Read the book! It is a excellent read. There are technical details in it a-plenty.
_When Genius Failed_ isn't simply a description of a scandal, but also a pop-grade exploration of the technical factors that led to the scandal. The book is impossible to write without conversance with its technical subject matter. Which is my point: Lowenstein wasn't a quant, but he was able to accurately and effectively write on them.
For example, when discussing LTCM volatility strategies: >The stock market, for instance, typically varies by about 15 percent to 20 percent a year. Now and then, the market might be more volatile, but it will always revert to form—or so the mathematicians in Greenwich believed. It was guided by the unseen law of large numbers, which assured the world of a normal distribution of brown cows and spotted cows and quiet trading days and market crashes. For Long-Term’s professors, with their supreme faith in markets, this was written in stone. It flowed from their Mertonian view of markets as efficient machines that spit out new prices with all the random logic of heat molecules dispersing through a cloud. From this quote it looks like Lowenstein believed that 1. Volatility is not mean reverting 2. The reason people at LTCM believed volatility was mean reverting was due to complex mathematical models rooted in market efficiency. Now, volatility mean reversion is something that can be easily seen by looking at a graph of volatility over time [1].
Also, Lowenstein does not do a good job at describing the way LTCM modeled risk, and the way it failed. In fact, he barely even tries. He just hints here and there about "correlations going to one", but nothing more. For example, which assumptions failed? Did they assume that different kind of bets (relative value between bonds, merger arbitrage, arbitrage between double-listed equities, etc) were uncorrelated? Did they get hurt more by different kind of bets being correlated, or by some bets going particularly wrong? Did they stress test their risk measures in any way?
[1] E.g. https://a.c-dn.net/b/4tKv1V/Forex-Trading-Video-SPX-and-VIX-...
You are in no position to judge how accurately or effectively it was written (unless you judge effectiveness as entertaining you).
How about another example: Bill Bryson. He's a brilliant writer and I really like all of his books. Except for A Short History of Nearly Everything. That's mostly a regurgitation of other popular science writers; it is a good read, but if you are fond of the genre, you'll spot his sources and it kind of ruins the effect.
Compare those with J.E. Gordon on structures and materials, John Clark's Ignition (which is a collection of amusing anecdotes and settling scores, I admit; the closest in my field is M.A. Padlipsky), Peter Ward (Gorgon), or Mark McMenamin (The Garden of Ediacara, some thumbs up).
If you want to know the story behind some event, journalists are admirably well suited to tell it. If you want to know about some field, they really aren't. In a world full of books, reading a journalist writing about phlebotomy or biochemistry is probably not all that useful.
I'm definitely in agreement about your Dijkstra amnesia effect.