well "special") it shows some insides in workflows that i have in my mind but might give a benefit to others not beein the author
While trying out the search/chat i have to admit it gave better answers than i expected.
Due to having a very fond knowledge of how to do stuff efficiently with the lib, i tested the chat on telling me whats the most efficient way to achieve XYZ. While it listed me all possibilities (all of them correct) it also correctly pointed out whats the most "efficient" way.
Also i gave it some question that, i know from experience when others first tried the lib, could be confusing. But it was resolved correctly.
Allover a pleasant result
2. On (github.com/electronicarts/CnC_Renegade/) -> https://deepwiki.com/electronicarts/CnC_Renegade/
For those who dont know , CnC Renegade is a very old game (~2000) which was coded by the original Westwood. Its mainly in C++ (some c) and a through and through plain code. There is no real documentation in the repo other than some base info for dependencies etc.
First of all i saw that the resulting documentation well.... lacked documentation i guess? It just in multiple pages explaind whats in the main Readme (which is not really alot). So from the "docs generating" perspective, no gain here.
Than i tried to chat with it about it - and it seemed like it has a basic understanding of the code. For me its harder to validate the results (tbh i only read over the code once when it was released - curiosity) but it seemed like it was no total loss.
Conclusion: To me it seems like, to get a very good basic documentation out of it, it already must have a good basic documentation. Apart from the graphics it added, i didn't really see a gain compared to the already existing documentation.
Based on the chat results i'd say, those might be decent and helpfull if you dig into a new codebase especially a more complex one and you are searching for a specific thing in 1000s of loc in multiple files.
Would i use it in the future? Ill maybe try, but only the chat feature - for the generated docs as elaborated i don't see any use.
but then as i kept going along it just got tiring, it kept calling everything sophisticated even when it wasn't
it's the same as all the other AI slop, it's really impressive the first time you see it
and then you keep seeing it and get tired of its patterns of speech etc and oh it's just making up nonsense
and now the ai slop "documentation" is up on the public internet for all to see with no way for me to remove it :)
Do we need this, when we have tools like Claude Code, Codex etc that you can talk to about the codebase they are started in?
what about the dependencies? you could just clone them as well (which is what I do occasionally), but deepwiki is faster (for indexed repos) and free
I really don't like how AI summaries creep up in SEO rankings and make it harder for me to find the actual, official documentation.
I'm working on RecallBricks (memory infrastructure for AI coding tools) and seeing similar problems: AI tools are great at answering questions about code right now, but they don't remember the conversation you had last week about why you chose this architecture over that one.
For documentation specifically, have you thought about combining the AI-generated docs with a memory layer that captures decision history? Like "this API endpoint exists because of issue #247 where users needed X functionality." That context makes docs way more useful than just describing what the code does.
Curious how you're handling the "outdated docs" problem mentioned above - do you have triggers to regenerate when code changes significantly?