Here we set out to rigorously test the nature of the energy landscape of the amyloid elongation reaction by utilizing a Φ-value analysis inspired approach. The full workflow is shown in Figure . We analyse changes in elongation kinetics as changes in free energy barrier (∆∆G ‡-U ) and fibril stability (∆∆G A-U ) upon mutagenesis to compile an ensemble of Φ-values, which are used as constraints in MD simulations starting from the fully fibrillar state. We find that the energy landscape differs substantially from the classical folding funnel in that only a small range of states allow entry to the pathway, accessed through a well-defined transition state ensemble (TSE). In this way, the amyloid free energy landscape more closely represents a golf course than a funnel . Our model converges findings of several experimental and computational studies , rationalizes the auto-catalytic nature of amyloids as well as fundamental experimental observations, such as most monomer-fibril end collisions being unsuccessful and how changes to the solution conditions or protein concentration may lead to saturated growth. Combined, our work provides a significant advance towards a mechanistic understanding of the protein aggregation reaction.