Generative AI agents are transforming business operations by autonomously managing tasks such as customer service and logistics, but their effectiveness is heavily dependent on having real-time information. The delay between actual events and an agent's awareness, known as the "context gap," can degrade the quality of decisions when relying on outdated data. A scenario involving an airline's AI agent illustrates the pitfalls of acting on stale information, which resulted in unsuccessful customer service. By contrast, using a real-time context engine allows the agent to make swift and informed decisions, transforming a potentially negative customer experience into a positive one. The key to overcoming the context gap lies in adopting continuous stream processing architectures that provide fresh data, enabling AI agents to perceive the world as it is, in real-time. Platforms like DeltaStream are making it easier for developers to integrate real-time data into AI systems, thus empowering the next generation of intelligent, context-aware automation.