The standard statistical practice is to fix your risk of false positives through the preemptive choice of a p-value threshold and then to attempt to minimize your risk of false negatives through increases in the "power" of your experiment. But, honestly, these two are in tension with one another. There are lots of possible choices.
It's important to know the difference, though. It changes how you interpret results. A positive result might be doubted because you, as a reader, would have preferred more protection against false positives, and, thusly, a smaller p-value threshold. A negative result might be doubted because you believe that the experimenter under-powered their experiment. You might also, in a repeating experimental process, wish to obtain greater power by sacrificing false-positive protection. This is as easy as changing the p-value threshold.
A last perspective is that in the typical scientific practice, you basically control false-positives through pushing the p-value down and making the experiment more challenging (reducing power). Then, you re-establish power through more expensive experiments (use better tools, run the experiment for longer, improve controls, improve data efficiency). Often the "typical" p-value is set by the community in relation to what level of false-positive the overall community is willing to tolerate in publication. That's why psychologists are happy with a 5% threshold whereas physicists might seek a threshold of 10^-3 or smaller. The physicists are upholding themselves to a much more expensive experimental standard and would vastly prefer false negatives.
In fact you're probably (probably!) better off building a good intuition within the domain and then improvising the tests, in the sense that this way you're less likely to arrive at bogus conclusions, as opposed to someone who thinks they'll just apply some formula like this was a high school maths problem - here we plug in some magic that speaks back the truth. I've seen it time and again that (especially senior) people can rapidly and accurately judge the results of things based on very "un-scientific" improvised methods and numbers. YMMV.