Mathematical optimization

Sep 04, 2026

In Case You Missed It in August 2026 (Ep. 1024 with Jon Krohn)

This episode explores the critical gap between AI investment and return, featuring insights from industry leaders. It covers why most organizations fail to see ROI from AI, the crucial role of mathematical optimization in agentic AI to ensure constraint adherence, practical strategies for structuring AI skills in tools like Claude for quality output, and a 10-20-70 budget framework emphasizing upskilling. Additionally, it delves into the growing importance of the semantic layer for analytics agents to ensure consistent data interpretation and efficiency in large enterprises.

Aug 04, 2026

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.

Oct 14, 2025

931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin

Gurobi's Jerry Yurchisin explains the power of mathematical optimization, a prescriptive approach that complements AI's predictive capabilities. This summary covers how to get started with free resources, the use of GPUs and LLMs to enhance optimization, real-world applications at companies like Toyota, and its relationship with quantum computing.