Explore recent developments in selective inference through this tutorial from the Adaptive Data Analysis Workshop. Delve into advanced topics including Gaussian randomization schemes, randomized conditional approaches, and the Polyhedral Lemma. Examine computational challenges in randomized inference, full model and target concepts, and the randomized selective law. Learn about approximate reference techniques, confidence intervals, and selective maximum likelihood estimation. Investigate marginal screening of eGenes, validity of inference, power analysis, and point estimation comparisons. Conclude by revisiting LASSO and its data generative scheme. Gain insights from Snigdha Panigrahi's expertise in this comprehensive exploration of cutting-edge selective inference methodologies.