Think Like a Tester: What to Look For in AI-Generated Code

The testing pyramid - the canonical shape of tests that defined what types of tests we need to write to make sure the app works - is ... obsolete. In this presentation, Roman Sandler and Gleb Bahmutov argue what the testing shape works better for today's web applications.

React Testing Library is a great framework for React component tests because there are a lot of questions it answers for you, so you don’t need to worry about those questions. But that doesn’t mean testing is easy. There are still a lot of questions you have to figure out for yourself: How many component tests should you write vs end-to-end tests or lower-level unit tests? How can you test a certain line of code that is tricky to test? And what in the world are you supposed to do about that persistent act() warning?
In this three-hour workshop we’ll introduce React Testing Library along with a mental model for how to think about designing your component tests. This mental model will help you see how to test each bit of logic, whether or not to mock dependencies, and will help improve the design of your components. You’ll walk away with the tools, techniques, and principles you need to implement low-cost, high-value component tests.
Table of contents- The different kinds of React application tests, and where component tests fit in- A mental model for thinking about the inputs and outputs of the components you test- Options for selecting DOM elements to verify and interact with them- The value of mocks and why they shouldn’t be avoided- The challenges with asynchrony in RTL tests and how to handle them
Prerequisites- Familiarity with building applications with React- Basic experience writing automated tests with Jest or another unit testing framework- You do not need any experience with React Testing Library- Machine setup: Node LTS, Yarn

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.

Knowledge of AI tooling is critical for future-proofing the careers of React developers, and the Vercel suite of AI tools is an approachable on-ramp. In this course, we’ll take a closer look at the Vercel AI SDK and how this can help React developers build streaming interfaces with JavaScript and Next.js. We’ll also incorporate additional 3rd party APIs to build and deploy a music visualization app.
Topics:- Creating a React Project with Next.js- Choosing a LLM- Customizing Streaming Interfaces- Building Routes- Creating and Generating Components - Using Hooks (useChat, useCompletion, useActions, etc)

In this workshop I’ll cover a repeatable process on how to spin up full stack apps in Cursor.  Expect to understand techniques such as using GPT to create product requirements, database schemas, roadmaps and using those in notes to generate checklists to guide app development.  We will dive further in on how to fix hallucinations/ errors that occur, useful prompts to make your app look and feel modern, approaches to get every layer wired up and more!  By the end expect to be able to run your own AI generated full stack app on your machine!
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The way we write code is fundamentally changing. Instead of getting stuck in nested loops and implementation details, imagine focusing purely on architecture and creative problem-solving while your AI pair programmer handles the execution. In this hands-on workshop, I'll show you how to leverage Cline (an autonomous coding agent that recently hit 1M VS Code downloads) to dramatically accelerate your development workflow through a practice we call "vibe coding" - where humans focus on high-level thinking and AI handles the implementation.You'll discover:The fundamental principles of "vibe coding" and how it differs from traditional developmentHow to architect solutions at a high level and have AI implement them accuratelyLive demo: Building a production-grade caching system in Go that saved us $500/weekTechniques for using AI to understand complex codebases in minutes instead of hoursBest practices for prompting AI agents to get exactly the code you wantCommon pitfalls to avoid when working with AI coding assistantsStrategies for using AI to accelerate learning and reduce dependency on senior engineersHow to effectively combine human creativity with AI implementation capabilitiesWhether you're a junior developer looking to accelerate your learning or a senior engineer wanting to optimize your workflow, you'll leave this workshop with practical experience in AI-assisted development that you can immediately apply to your projects. Through live coding demos and hands-on exercises, you'll learn how to leverage Cline to write better code faster while focusing on what matters - solving real problems.

A comprehensive workshop designed specifically for React developers ready to become AI engineers. Learn how your existing React skills—component thinking, state management, effect handling, and performance optimization—directly translate to building sophisticated AI applications. We'll cover the full stack: AI API integration, streaming responses, error handling, state persistence with Supabase, and deployment with Vercel.Skills Translation:- Component lifecycle → AI conversation lifecycle- State management → AI context and memory management- Effect handling → AI response streaming and side effects- Performance optimization → AI caching and request optimization- Testing patterns → AI interaction testing strategiesWhat you'll build: A complete AI-powered project management tool showcasing enterprise-level AI integration patterns.