What does it mean?
AI makes building small agent workflows easier, but repeated additions can create hidden dependencies among prompts, tools, and integrations. The source compares these patchwork systems to a 'big ball of mud' in software engineering. The result may work briefly while becoming harder to maintain.
Make it concrete.
Imagine an expense agent that expands from parsing invoices to emailing managers, updating sheets, and triggering approvals. A small change unexpectedly breaks reporting because no one tracked the dependencies.
A common mistake.
Treating fast prototyping as proof the resulting system is maintainable.
When should you use it?
When a simple automation acquires multiple tools, permissions, triggers, and handoffs.
Why keep this thought?
Keeping dependencies visible prevents a useful prototype from turning brittle.
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.