In this talk, I will share several research progress in mixed-integer optimization (MIO) that may influence the next generation MIO solvers. The first topic is a comparison between Google’s AlphaEvolve framework and the classical modeling–optimization pipeline. The second topic concerns GPU-accelerations for within MIP solvers. The third topic builds on the relationship between cutting planes, surrogate model, and enumeration. We explored the integration of the Fenchel-cut framework into SCIP solver, which was also named as local cuts in TSP context. Our preliminary results suggest that Fenchel cuts can be stronger than mixed-integer rounding cuts, although their generation is computationally expensive. These findings raise further theoretical questions, particularly regarding how to break the “single-row barrier” that underlies most modern cutting-plane systems.