With bayesian probability a single observation can be informative (in the sense that a single observation leads to a change in distribution over hypotheses or parameters). It's a matter of narrowing down beliefs on weighted possibilities though, not a definitive answer on the state of reality.
The author doesn't rely on observation. They propose combinatorial models, obtain large time estimates and notice that observation is consistent with these estimates because sample size one, it's a coincidence.
