Imagine an AI that could read complex engineering documents and automatically design circuits based on the information it finds. That's the vision behind DocEDA, a revolutionary new system that's poised to transform electronic design automation. Designing analog circuits is a notoriously complex and time-consuming process, often requiring engineers to painstakingly extract parameters from datasheets and technical documents. This manual approach is not only slow but also prone to human error. DocEDA tackles this challenge head-on by leveraging the power of Large Language Models (LLMs) and computer vision. It works by first analyzing the layout of a document, identifying key sections like component parameters, circuit diagrams, and performance curves. Then, using the chain-of-thought reasoning abilities of LLMs, DocEDA extracts crucial parameters from these sections, even deciphering complex tables and textual descriptions. What's truly remarkable is how DocEDA handles circuit diagrams. It uses an enhanced computer vision model called GAM-YOLO to identify components and their connections, effectively converting images into circuit netlists—the standard format for circuit simulation software. Finally, DocEDA doesn’t stop at extraction; it optimizes the circuit layout for performance using a technique called Implicit Space Mapping. This intelligent optimization process significantly reduces the reliance on time-consuming simulations, leading to faster design cycles. DocEDA's potential impact on the electronics industry is immense. By automating tedious and error-prone tasks, engineers can focus on higher-level design considerations, accelerating innovation and bringing new products to market faster. While still in its early stages, DocEDA points to a future where AI plays a central role in streamlining the entire hardware design process, from concept to silicon.