I can empathize with the author. The first time you write some code collaboratively with GPT and it actually works, you feel a burning need to shout about it. Because it's one of those moments where something "clicks" and you suddenly feel like you've discovered fire. Once you figure out how to work with them, it makes you excited for the future and you can clearly see where LLMs will fit permanently into your toolbelt. They're far from perfect now, and sometimes the time savings is a wash - you get instant specialized expertise that can produce code like a senior engineer, but you need to goad and coax it like it's a high maintenance intern. But the thinking power expended is still somehow lower - it's a new way of working with technology and deferring some of the grueling parts to the machine. This becomes especially obvious when the code requirements depend on an esoteric API or conventions that you'd normally need to spend time researching and manually enumerating.

Author here. My intention was to show that you can use it to help you get going quickly for a very practical, one-off, and self-contained use cases. As I mentioned in other comments already, I did not trust it blindly and did not share any sensitive data with it. Definitely not an ad!