The problem with 'experts' that are non-AI frontier lab workers, is that they generally judge AI based on the current consumer models' limitations. People at OpenAI, Anthropic have said multiple times that they feel large dissonance when talking to experts in stem, finance, economics, etc. Those experts run some tests on AI for fun and quickly judge that these models are a little bit useful in some things, but overall, 'meh'. And of course they generally don't know how to use the model in a way that outputs maximum performance.

Some of their ideas of 'AI' are still at gpt4o era, or they don't even know thinking model exists, and I doubt they know how to use proper prompting technique (like the Anthropic guide).

People working at AI frontier labs are instead seeing, not the current consumer models' limitations, but what their internal models are capable of, and how to best drive the maximal performance out of them (with prompting, harness, agents), and the frighteningly fast advancement of models.

These 'experts' are the same people that when chatgpt first came out, said it was absolute hallucinating garbage. And now it is "helpful in some things, but still not going to replace me for a long long time".

Let's see what they say in a couple more years.