$400 Fullstack Live Event Free With a Membership!
AI is no longer limited to chat interfaces or API calls to large language models. It is becoming embedded directly into applications, workflows, and user interfaces.
In this Fullstack Live Event, you will explore how to bring intelligence into real-world software beyond chatbots. From browser-based machine learning to reliable AI-generated UIs, you will learn how modern applications can become truly AI-driven without sacrificing performance, consistency, or maintainability.
When people think of AI today, they often think of chatbots and LLM APIs. But in many cases, intelligent behavior does not need the latency, cost, or complexity of large models in the cloud.
This session explores the “other side” of AI: efficient machine learning that runs directly in the browser or close to the application. You will see how real-time predictions, lightweight neural networks, and server-side inference can be integrated into production systems.
Through live examples, you will learn when to use JavaScript-native ML tools, when to rely on external models, and how to design AI features that are fast, practical, and production-ready using the tools you already know.
Explore how to run efficient machine learning directly in the browser and on the server without relying on large language models. You will see real-time predictions, lightweight neural networks, and server-side inference in action. Live demos in Node.js show how to integrate ML into production-ready applications using familiar JavaScript and Python tools.
Learn how to solve the challenges of AI-generated user interfaces, including inconsistency, styling issues, and maintainability problems. Discover how a parameterized, type-safe UI architecture enables predictable and scalable AI-powered interfaces. Based on real-world experience at Adobe, this session shows how to design robust systems instead of relying on unpredictable code generation.
how to integrate machine learning directly into browser-based and fullstack applications.
how to build fast and efficient AI features without relying on heavy LLM workflows.
how to design reliable, maintainable AI-generated user interfaces.
how to structure AI systems that are consistent, testable, and production-ready.
frontend and fullstack developers who want to integrate AI beyond chatbot use cases.
software engineers who want to understand browser-based machine learning and inference.
UI engineers and architects who want to design reliable AI-driven interfaces.
product and tech teams who want to build scalable AI features into real applications.
Laurie is a Senior Software Engineer specializing in intuitive fullstack solutions. With a background in cognitive psychology, she bridges the gap between technology and human behavior. She focuses on building user-friendly applications, accelerating development workflows, and mentoring the next generation of engineers through workshops and knowledge sharing.
Navya is a Senior Software Engineer at Adobe with a strong focus on frontend technologies and scalable web applications. She is an experienced conference speaker who regularly shares insights on GraphQL, DevTools, and modern web technologies. Passionate about clean UI architecture and great developer experience, she actively contributes to the tech community.