Memory is usually where agentic systems go to become expensive. That is not the glamorous failure mode. It is not the cinematic robot rebellion, nor the slightly more realistic spreadsheet full of hallucinated invoices. It is quieter: an LLM agent keeps improving a program, stores previous attempts, retrieves a few “good” ones, and then spends half its context window rereading code scaffolding that no longer explains anything useful. ...
A supply chain rarely fails because one objective was neglected in a spreadsheet. It fails because the spreadsheet quietly pretended the objective would stay still. Yesterday the priority was margin. Today it is carbon exposure. Tomorrow a route becomes expensive, a supplier becomes unreliable, demand arrives in a pattern that looks suspiciously like a sine wave wearing a hard hat, and the “optimal” plan starts ageing like milk. ...
TL;DR for operators Optimization work usually looks technical from the outside: equations, solvers, constraints, tolerances, and someone quietly muttering about convergence. Inside the business, the real bottleneck is often less glamorous. Someone has to decide what the problem actually is, how to formulate it, which algorithm to try, which hyperparameters to tune, and whether the resulting answer is useful or merely mathematically decorative. ...