This document discusses using profilers to optimize code performance. It introduces common Python profilers like cProfile and line_profiler. As an example, it profiles a fibonachicken.py code that calculates the number of chickens needed based on fibonacci numbers. Both the fib() and is_fibonacci() functions were bottlenecks. Two hypotheses for improvement were tested: 1) optimizing fib() using Binet's formula, and 2) improving is_fibonacci() to not use fib() by using Gessel's formula instead. Profiling confirmed the optimizations were effective. The document emphasizes considering code efficiency along with system details and circumstances to identify optimization opportunities.