Generic programming using the C++ template facility has been a successful method for creating high-performance, yet general algorithms for scientific computing and visualization. However, adding template code tends to require more template code in surrounding structures and algorithms to maintain generality. Compiling all possible expansions of these templates can lead to massive template bloat. Furthermore, compile-time binding of templates requires that all possible permutations be known at compile time, limiting the runtime extensibility of the generic code. We present a method for deferring the compilation of these templates until an exact type is needed. This dynamic compilation mechanism will produce the minimum amount of compiled code needed for a particular application, while maintaining the generality and performance that templates innately provide. Through a small amount of supporting code within each templated class, the proper templated code can be generated at runtime without modifying the compiler. We describe the implementation of this goal within the SCIRun dataflow system. SCIRun is freely available online for research purposes.