The Barabási-Albert model grows scale-free networks via preferential attachment — rich get richer. Bianconi and Barabási added node fitness η, drawn from a distribution. When fitness variance is high, a fittest-gets-all phase emerges (Bose-Einstein condensation on networks): one supremely fit node captures a finite fraction of all links, suppressing the scale-free degree distribution.