Domain-independent planning is one of the long-standing sub-areas of Artificial Intelligence (AI), aiming at approaching human problem-solving flexibility. The area has long had an affinity towards playful illustrative examples, imprinting it on the mind of many a student as an area concerned with the rearrangement of blocks, and with the order in which to put on socks and shoes (not to mention the disposal of bombs in toilets). Working on the assumption that this ''student'' is you -- the readers in earlier stages of their careers -- I herein aim to answer three questions that you surely desired to ask back then already: What is it good for? Does it work? Is it interesting to do research in? Answering the latter two questions in the affirmative (of course!), I outline some of the major developments of the last decade, revolutionizing the ability of planning to scale up, and the understanding of the enabling technology. Answering the first question, I point out that modern planning proves to be quite useful for solving practical problems - including, perhaps, yours.