We Specified an AI Agent in 2016. We Called It Analytics.

A 2016 IBM patent for real-time concert feedback is re-examined as an early blueprint for an AI agent. The system was designed as a sense-think-act loop, using multimodal perception from instrument sensors, audience cameras, and user ratings to generate insights. Its 'analytics engine' grounded inferences in both historical performance data (episodic memory) and a domain knowledge base (semantic memory), mirroring modern agent architectures. The author reflects that while the system's architecture was structurally sound, its reasoning component was weak, a problem inverted by today's powerful but often poorly architected foundation models.