Webflow Innovation & Technology Culture

What types of products or services does your engineering team work on/create? What problem are you solving for customers?

We’re building an AI-native web experience platform, one that lets cross-functional teams of marketers, designers and developers visually build, manage and optimize enterprise-grade websites — without hand-coding every detail. Traditionally, a designer creates something in Figma, then an engineer rebuilds that design from scratch in code. That handoff is slow, expensive and full of “this doesn’t look like the mockup” moments. 

Webflow eliminates that gap. It gives designers and marketers direct control of the web so they can design, build and publish sites themselves, while still maintaining the quality and flexibility engineers expect. When you do need custom logic or integrations, developers can extend the platform with code or APIs, so it scales with your business, not around it. In short, Webflow helps teams ship well-designed, enterprise-grade custom websites fast — without waiting on a dev queue. It’s visual, collaborative and built for flexibility.

Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?

I lead our developer productivity team, which keeps our platform fast, modern and reliable. That means constantly upgrading our tech stack across many interdependent services without disrupting what 300,000 customers rely on daily. These platform upgrades are notoriously complex; they touch nearly every part of the codebase and have historically taken weeks of manual effort to execute safely. To move faster, we treated AI as an active collaborator, not just a code-generation tool. We use a mix of AI-powered pair-programming tools and integrated development environments, including Cursor, Augment Code, Claude Code and OpenAI Codex, to generate codemods, detect errors and refactor legacy patterns. Engineers pick whichever tool fits their needs; some prefer Augment Code in-context code understanding for large-scale refactors, while others like Claude Code’s reasoning capabilities to interpret errors and recommend safe transformations. 

AI helped map dependencies early, flag risks and cluster related migration tasks so we could parallelize the work across teams. What used to be a slow, error-prone upgrade cycle is now a coordinated semi-automated flow with engineers in the driver’s seat, where AI is doing the heavy lifting. 

What would that project have looked like if you didn’t have AI as a tool to use? How has AI changed the way you work, in general?

Without AI, this kind of platform upgrade would’ve stretched across multiple quarters — a slow, manual process of dependency mapping, repetitive code updates and endless test cycles. Every small API change in React or Node needed custom scripts and manual reviews. Reliable, yes. Scalable? Not really.

With AI in the mix, we compressed that cycle dramatically. Instead of writing migration scripts from scratch, engineers could prompt AI tools to propose code transformations, validate patterns, spot edge cases and even generate test coverage. The result wasn’t just speed; it was consistency. Teams could move in sync, applying shared migration patterns across the entire codebase and reducing regressions.

AI has reshaped how we approach platform evolution at Webflow. Upgrades aren’t big, disruptive events anymore; they’re continuous, incremental improvements. Engineers have the freedom to experiment with the AI tools that best fit their workflow. And we’re always exploring what’s next — not for novelty, but for how it amplifies creativity, safety and speed. AI has become our quiet partner in keeping Webflow modern, stable and fast.