We build agentic AI systems the way Victor Frankenstein built his creature: stitching together parts that each work well in isolation \u2014 a language model here, a tool-calling framework there, a vector database, a scheduler, a handful of subagents \u2014 and animating the whole thing with just enough orchestration logic to make it move. Then we’re surprised when it develops a mind of its own.<\/p>\n\n\n\n
Most “agentic AI Frankensteins” aren’t the result of one bad decision. They’re the accumulation of many reasonable ones:<\/p>\n\n\n\n
A single model that hallucinates is a nuisance. A chain of agents that hand off tasks, retry on failure, and take real-world actions (sending messages, spending money, modifying infrastructure) can turn a small mistake into a cascading one \u2014 especially when the failure mode wasn’t anticipated by any single component’s designer.<\/p>\n\n\n\n
The lesson from Shelley’s novel was never “don’t build anything ambitious.” It was that ambition without responsibility for the whole creation is where things go wrong. The same is true for agentic AI: the risk isn’t in connecting powerful components together \u2014 it’s in doing so without anyone accountable for the creature that results.<\/p>\n\n\n\n