Adaptive compilation uses a feedback-driven process to leverage additional compilation time into improved executable performance. Previous work on adaptive compilation has demonstrated its benefit at an inter-optimization level. This dissertation investigates the ability of adaptive techniques to improve the performance of individual compiler optimizations. We first examine the ability to use adaptive compilation with current commercial compilers. We use adaptive techniques to find good blocking sizes with the MIPSpro compiler. However, we also observe that current compilers are poorly parameterized for adaptive compilation. We then construct an adaptive inlining system that demonstrates the potential of adaptive compilation to improve individual optimizations. We design the inliner to accept condition strings that determine which call sites are inlined. We develop an adaptive controller for the inliner based on a detailed understanding of the search space that the condition strings provide. Our adaptive inlining system consistently finds good sets of inlining decisions and outperforms static techniques. In addition, we demonstrate the inability of static techniques to provide a universal inlining solution and the necessity of adaptive inlining. Adaptive inlining demonstrates the capacity of adaptive compilation to improve the performance of a single, carefully designed optimization.