Claude helped write the article. It is 2026. I proof read it though and yes, giving an LLM a list of specific criteria of what you are looking for in a product is actually a pretty good experience.

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paffdragon 7 hours ago | parent | next [-]

If it works for you, it works. I just see the same phrases used repeatedly so frequently nowdays - including my own LLM conversations.

Regarding the use of LLM for picking infra. The issue I usually have with such task is that they frequently omit things - either from the list of options or the features compared. And depending on my familiarity with the topic, I might never notice, which might steer my decision making into a different direction. Basically a certain bias. Sometimes prompting it to repeat reveals more, but ultimately I end up hitting the search and doing my own research, then I might use the LLM again with now more knolwedge and data. Did you run into this too? What was your process?

	▲	willy__ 7 hours ago \| parent [-]
		I do understand what you mean with bias.. some models where quite stubbornly ignoring things like "I want made in EU - not GDRP compliant - not one office or data center in the EU". I remember this being especially painful for TEM and market email providers. Usually they suck at finding the right pricing data at first try.. so I ended up throwing screenshots of pricing pages. Now that I am writing this up, in some instances manually comparing them would have been faster :D ... The bias might come from the huge amount of US dominance in training data and might not even be intentional. In some niches you don't have many options, that's what I tried leaning on in the article.

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rmsaksida 3 hours ago | parent | prev [-]

> Claude helped write the article. It is 2026.

If that's the case, why do we have to suffer through an AI-generated article? Just give us the prompt.

This topic interests me but I stopped reading as soon as I noticed the slop. I'd much rather read a couple of human-written paragraphs with your personal experience.