Many computing problems of today are dressed-up reflections of the past. By studying the timeless literatures of the past, and temporarily ignoring the "new is always better" attitude, we can find effective solutions to the problems of today.
Be it web caching, which can take inspiration from microprocessor's cache architecture. Or distributed computing, which is correlated with the no. of machines processing something regardless of the absolute quantity of data. Or even the application of machine learning to the real-world, that can take a lot of statistical lessons from the past. Or substituting the reckless use of regex with a DSL if only compiler theory was more intelligently applied. And the list goes on.