Modern computing systems have reached unprecedented levels of complexity, rendering traditional design methodologies increasingly inadequate. As system architectures evolve toward greater specialization and heterogeneity, the challenge intensifies, particularly with the rise of domain-specific architectures that demand intricate optimization across multiple design parameters. This complexity explosion necessitates fundamentally new approaches to system design and optimization. Artificial intelligence agents have demonstrated transformative potential across diverse fields, from autonomous systems to scientific discovery, offering data-driven methodologies that can navigate complex decision spaces. These agents, powered by deep learning and reinforcement learning, have shown remarkable capabilities in domains requiring continuous adaptation and intelligent decision-making. The next frontier is to harness similar agent-based approaches for architectural design and optimization, potentially revolutionizing how we approach memory controller optimization, resource allocation, compiler tuning, and power management. While current ML-assisted architecture research has produced innovative algorithms and methods that enhance system efficiency through learned embeddings and automated design space exploration, the full potential of autonomous AI agents in system design remains largely untapped. As we stand at the threshold of "Architecture 2.0," a crucial question emerges: What foundational infrastructure must be established to enable AI agents to transform computer system design? This talk examines the essential building blocks for developing AI agent-assisted architecture research through a shared ecosystem. Such infrastructure would provide standardized environments for agent development, training datasets, and unified platforms for reproducible experimentation and comparative analysis. The talk presents a vision for collaborative ecosystem development that addresses the unique challenges of bringing AI agents to systems and architecture research. Through collective effort, we can establish the foundations to transform modern computer system design for the next generation of computing.