Workers in denial are like lemmings, headed for the cliff... not putting myself above that. A moderate view indicates great disruption before new jobs replace the current round being lost.
As a writer, this is deeply comforting. The book is total shit. It sounds like an AI, not like something a person would connect with for even a moment. Not even in the opening lines.
When you've read it in its entirety, could you indicate on a scale from 1 to 10 what score it would get compared to published books you've read (including of course all the best and the worst ones)?
If you flip through something claiming to be a "book" and immediately see that a majority of pages just contain nonsensical bulleted lists, and furthermore see that chapter titles are printed overlapping with the book title on each page, you can correctly conclude the entire thing is a zero-effort pile of shit without wasting any further time to read it.
I read through a bit of it and it really wasn't all that bad. The only thing that I found to be really problematic were the made up experiences. Clearly hallucinations are still a big problem for LLMs, but if we manage to get rid of those a book like this can really be quite serviceable (a lot of human-written books are badly written so the bar isn't incredibly high, imho).
The creator should really tweak the prompt/process to include automatic review explicitly intended to remove hallucinations. It clearly is already the intent: "Future iterations of this experiment will include AI-powered fact-checking of the content."
I'm looking forward to what the improved version will look like.
Flip through the middle of the book. Nearly every page has either a bulleted list or a numbered list. In several cases, a single list spans multiple pages.
That’s the format of an outline, not a legitimate book.
Is it? Or are 'legitimate' books just too often not concise and structured enough?
I do a lot of personal knowledge management and I use a shit ton of sections and lists in that. Books evolved from the art of telling stories, not from efficiently conveying knowledge. Perhaps we're just way too used for books etc. to an approach that is suboptimal. I know I personally despise news articles and blogs that start with "setting the scene" and are incredibly and needlessly verbose, using thousands of words to say what could be made clear in a single paragraph.
Viewed from another angle: Reading text is inherently serial in nature even though a lot of things are related to each other in a graph. A document with sections with bulleted lists is actually a way to represent a tree, which is closer to a fully unconstrained graph. I would argue that trees like that are much easier to parse than classically written texts.
There is irony here in that I only used some whitespace to add structure, but never used any bulleted lists in this comment.
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I did generate an alternative with Google Gemini 2.5 Pro, but the formatting doesn't work here on HN. It was decent, though!
> I do a lot of personal knowledge management and I use a shit ton of sections and lists in that.
That's because these are notes, not a book. A list-heavy outline format makes sense for notes, as these are summaries that supplement your own memory and knowledge you've already taken in. They're not a sole/primary source of conveying knowledge to others on their own.
> Perhaps we're just way too used for books etc. to an approach that is suboptimal.
If you truly believe books are "suboptimal", I can only suggest that you consider looking inward and do some reflection:
Is the "problem" really with books and long-form writing, which is the dominant form of knowledge transfer across several thousand years of human civilization?
Or is the problem with people's attention spans in the past decade, due to dopamine-fueling social media doom scrolling and AI usage?
When AI is cheap, why use juniors, regular software engineers or off-shore labor at all? AI replaces these things. Why not use the best available talent to oversee and guarantee the work of coding agents? To define requirements and translate them into maintainable code? This is the trend. It takes mastery to produce good, maintainable code from vague requirements using coding agents. This seems like value add a human will continue to provide.
I also see the blending of engineers and data scientists with product managers.
When AI is cheap, why use off-shore labor at all? AI replaces it. Why not use the best available talent to oversee and guarantee the work of coding agents? To define requirements and translate them into maintainable code? This is the trend.
I am building a knowledge graph using BAML [baml-py] to extract documents [it's opinionated towards docs] and then PySpark to ETL the data into a node / edge list. GPT4o got few relations... Gemini 2.5 got so many it was nuts, all accurate but not all from the article! I had to reign it in and instruct it not to build so vast a graph. Really cool, it knows a LOT about semiconductors :)
So you probably shouldn’t trust any external service and we do have the ability to subscribe to any topic. But we have zero interest in snooping unless we discover illegal activity at which point we will take immediate action.
I don't really mean you, but let's say you are compromised... if I put a localhost http server up on the web using your stuff, am I now compromised? Not clear how this would work...
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