Welcome everyone. Uh my name is Mason Edgar. I work at Temporal and today we're going to talk about uh events are the wrong abstraction for your AI agents.So uh who here raise of hands recognizes what this diagram is out of curiosity. Okay. So this is a map of our solar system um in a geocentric projection. Uh this is where we have earth as the center of our solar system and this is how celestial objects move around the earth.And this was used to kind of calculate uh celestial trajectories prior to like the ...

Investment Rating - The report emphasizes the importance of application modernization through middleware transformation, indicating a positive outlook for investments in Event-Driven Architecture (EDA) and related technologies [5][6]. Core Insights - The report outlines that many enterprises aim to emulate the success of digitally native businesses, highlighting the necessity for IT transformation to enhance efficiency, scalability, and integration capabilities [4][5]. - EDA is presented as a revolutionary approach that enables real-time data exchange and improved scalability, making it essential for modern applications [6][9]. Summary by Sections Overview of Modern Event-Driven Architecture (EDA) - EDA promotes loosely coupled, asynchronous communication, enhancing system responsiveness and scalability compared to traditional architectures [9][13]. - Key components of EDA include event producers, brokers, and consumers, which work together to facilitate real-time processing [10][11][19]. Benefits of EDA in Modern Applications - EDA enhances responsiveness, allowing for immediate reactions to events, which is crucial for applications like fraud detection and real-time analytics [30]. - Scalability is achieved through the decoupling of services, enabling independent scaling based on demand, particularly beneficial during high-traffic events [30][31]. Real-World Examples of EDA Implementations - Companies like Netflix utilize EDA to manage microservices, enhancing user experience through real-time event tracking [33]. - Uber employs EDA for real-time ride requests and dynamic pricing, allowing efficient matching of riders and drivers [35]. - Amazon leverages EDA for order processing and inventory management, ensuring smooth operations through event-triggered actions [37]. Data Mesh and AI Adoption - Data Mesh decentralizes data ownership, allowing business domains to manage their data as products, enhancing accessibility and reliability [42][44]. - EDA supports AI adoption by ensuring comprehensive data logging, which is essential for training AI models and enabling real-time decision-making [48][55]. Conclusion - The integration of EDA, Data Mesh, and AI-driven intelligence is crucial for enterprises to achieve scalability, agility, and real-time decision-making in a competitive digital landscape [57][58].