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YieldArch-AI: Meta-Cognitive Yield Optimization for Semiconductor Fabrication

YieldArch-AI: Meta-Cognitive Yield Optimization for Semiconductor Fabrication

via Dev.to PythonAniket Hingane

How I built a Meta-Cognitive Agent that Dynamically Adjusts Reasoning Depth for Real-Time Semiconductor Yield Analysis. TL;DR I developed YieldArch-AI, an experimental meta-cognitive agent for semiconductor manufacturing. The agent dynamically adjusts its reasoning depth between shallow heuristics and deep root cause analysis. This approach reduced operational latency and token costs by 60% in my experiments. I used LangGraph for stateful orchestration and simulated complex fabrication anomalies. The project demonstrates the power of "thinking about thinking" in industrial AI applications. Introduction From my experience in the tech industry, we often talk about AI agents as if they are monolithic solvers—entities that receive a prompt and output a solution. But in my opinion, this is a dangerous oversimplification, especially when you step into the high-stakes world of semiconductor fabrication. In my view, the real challenge isn't just "reasoning," but rather "deciding how much to re

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