Will be talking about a new set of tools for inference after model selection. The highlight will be doing inference along steps of the forward stepwise, least angle regression, and lasso paths, though the framework for inference is applicable well beyond these cases, and other problems will be briefly discussed as well. If time permits, I will also discuss some asymptotic results about the robustness of the proposed tests to non-Gaussian noise distributions.