Convex geometry has provided some of the most powerful and general tools for efficient algorithms. In this talk, we discuss developments in algorithmic convex geometry under 5 different general problems --- sampling, optimization, integration, rounding and learning (SOIRL, pronounced SWIRL) --- and their interplay with isoperimetric and probabilistic inequalities. We will highlight several open problems and conjectures on the way.