The Constraint Your LLM Will Quietly Ignore (with Gurobi's Jerry Yurchisin)
Jerry Yurchisin from Gurobi Optimization explains mathematical optimization as an AI technology where constraints are hard guarantees, unlike LLMs which may ignore critical constraints. He outlines the three core building blocks of any optimization model: decision variables, constraints, and an objective function. The discussion highlights where optimization fits in the agentic AI era, with agents framing problems and generating code, then handing off to solvers like Gurobi via MCP servers. Jerry also covers advancements in non-linear solving, strategies for pitching optimization to stakeholders, and diverse case studies including energy grids, retirement planning, and USA Cycling's Paris 2024 gold medal.
