I am the solver programmer mentioned in the article. I think it came out pretty decently. Maybe not all the details are right (I was late answering fact checking email) but I think it's a decent read and the author has done a good job!
I noticed in the article that piosolver can incorporate a mixed strategy with multiple bet sizes. Pretty neat, is that a recent feature? As I rememember it, a few years back people would discuss what the optimal bet size was in various situations with the implicit assumption that there is just one.
What happened in chess is now happening in poker: at first people were all about the best theoretical move and then gradual shift to "not necessary the best just sound enough but less likely to be analyzed by the opponents" started happening.
As to the first part of your question: the solutions are pretty much perfect. The only assumption is about possible bet sizes. As to accuracy we measure it in theoretical exploitability (how much a perfect adversary who knows our strategy exactly could win against us). You can easily go so low that even a theoretical perfect adversary wouldn't get close to beating the rake vs the solution, even at high stakes.
Disclaimer: I'm doing phd in this area, generalizing to harder games than poker.
We considered it very unlucky that the science paper was published as we thought more people will implement solvers then (ours was ready in mid 2014 and we released and a working solver with a GUI in early 2015, 3 months after the Limit Holdem paper). As it turned out though it didn't really matter much.
I had an idea to code a poker solver around 2008. Unfortunately I was yet to learn to code back then. The biggest challenge was to overcome implementation issues. Once I got the crucial part to be fast enough I knew the solver is possible. I think not having much background in the field allowed me to come up with more natural (and better) tree representation and memory efficient (even if not the fastest) algorithm as I was thinking more as poker player than a computer scientist back then.
It’s an interesting history.