Agreed, and there is already a solution that’s better to support anyway. It may not be perfect, but Wikipedia operates on this model at scale at a much smaller annual budget than any of the AI companies and has produced much higher quality content overtime for all of humanities benefit than the AI teams which are most just scraping the work of others while spending most of their original work to replace human labor for their own financial benefit.

Wikipedia community bans AI-generated entries because verifying and removing AI hallucinations imposes even more workload on editors than writing articles from scratch [1, 2].

If you don’t agree that Wikipedia’s approach, one can always fork it like was done with SpaceX / Twitter did with its launch of Grokipedia on October 27, 2025, which hasn’t been really incorporating much improvement well with lots of digressions in its quality and reliability [3].

[1] https://en.wikipedia.org/wiki/Wikipedia:Writing_articles_wit...

[2] https://en.wikipedia.org/wiki/Wikipedia:Editing_policy#Artif...

[3] https://en.wikipedia.org/wiki/Grokipedia#Reliability

[Edited for better formatting]

This is exactly how I use Claude in all of my technical writing. I even wrote a skill for this.

Every claim has to be backed up by a reference. Every reference has to be double-checked. Primary sources are much preferred over secondary sources, and where no primary source can be found, that must be noted.

I also insist on simpler, more easy-to-understand writing, even if that makes the total output longer. Aiming at a general audience, of the same reading level as a standard newspaper.

Most of the rest of the skill is about ensuring the Chicago Manual of Style is properly followed, widow/orphan control and how that applies to callout boxes, tables, etc….

I've had the same thought as probably have many others - what solutions exist in this space?

To put it into words: a layer over an LLM that tracks provenance: the documents it has access to, the facts it has extracted, the mathematical expressions and queries it's run and finally the artifacts and results it's yielded complete with receipts for exactly how it arrived at it's findings and conclusions.

I assume legaltech products have to do it like this. Is the general pattern implemented somewhere on github?

But soon, the majority of those references, documentation and work will be AI generated. We are peeing and likely defecating in our own water well.

I mean you can definitely do that - just set it up do to that.

What you are describing is that a majority of humans are inherently not interested in that. There are are a subset of people who would like to do that - and certainly can now that they have the tooling.

Its just a vastly strong tool. If you want it, build it.