Automated Caching with RTK Query (Part 4)

In Part 3 , we looked at how Tanstack Query revolutionized caching by moving server state out of our global state managers. But what if you work on a massive enterprise application that is already deeply invested in Redux ? Do you have to rip out Redux to get good caching? Absolutely not. Welcome to Part 4 . Let's talk about the tool that made Redux fun again: RTK Query . Introduction If you spend enough time on tech Twitter (X), you will inevitably hear people saying things like "Redux is dead." This is not true as redux is powering some of the largest, most complex applications on the internet. However, the way we write Redux has fundamentally changed with the introduction of Redux-Toolkit (RTK) In the old days, fetching a list of users in Redux required a mountain of boilerplate: Write an Action for FETCH_USERS_REQUEST . Write an Action for FETCH_USERS_SUCCESS . Write an Action for FETCH_USERS_FAILURE . Write a massive Thunk to make the actual API call. Write a Reducer to handle the