Stein's method has proved to be an extremely versatile tool for establishing distributional approximations. In this talk, we describe three settings of apparently quite different kinds, in which Stein's method has nonetheless turned out to play a significant part in the analysis: `small world' networks, (logarithmic) combinatorial structures and biological metapopulation models. In each case, Stein's method emerged by accident, rather than by design, illustrating its widespread usefulness.