Imagine a world where AI assistants manage the health of our bridges, predicting potential problems before they become disasters. That's the promise of a new wave of research exploring the use of Large Language Model (LLM)-based agents in bridge operation and maintenance. Traditionally, bridge maintenance has relied on manual inspections and scheduled tests, a process that can be slow, costly, and sometimes miss critical warning signs. This new research proposes a revolutionary approach: equipping bridges with their own AI assistants. These LLM-powered agents can analyze vast amounts of data from sensors, drones, and historical records to paint a comprehensive picture of a bridge's health. They can predict potential issues like cracks, corrosion, or structural weaknesses, and even suggest optimal maintenance strategies. This shift towards AI-driven maintenance could dramatically improve efficiency, reduce costs, and most importantly, enhance safety. By catching problems early, we can prevent catastrophic failures and ensure the long-term health of our vital infrastructure. While the technology is still developing, the potential impact on bridge management and public safety is immense. The challenges ahead lie in integrating complex engineering knowledge into these AI systems and addressing the ethical considerations of entrusting critical infrastructure to autonomous agents. But the possibilities are clear: a future where AI helps us build and maintain safer, more resilient bridges for everyone.