Honestly, this is a clever way of doing this. It means the additional instructions are stored alongside the text they reference, which makes it easier for doc writers to keep in sync and it probably also makes it more effective since the bot is guaranteed to read it at the right time in the right context.
I doubt they actually send it with every request and hide it in CSS, it probably does some other kind of check (IP, user agent, token...). This also tracks with the fact it is now entirely gone - presumably they just fixed that if statement and it's again chatbot-only.
What? This is the most logical solution and the most likely one given the behaviour seen in the post. And even if they were sending every human reader the LLM content too, who cares? It's a few kilobytes at worst in a multi-megabyte page.
It still doesn't make sense. That pages are probably built from an internal repository/database where that information is in a human readable format (e.g. Markdown or some sort of CMS) that is then processed by a CI to produce the public static HTML pages.
It would be more efficient to give the chatbot context the source files, in a format that is more efficient for that (Markdown documents, for example) and that will of course contain the internal notes, that are stripped during the build of the public HTML version.
Why a chatbot should waste resources in parsing a public webpage for the same information that you have internally in possibly a more appropriate format?
Also having a check for user agent/IP to do so is still inefficient, because you can't serve static HTML/CSS/JS and thus you have to do processing work on each request, a thing that doesn't make a lot of sense for static content of this kind.
Nobody said it's efficient, welcome to the modern IT landscape. The docs are surely some SaaS with a WYSIWYG editor, access controls and analytics. Every page probably does a dozen database lookups and involves 3 mixroservices and 4 external providers minimum.
Given they probably need to go through layers of management, across teams, and go through relevant testing to adjust the LLM prompt, this was probably a nice quick and flexible way to create a "shadow" prompt.
Maybe? But it also doesn't necessarily belong into the prompt. The model probably accesses the help pages as a RAG knowledgebase, so putting it there makes sense.
I doubt they actually send it with every request and hide it in CSS, it probably does some other kind of check (IP, user agent, token...). This also tracks with the fact it is now entirely gone - presumably they just fixed that if statement and it's again chatbot-only.