Agentic AI: Why Experience Matters More Than Hype
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Agentic AI systems are fundamentally distributed systems that require production-hardened infrastructure to succeed. While the market shows significant hype with high valuations and low revenue multiples, 95% of AI projects are failing due to infrastructure engineering challenges rather than lack of imagination. These systems introduce new complexity layers including stochastic components, specialized GPU infrastructure, long-lived workflows, and side-effecting actions. Building reliable agentic systems requires experience with durability, observability, backpressure, and fault tolerance - lessons learned from 15 years of distributed systems development at scale.
