Within an event-driven, microservices architecture there's often a big gap between a web component that relies on some data, and the event data itself. There will usually be several services in the middle, from multiple APIs, databases, distributed caches etc. Building and updating that web component might mean touching many codebases and coordinating across many teams. This can be slow and hamper experimentation. What if... we bring that raw event data right into the browser, making it, in effect "event driven"? That web component can be developed and iterated on at lightning speed. New components can be built without the need for new endpoints. With access to the raw data, frontend developers suddenly have the freedom to explore new, bold ideas without fear of the upstream complexity.

Performant Architecture for a Fast Gen AI User Experience

More and more developers are being asked to build Generative AI experiences into their web applications everywhere. However, the user's experience with Generative AI can sometimes be slow and frustrating. It’s been years since we would gladly wait over 10 seconds for a response to anything online. As AI processing gets faster, there are new limiting factors that could be negatively affecting your AI user experience.

In this talk, we will cover different ways to minimise laggy experiences in web applications when interacting with third-party Generative AI tools. We’ll be using a practical demonstration to show how you can reduce latency as we build one of my favourite sci fi gadgets, the babel fish.