The MongoDB query engine can benefit from simplifying complex Boolean expressions to improve query performance. Document databases like MongoDB encourage storing data in fewer collections with a large number of fields, which improves efficiency but requires careful handling of complex filters. Simplifying Boolean expressions can reduce computational overhead and enable better plan generation, leading to faster query execution times. The solution uses a modified Quine-McCluskey algorithm and Petrick's method on an efficient bitset representation of Boolean expressions. MongoDB's culture supports innovation by empowering engineers to tackle problems and solve them from beginning to end. The simplification technique can lead to significant improvements in throughput, such as 18,100% in one demanding case involving large collections and selective indexes. The project reflects MongoDB's commitment to turning customer challenges into successes and its practice of taking what is learned from individual projects and making broad improvements to improve performance.