The 'directionality' of reductions?
Don't worry&nbsp;&ndash; everybody gets confused by the direction of reductions. Even people who've been working in algorithms and complexity for decades occasionally have a, "Wait, were we supposed to be reducing $A$ to&nbsp;$B$ or $B$ to&nbsp;$A$?" moment.

Reducing $A$ to&nbsp;$B$ produces a statement of the form "If I could solve&nbsp;$B$, then I'd also know how to solve&nbsp;$A$". "Solve" in this sense could mean "compute using any Turing machine", or "compute in polynomial time" or whatever other notion of solution your context requires.

This may seem counterintuitive, since "$A$ reduces to&nbsp;$B$" implies that solving&nbsp;$B$ is at least as hard as solving&nbsp;$A$, so you haven't reduced the difficulty. However, you can think of it as reducing the number of problems you need to solve. Imagine that, at the start of the day, your goals were to find an algorithm for&nbsp;$A$ and an algorithm for&nbsp;$B$. Well, now that you've found a reduction from $A$ to&nbsp;$B$, you've reduced your goals to just finding an algorithm for&nbsp;$B$.