Chris Hecker coined a comparison at GDC 2008 this year, what I call Simple, Tricky, and Wicked problems. In a similar vein I’ve coined a comparison of my own: good and bad problems. Just as some problems are easy or hard to solve, some problems are important to solve and some aren’t. Or rather, some problems are worth solving and some aren’t. It was worth solving “rewinding gameplay” for Prince of Persia because it significantly improved the game. Strict design control of hundreds of characters is a bad problem. Bad problems aren’t bad design decisions, necessarily. Rather, they are production problems that can led to more work then the problem is worth to the game. AI Engineers run into this all the time, because a lot of AI work is concentrated on it just not looking bad. As a team member, being able to identify where coming at a bad problem sideways or avoiding it all together is a valuable learned skill. The more you can look at a design and identify the good problems to solve – the problems where you get a huge audience payoff vs. the problems that no one will notice the effort – the better your product will be. I claim exponentially better.