From a technical bottom-up perspective, the core essence of an Agent is essentially a set of if-else logic, context switching, and thread switching. What does this imply?

Digging deeper, the entire AI narrative is quietly shifting its focus back to one place—CPU.

Why is that? Because these seemingly intelligent Agents, no matter how optimized, ultimately rely on chip computing power to execute. Context switching requires rapid CPU scheduling, and thread parallelism depends on multi-core architectures. These are not issues that GPT can solve.

Looking at it this way, the key players in the chip industry—AMD, Intel, and ARM—actually become the real beneficiaries. Whether their CPU architectures can efficiently handle complex parallel computations and frequent context switches directly determines the practical implementation efficiency of the Agent ecosystem.

Interestingly, the market still hasn't fully realized this layer.