We've moved the goalpost for AI often enough that even being as capable as "a sufficiently dedicated human analyst" is not considered noteworthy.
I keep banging on that drum but the first AI system to prove mathematical theorems was Logic Theorist by Alan Newell and Herbert Simon, presented at the Dartmouth conference that named the field of AI in 1956. Wikipedia says:
Logic Theorist proved 38 of the first 52 theorems in chapter two of [Alfred North] Whitehead and Bertrand Russell's Principia Mathematica, and found a new and shorter proof for Theorem 2.85.[3]
https://en.wikipedia.org/wiki/Logic_Theorist
The first system to outperform human experts in medical diagnosis was MYCIN, an Expert System from the early 1970's at Stanford. Wikipedia again:
An evaluation of MYCIN was conducted at the Stanford Medical School. The first phase of the evaluation consisted of 10 test cases of diverse origin, chosen by a physician who was not acquainted with MYCIN's methods or knowledge base. These cases were presented to 7 physicians and 1 senior medical student. 10 prescriptions were compiled for each of the cases, 1 recommended by MYCIN, 1 prescribed by the treating physician at the county hospital, and 8 by the aforementioned individuals. The second phase of the evaluation consisted of eight infectious disease specialists being provided the clinical summary and set of 10 prescriptions for each of the 10 cases and tasked to provide their own recommendations for each case and assess the 10 prescriptions. MYCIN received an acceptability rating of 65%, which was comparable to the 42.5% to 62.5% rating of five faculty members.[9] This study is often cited as showing the potential for disagreement about therapeutic decisions, even among experts, when there is no "gold standard" for correct treatment.[citation needed]
https://en.wikipedia.org/wiki/Mycin#Results
And then of course there's the long history of human-dominating AI players for traditional board games starting with DeepBlue's win against GM Gary Kasparov in 1996.
Again: we've had that sort of AI for a long, long time now.
It would be great if any claim of "moving goalposts" has better be very well informed about the history of AI and its accomplishments, as well as its failures, first.
Common sense is ironically the hard part of AI, not the fix-point rule application.
So any exclamation of "it was just using common sense", is missing the forrest for the trees.
Still, OP’s argument still holds even if AIs today have much more data to rely upon.
The internet is at your disposal go write a bunch of rules that make use of that data to do common sense reasoning, I dare you.
I don't know why you say this, I didn't say anything about common sense.
However, you mention CYC. That's a system that is perfectly capable of common sense reasoning and very much like an LLM in many ways. And that should be no surprise: LLMs are giant Expert Systems trained on a human knowledge-base, i.e. the web. OpenAI basically managed to achieve what Doug Lenat was trying to achieve except they did it with machine learning over massive data and compute instead of painstaking manual coding, but it's the same kind of system in the end.
Neural fuzzy systems can represent complex superpositions succinctly, knowledge graphs are collapsed and crisp.
It's like saying the tree unfolding of a graph is the same as that graph. Sure in the limit at infinite space requirements.
You can also consider Watson, different to Cyc in that its knowledge base was built with a lot of machine learning, including some neural nets. It wasn't an LLM but the original version (before corporate went at it and destroyed it) was perfectly capable of interacting in an open-ended manner, notably winning at Jeopardy years before BERT was a glimmer in Jacob Devlin's eye.
I note again that you were the one who brought common sense reasoning in the conversation but there's a large literature on rule-based systems that do that based e.g. on non-monotonic logics. You should familiarise yourself with that literature before engaging in dares with strangers on the internets.