Critical vulnerability in LangChain – CVE-2025-68664

Why would there be? You're using something to prompt the LLM, aren't you - what's stopping you from sharing the input?

The same logic can be applied in an even larger extent to foreign-language content. I'd 1000x rather have a "My english not good, this describe big LangChain bug, click if want Google Translate" followed by a decent article written in someone's native Chinese, than a poorly-done machine translation output. At least that way I have the option of putting the source text in different translation engines, or perhaps asking a bilingual friend to clarify certain sections. If all you have is the English machine translation output, then you're stuck with that. Something was mistranslated? Good luck reverse engineering the wrong translation back to its original Chinese and then into its proper English equivalent! Anyone who has had the joy to deal with "English" datasheets for Chinese-made chips knows how well this works in practice.

You are definitely bringing up a good point concerning accessibility - but I fear using LLMs for this provides fake accessibility. Just because it results in well-formed sentences doesn't mean you are actually getting something comprehensible out of it! LLMs simply aren't good enough yet to rely on them not losing critical information and not introducing additional nonsense. Until they have reached that point, their user should always verify its output for accuracy - which on the author side means they were - by definition - also able to write it on their own, modulo some irrelevant formatting fluff. If you still want to use it for accessibility, do so on the reader side and make it fully optional: that way the reader is knowingly and willingly accepting its flaws.

The stigma on LLM-generated content exists for a reason: people are getting tired of starting to invest time into reading some article, only for it to become clear halfway through that it is completely meaningless drivel. If >99% of LLM-generated content I come across is an utter waste of my time, why should I give this one the benefit of the doubt? Content written in horribly-broken English at least shows that there is an actual human writer investing time and effort into trying to communicate, instead of it being yet another instance of fully-automated LLM-generated slop trying to DDoS our eyeballs.

I wonder if this code was written by an LLM hahaha

Obviously.

> It gets the information across.

If it is poorly written by a human? Sure!

> The novelty of complaining about a new style of bad writing

But it's not a "new style of bad writing", is it?

The problem is that LLM-generated content is more often than not wrong. It is only worth reading if a human has invested time into post-processing it. However, LLMs make badly-written low-quality content look the same as badly-written high-quality content or decently-written high-quality content. It is impossible for the reader to quickly distinguish properly post-processed LLM output from time-wasting slop.

On the other hand, if its written by a human it is often quite easy to distinguish badly-written low-quality content from badly-written high-quality content. And the writing was never the important part: it has always been about the content. There are plenty of non-native English tech enthusiasts writing absolute gems in the most broken English you can imagine! Nobody has ever had trouble distinguishing those from low-quality garbage.

But the vast majority of LLM-generated content I come across on the internet is slop and a waste of my time. My eyeballs are being DDoSed. The only logical action upon noticing that something is LLM-generated content is to abort reading it and assume it is slop as well. Like it or not, LLMs have become a sign of poor quality.

By extension, the issue with using LLMs for important content is that you are making it look indistinguishable from slop. You are loudly signaling to the reader that it isn't worth their time. So yes, if you want people to read it, stick to bad human writing!