This research introduces a Large Language Model (LLM)-based agent that automates transistor sizing for analog and mixed-signal circuits, traditionally a manual, expertise-dependent process.

• Reduces the need for manual circuit design through automated reasoning
• Leverages LLMs' knowledge of electronic principles to suggest optimal component values
• Demonstrates practical application in sizing operational amplifiers (op-amps)
• Represents a significant step toward AI-assisted electronic design automation

This innovation matters because it addresses a major bottleneck in integrated circuit development, potentially shortening design cycles and reducing reliance on specialized expertise in electronics manufacturing.

LLM-based AI Agent for Sizing of Analog and Mixed Signal Circuit