AI is transforming the global software industry, enabling developers to become more productive than ever before. Large engineering organizations must now adapt to leverage these opportunities and keep pace with this evolution .For engineering leaders, this transformation presents both opportunities and challenges. The shift to AI-assisted development requires thoughtful consideration to accelerate quality, productivity and collaboration.

As AI accelerates projects, we're likely to see a shift toward more product complexity and larger codebases rather than simply faster delivery. This is a pivotal moment for individual developers and organizations to share their experience going through this major paradigm shift.

Drawing from personal experience and Hinge Health's journey as a large React Native team, this talk presents practical strategies for managing the transition to AI-assisted development in a large engineering organization. We'll explore how AI is transforming our product development pipeline through changes in developer productivity and satisfaction, CI, technical writing, project planning, and tooling to handle growing codebase complexity.

Developers find themselves in a world where old maps no longer apply. The rules of software development have fundamentally shifted, and continue shifting at unprecedented speeds.

Drawing from a year of exploration, this talk reveals where AI truly shines - from rapid prototyping to uncovering what we didn't know we didn't know - and hidden dangers that can erode the very trust our software depends on.

Come discover the patterns emerging from this new reality: when to explore freely, when to be careful, and what opens up when the old constraints disappear.

What happens when you need to refactor 377 files in a SvelteKit codebase? Without AI, you retire. With Claude Code, you ship it in 11 hours.

This talk walks through real-world examples of using Claude Code for massive refactoring work that would be soul-crushing to do manually. I'll cover:

• How I approach large-scale refactors with Claude (377 files → 364 files → and counting)

• Building and activating Claude Code skills reliably (based on my viral post that's getting 4k+ views in 3 days)

• The workflow patterns that actually work vs the ones that waste your time

• Real examples from production codebases

This isn't about AI replacing developers - it's about using AI to handle the tedious parts so you can focus on the interesting problems.