An applied systems lab focused on how people make constrained decisions in volatile environments.
GoodieYum is a living project that explores how real-world systems behave under pressure — when inputs are noisy, resources are limited, and decisions must be made without perfect information. The work here focuses on system design, decision structure, and governance: how constraints are shaped, how tradeoffs are managed, and how outcomes emerge from the interaction between people, processes, and tools.
The project spans multiple domains, including food systems, software, and information security operations. These are treated not as separate interests, but as different expressions of the same underlying problems: optimization under constraint, coordination across imperfect signals, and decision-making in environments that change faster than governance structures are often designed to handle.
Some work on GoodieYum takes the form of build logs and experiments, documenting systems as they are designed, tested, and refined. Other work takes the form of applied research, modeling how complex operational environments behave under stress and identifying where structural assumptions break down. Recipes, tools, diagrams, and papers are outputs of this process — not the focus themselves, but artifacts of system design in practice.
GoodieYum is intentionally iterative. Ideas are tested in public, revised over time, and grounded in real constraints rather than idealized scenarios. The goal is not polish for its own sake, but clarity: making complex systems legible, and designing structures that hold up when reality intrudes.
All work published on GoodieYum is the author’s own. The analysis, opinions, and conclusions expressed here are independent and do not represent the views of any employer, client, vendor, or affiliated organization.
About the Author
GoodieYum is authored by Jenny Moniz, whose work focuses on system design, security operations, and AI governance. Her background spans applied research and operational environments, with an emphasis on how governance, escalation, and decision boundaries shape outcomes in high-pressure systems.
This site documents independent work and ongoing experimentation. Content may evolve as systems are tested and refined.