Do you have a dumb question that you're kind of embarrassed to ask in the main thread? Is there something you're just not sure about?
This is your opportunity to ask questions. No question too simple or too silly.
Culture war topics are accepted, and proposals for a better intro post are appreciated.
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Is there a tactful way to ask your boss to lay off something? My boss, a smart guy whom I respect, has become obsessed with LLMs. Literally every conversation with him about work topics has become one where he says "I asked (insert model) and it said..." which adds no value to the conversation. Worse, he responds to questions with "have you tried asking AI?". For example the other day I asked him if he knows why multiple TCP streams are faster than one (when you would naively think they would be slower due to TCP overhead), and he asked if I asked AI. Which of course I didn't, because I actually wanted to know the answer, not get something plausible which may or may not be correct. And he's like that with every question posed lately, even when we had legal documents we had questions on he was like "did you try feeding it to Gemini and asking?"
It's frankly gotten incredibly annoying and I wish he would stop. Like I said, I actually have a lot of respect for the man but it's like he's chosen to outsource his brain to Grok et al lately. I suspect that my options are to live with it or get a new job, but figured I'd ask if people think there's a way I can tactfully address the situation.
Your boss has a point, at least in my opinion. If you're using a good LLM, like GPT-5T, hallucination rates are close to negligible (not zero, so for anything serious do due diligence). You can always ask followup questions, demand citations, or chase those up yourself. If you still can't understand, then by all means ask a knowledgeable human.
It is a mistake to take what LLMs say as gospel truth. It is also a mistake to reflexively ignore their output because you "wanted to know the answer, not get something plausible which may or may not be correct". Like, c'mon. I hang around enough in HN that I can see that even the most gray bearded of programmers often argue over facts, or are plain old wrong. Reversed stupidity is not intelligence.
Human output, unfortunately, "may or may not be correct". Or that is true if the humans you know are anything like the ones I know.
I even asked GPT-5T the same question about TCP parallelism gains, and it gave a very good answer, to the limit of my ability to quickly parse the sources it gave on request (and I've previously watched videos on TCP's workings, so I'm familiar with slow start and congestion avoidance. Even I don't know why I did that).
It's certainly true that human output can be incorrect. But it's incorrect at a much lower rate than an LLM is, assuming you ask a human who knows the topic. But that aside, it seems to me like "have you asked AI" is the 2025 equivalent of "let me Google that for you", and is just as annoying as that was. If I trusted an AI to give me a good answer I would just ask it, I don't need someone else to remind me that it exists.
"Let me Google that for you" wasn't always an invalid response. Very many questions that people can/do ask are trivially solved by a Google search.
LLMs are far more powerful than Google (until Google Search began using a dumb LLM). The breadth of queries they can reliably answer is enormous.
The specific question you asked your boss is in their capabilities! I checked! I can share the conversation if you want.
I ask a lot of hard questions. They are correct probably >95% of the time, and errors are usually of the omission/neglect type than falsity.
My point is that you aren't trusting LLMs enough. You don't, and shouldn't, take them as oracles and arbiters of truth, but they're good. Your boss is directionally correct, and will be increasingly so in the future. Especially so for conceptual, technical questions that don't depend heavily on your workplace and tacit knowledge (though they can ingest and make use of the context if you tell them).
If you asked most of your questions using an LLM, you will usually receive good answers. If the answers seem incomplete or unhelpful and there's an aspect you believe that only your boss can answer, then by all means ask him. But in all likelihood, that approach will save both you and him time.
On a practical note, I really hope either you or your boss pay for or have used the very best LLMs out today. GPT-5T is incredibly smart, and so is Gemini 2.5 Pro or Sonnet 4.5. They are very meaningfully better than the default experience of a free user, especially on ChatGPT. 90% of the disappointment going from 4o to 5 was because users were (by what might well be called a dark pattern) using basic bitch 5 instead of 5 Thinking. If your boss is using free Grok, it's not the worst, but he could do better.
And coding/IT is a very strong suit. To be fair, so is medicine, but I have had great results on most topics under the sun. If I had need for research grade maths or physics, they're still useful!
I am more than happy to field what you think is the hardest programming query you can come up with through 5T, ideally one that free ChatGPT can't handle. You have to push their limits to know them, and these days I can barely manage that with my normal requirements.
Do you find it reliably better than default 5? It seems to me that it's rather over-done and prone to skip ahead to something that is not necessarily what I want, rather than answering the specific query and working through with me as I prefer.
I'm not a frequent enough LLM user to say how much of this was solid improvement vs luck, but my experience with free ChatGPT 5 (or any current free model, for that matter) versus paid GPT-5-Thinking was night vs day. In response to a somewhat obscure topology question, the free models all quickly spat out a false example (I'm guessing it was in the dataset as a true example for a different but similar-sounding question), and in the free tier the only difference between the better models and the worse models was that, when I pointed out the error in the example, the better models acknowledged it and gave me a different (but still false) example instead, while the worse models tried to gaslight me. GPT-5-Thinking took minutes to come back with an answer, but when it did the answer was actually correct, and accompanied by a link to a PDF of a paper from the 1980s that proved the answer on like page 6 out of 20.
I followed up with a harder question, and GPT-5-Thinking did something even more surprising to me: after a few minutes, it admitted it didn't know. It offered several suggestions for followup steps to try to figure out the answer, but it didn't hallucinate anything, didn't try to gaslight me about anything, didn't at all waste my time the way I'm used to my time being wasted when an LLM is wrong.
I've gotten used to using LLMs when their output is something that I can't answer quickly myself (else I'd answer it myself) but can verify quickly myself (else I can't trust their answer), but they seem to be on the cusp of being much more powerful than that. In an eschatological sense, maybe there's still some major architectural improvement that's necessary for AGI but still eluding us. But in an economic sense, the hassle I've always had with LLMs is their somewhat low signal-to-noise ratio, and yet there's already so much signal there that all they really have to do to have a winning product is get rid of most of the noise.
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