Sorry - that probably came across as more passive-aggressive that I mean it. Just wanted to point out that guideline. People have easy access to AI, so they can always ask it for a summary if they want to and it doesn't really add anything to the discussion.

At this point I believe that when people do not cite using AI to generate their comment it's from a position of malice... like you're intentionally trying to position yourself as capable in whatever subject you're talking on but realistically you are not given the reliance on an LLM. Not saying anything about OP but just a general observation/opinion I've been building recently. Seems more common than ever to larp using AI.

> quoting and citing an LLM is miles better

Not really. If someone is interested in an LLM's opinion, they can ask it themselves, all LLM providers are one browser tab away.

So customers use OpenRouter to avoid lock-in to specific model providers, and in doing so they lock-in into openrouter's aggregation API?

Lock-in to what exactly? A string(string) function without any further restrictions? Note that aggregator users will not use more specific parameter features (because those vary by vendor), or they escape the aggregator and lock-in directly string(string, vendorOptions={"openAI.logprobs":true})

Selling vendor lock-in to vendor lock-in avoidant customers sounds like a losing proposition, like trying to beat competition on price and undercutting, which is a thing openrouter does too btw, the main reason people use these products is to get cheaper prices. I don't think 2$/M tokens is expensive, and I don't think those that try to cut costs are going to win, whether devs cutting token costs, or small business owners with 5 employees who look at AI as a way to fire 2 of them. I get that the other end of the spectrum is overspending and tokenmaxxing, but the conclusion is that extremes are bad? Nothing new here.