DevEx & Frontends at QCon San Francisco 2025

How does Netflix maintain a seamless viewing experience for millions of users, especially during traffic spikes or when backend datastores are overloaded? Autoscaling can help during traffic spikes, but it costs money, takes a few minutes to kick in, and capacity may not always be available.

Claude Code is the first developer tool built specifically to maximize AI development velocity.

Front-end has long been about reactivity frameworks and client-side state management. However, the alpha in these is receding.

Meta’s internal tools empower the company to operate efficiently, enabling the creation of unique, tailored solutions that fit evolving business needs.

Expanding the market of your VR game to other platforms may seem like an easy way to increase your revenues but the journey is all but simple. When what makes your game unique is the presence and immersion it provides, reproducing the experience on a flat screen is a daunting task.

Solopreneur & Sustainable Business don't often go together, but that's what can happen when you create something "Good Enough" and hang around "Long Enough". Joe, a true Unicorn in the volatile games business, has survived for 16+ years by creating 19 games in his Clutter Franchise.

Delivering AI-powered features in mobile apps is not just about calling an LLM API. It's about crafting fast, reliable, and engaging user experiences.

Uber Eats has many surfaces developed using native-first design. Historically these were built on the Android and iOS stacks. To accelerate development and enable rapid iteration and experimentation, while preserving the native-first design, a webview-powered stack was developed.

The AI coding agent landscape evolves weekly. This talk compares today’s frontrunners, shows where each shines, and shares prompts, policies, and “rules templates” that turn code suggestions into production-quality output.

In this session you'll learn how product leaders turn GenAI enthusiasm into an enterprise-ready blueprint for real productivity gains.

As AI accelerates delivery, new attack surfaces and compliance risks emerge. This session distills best practices for threat-modeling AI pipelines, guarding sensitive data, detecting prompt-injection, and validating AI-generated code before it merges.