If you let a continuous-time Markov chain run for a very long time, sometimes it settles into a kind of probabilistic steady state — where the chance of being in any given state no longer changes. That steady state is exactly what this chapter is about: how to find it, when it exists, and why it links to the jump chain that records just the state visits.