[jdprgm]

I had basically this exact idea too a few months ago and at the time already found a few implementations attempting it. https://robomonkey.io/ being one example I found so didn't pursue it further.

Also it turns out llm's are already very good at just generating Violentmonkey scripts for me with minimal prompting. They also are great for quickly generating full blown minimal extensions with something like WXT when you run into userscript limitations. These are kind of the perfect projects for coding with llm's given the relatively small context of even a modest extension and certainly a userscript.

I am a bit surprised YC would fund this as I think building a large business on the idea will be extremely difficult.

One angle I was/am considering that I think could be interesting would be truly private and personal recommendation systems using LLM's that build up personal context on your likes/dislikes and that you fully control and could own and steer. Ideally local inference and basically an algo that has zero outside business interests.

[jmadeano]

Great minds think alike :) I think it is important for users to have more control over how the browse the internet, so I'm happy to see others building in the space!

> Also it turns out llm's are already very good at just generating Violentmonkey scripts for me with minimal prompting. They also are great for quickly generating full blown minimal extensions with something like WXT when you run into userscript limitations.

We've thought about full blown extensions and maybe we'll get there, but I'd wager that there is gap between users who would install/generate a userscript vs a full blown extension. Also a one-click install userscript is much simpler to share vs full chrome store submission/approval (the approval time has been a pain for many developers I've talked with). With that said, this is early days and we're still figuring out what people want.

> One angle I was/am considering that I think could be interesting would be truly private and personal recommendation systems using LLM's that build up personal context on your likes/dislikes and that you fully control and could own and steer. Ideally local inference and basically an algo that has zero outside business interests.

I've definitely considered the idea of your own personal, tunable recommendation system that follows you across the web. And I have some background there (worked on recommendations systems at Pinterest), but recommendation systems are very data hungry (unless we regress to the XGBoost days), and task of predicting will/won't the user like this image (binary) is vastly easier than operating over the entire page UI. Definitely not impossible, but we aren't there yet. For now, I just want to make it super easy for you to generate your own useful page mods

[AJ007]

Maybe I'm going too far from the tipping point of "this is easy" when it actually isn't, but the ability to clone an open source project now, modify some part of it, and then compile it locally seems like the future. This is almost trivial to do now.

Why not do the same for the web?

Without going off on a rant about all of the user hostile bullshit that's being shoved down our throats right now, I think one inevitable outcome of AI is that users are going to need to have defensive local AI agents protecting them and fact checking data. This is the trojan horse for the big tech companies that rely on ad revenue and dark patterns to manipulate their users: if they provide the AI agents, they will be obviously inferior and not super-intelligent, just like when Google's early public image-gen model was making image of ethnically and gender diverse nazi soldiers, etc.

[gagik_co]

Yeah I have thought about more user friendly Violentmonkeh before. This sort of thing just needs to be open source and non-profit, there isn’t even much upkeep to it. At what point will the investors want some form of return?

This is built from the system that created enshittifcation in the first place; a cleaner web is definitely not going to come from a startup.