The escalating complexity of modern System-on-Chip (SoC) designs challenges traditional RTL signoff, creating bottlenecks in design creation and RTL signoff. This tutorial introduces a transformative paradigm: applying Agentic AI to intelligently automate and optimize the entire design-to-signoff process, moving beyond static flows to a dynamic, intelligent ecosystem that’s capable of autonomous reasoning and adaptation; supporting engineers from initial concept and design exploration through final, comprehensive verification.

Central to this strategy is the novel Model Context Protocol (MCP), a standardized semantic communication layer that transforms IC design and verification tools into active, context-aware participants by exposing real-time design state, creation parameters, and tool capabilities. This enables a rich, shared understanding, allowing tools to publish critical information and respond intelligently, effectively merging design exploration and verification.

Leveraging MCP, platform-agnostic Agentic AI frameworks orchestrate complex tasks across design and verification domains. These agents are empowered to reason, plan, adapt, and execute strategies dynamically. They assist in design space exploration, architectural optimization, rapid iteration, identifying critical verification paths, generating targeted stimulus, intelligent debug, and root-cause analysis with minimal human intervention. This drives significant acceleration for design and verification closure, reducing cycle times and improving signoff quality.

The approach is engineer-centric, providing intuitive guidance to configure and deploy these advanced AI capabilities, fostering a collaborative human-AI partnership. This tutorial will detail the architectural principles behind this Agentic AI approach, demonstrating how MCP facilitates interoperability and enables autonomous, trusted RTL signoff. Attendees will gain insights into fostering design quality and liberating engineers from repetitive tasks.