Scaling a11y

In this workshop, we discuss the merits of serverless architecture and how it can be applied to the AI space. We'll explore options around building serverless RAG applications for a more lambda-esque approach to AI. Next, we'll get hands on and build a sample CRUD app that allows you to store information and query it using an LLM with Workers AI, Vectorize, D1, and Cloudflare Workers.

Next.js is a compelling framework that makes many tasks effortless by providing many out-of-the-box solutions. But as soon as our app needs to scale, it is essential to maintain high performance without compromising maintenance and server costs. In this workshop, we will see how to analyze Next.js performances, resources usage, how to scale it, and how to make the right decisions while writing the application architecture.

In this workshop, we'll take a tour through the most effective approaches to building out scalable UI components that enhance developer productivity and happiness :-) This will involve a mix of hands-on exercises and presentations, covering the more advanced aspects of the popular styled-components library, including theming and implementing styled-system utilities via style props for rapid UI development, and culminating in how you can build up your own scalable custom component library.
We will focus on both the ideal scenario---where you work on a greenfield project---along with tactics to incrementally adopt a design system and modern approaches to styling in an existing legacy codebase with some tech debt (often the case!). By the end of the workshop, you should feel that you have an understanding of the tradeoffs between different approaches and feel confident to start implementing the options available to move towards using a design system based component library in the codebase you work on.
Prerequisites: - Familiarity with and experience working on large react codebases- A good understanding of common approaches to styling in React