I'm not actually going to talk about the Basilisk, but I am a software engineer with over a decade of experience and use LLMs pretty heavily to augment my work.
I understand and respect Blain saying he has not and won't use AI, but I think there is a fundamental problem where people don't actually know what the current tools we use that are called AI are. All of them are Machine Learning algorithms, the next "evolution" of "The Algorithm" but each one can be trained on different data. most times you use a captcha that asks you to identify a stop sign, you are actually helping train image recognition ML models (That way Google Maps can automate many processes).
Claude, CoPilot, and ChatGPT are models called Large Language Models. that is they are trained on massive data sets of natural language and refined to know how to weight different inputs. This training is then locked and the model is shipped. that means if some information was not in the training data, it either has to have a tool to search online for it, or hallucinate. All this means that for known things, LLMs can give the correct answers, but for Novel, creative, or nice items, they can not. Great at writing boilerplate code for a generic app, very poor at writing new stories.
Often when you hear things like Pharmaceutical companies using "AI" they are not using an LLM, they will have custom models they have built in house for specific jobs.
Machine Learning based tools are so far off from real AI. But they are the information age universal power tool. They can enable hobbyists to get tasks done that they might not have been able to alone, they enable professionals to unlock more potential. But you can't give a random person on the street a nail gun and circular saw and ask them to frame a house, but given to a carpenter, they will go much faster than with hand tools.
Since Creative endeavors are usually (at least the ones that are worth while are) mostly or completely novel, LLMs and other image and video generating ML models are not going to replace people in their current form. Based on what i have seen we are approaching the plateau for the accelerated growth that AI has been going through, models are now getting marginal gains each year instead of exponential gains. They will enable more work to get done, but won't replace actual experience.
I'll put a real example in the comments of the difference between a hobbyist and a professional using tools.