There are a broad selection of code-improving optimizations and scheduling techniques based on profile information. Industry has been slow to productize these because traditional ways of profiling are cumbersome. Profiling slows down the execution of a program by factors of 2 to 30 times. Software vendors must compile, profile, and then re-compile their products. In addition, profiling requires a representative set of inputs and is hard to validate. Finally, profiling has had little success for system code such as kernel and I/O drivers. This paper discusses experiences AT&T Global Information Solutions has had with commercializing profile-driven optimizations. Three approaches to profiling are discussed, along with results and comments concerning their advantages and drawbacks. The validity of profiling is discussed. One new innovation, hardware-based profiling, removes many of the problems vendors have with profiling. The paper also discusses methods to profile system code and support debugging. In general, the data and techniques presented in this paper can be used to productize profiling and advocate its use to the software business community.