Thanks to AI, designers and PMs are now prototyping and deploying faster than ever, sometimes without writing a single line of code. Tools like Lovable, Bolt and others can generate entire applications directly from prompts, while design tools are blurring the lines between mockups and implementation. So where does that leave React engineers?

As AI tools become UI builders, one trend is clear: React is becoming their default output. It's quickly turning into the universal framework of AI, putting React developers at risk of seeing their core skills commoditized.

In a world where AI can generate impressive UIs and ship entire components from a single prompt, it's tempting to declare the death of frontend engineering.

But what if we're just looking at it wrong?

The pixel-pushing days may be over, but the complexity is just shifting layers. Welcome to the age of the back of the frontend. This talk explores how AI is fragmenting the frontend into fast, flashy outputs and deeply nuanced logic, and why the real value now lies beneath the surface.

We'll break down what's actually being automated (spoiler: it's not the hard stuff), the logic, flows, edge cases, performance, that's still on us. We'll examine where human acuity still matters, why knowing when not to use AI might be your new superpower, and how the integration of AI-generated React components into complex, multi-framework applications creates new engineering challenges.

This talk doesn't shy away from the uncomfortable question: what is your job when everyone can "build"?

If you're a frontend dev wondering whether you still have a job, you do. But it may not look the same as the one you trained for. The new frontier isn't just building components, but designing the systems that allow AI-generated components to function in the beautiful complexity of production applications.

Toss, South Korea’s leading fintech app, runs 40+ micro React Native apps inside a brownfield super-app with 20+ daily deployments. We’ll share how we customized the bundling pipeline—replacing Metro with esbuild and enabling dynamic multi-bundle loading—to achieve sub-10s builds, sub-200KB bundles, and scalable React Native deployments at scale.

In this session, I’ll explore how AI-powered tooling is transforming large-scale refactoring and codebase migrations, making these complex tasks faster and more efficient. By leveraging tools like Large Language Models (LLMs), static analysis, and refactoring frameworks, we can automate repetitive code transformations, accelerate migration paths, and reduce human error. I’ll share practical examples of how we can migrate legacy systems to modern frameworks, break monolithic architectures into service-based structures, and automate large-scale code changes across thousands of files.

I’ll demonstrate how tools like OpenAI Codex, GitHub Copilot, and fine-tuned models for domain-specific transformations can assist in these processes, while still integrating with traditional migration tools and CI/CD systems. I’ll also cover the importance of developer oversight, highlighting lessons learned from real-world production rollouts and how to balance automation with manual reviews.

By the end of the talk, I want attendees to walk away with a clear understanding of how to use AI to enhance their refactoring and migration workflows, ensuring they can handle large-scale transformations while maintaining code quality, consistency, and governance.

Stay ahead of the curve with the latest updates and upcoming improvements in Expo and React Native. What’s changing, what’s new, and why React Native remains a great investment after a decade.