I understand the value prop you are describing, but that is not the value prop described in the article. The article did not describe an LLM agent intuiting a h

I understand the value prop you are describing, but that is not the value prop described in the article. The article did not describe an LLM agent intuiting a hypothesis, checking with data, and coming up with a narrative all for 60 cents. The author did 80% of the work, and had the LLM do the final stretch. Maybe there's value there, but the article did not present a workflow that obviated the need for graphs. This execution gap is common in these LLM blog posts (ex. the LLM can write a login function in Swift, so the author claims LLMs will be writing production ready iOS apps tomorrow). The common thread I see is that getting from the point of "explain why this endpoint is slow" to the point of "An LLM agent can chase down hypotheses, several at a time, and present them with collected data and plausible narratives." is a lot more expensive than 60 cents - it's months of paying for an enterprise license where this feature is promised to be "just around the corner"