The author is a bit too categorical, there are certainly use-cases where both speed and code-size matters a great deal. Others have mentioned Monte Carlo algori

The author is a bit too categorical, there are certainly use-cases where both speed and code-size matters a great deal. Others have mentioned Monte Carlo algorithms, but there are others: not very long ago I was doing an effect in a shader that needed a PRNG, it would have been lunacy to use a CSPRNG. High quality statistical properties are not important at all, but speed and instruction size is VERY important. My hunch is that this is often true in game-dev: Minecraft probably should not use a CSPRNG to generate its random world. However, in general, I basically agree: for MOST tasks where you need a random number generator, a CSPRNG is probably the right choice and it's a reasonable "default" choice if you don't have good reasons why it shouldn't be. It's a continual annoyance to me that PRNG libraries usually don't include any solid CSPRNGs (looking at you, C++ header <random>) when it's often the right choice.