Many researchers (including me) spend a large chunk of their time writing code, despite having little to no formal training about how to do so effectively. This results in wasted time, lower-quality output, and also negatively impacts the reproducibility and transparency of our work. In this OSCoffee, we will discuss the importance of good research code, and some strategies and tips (some Python-specific, some language agnostic) that can make your code more usable, replicable and adaptable.