What does it mean?
Piecemeal AI systems can become fragile when nobody has a reliable understanding of how their pieces interact. The practical response is not always another patch. Mapping dependencies and simplifying responsibilities can be more effective than layering new prompts over old assumptions.
Make it concrete.
Imagine a support agent whose routing rules have been patched dozens of times. Before adding another exception, the team maps the workflow and removes redundant handoffs.
A common mistake.
Adding fixes indefinitely without checking whether the underlying workflow still makes sense.
When should you use it?
When recurring failures, confusing dependencies, or maintenance effort outweigh the automation's savings.
Why keep this thought?
Simpler systems are easier to explain, debug, and evolve.
Explore the source.
Nielsen Norman Group — The New Big Ball of Mud: Why Agentic AI Systems Turn Fragile ↗An editorial interpretation of the linked source, not a direct quotation or endorsement.