Onboarding friction was one of the biggest drivers of drop-off across GoDaddy’s experiences. Customer knew they wanted to build a website or grow their business, but the blank page often stopped them before they made progress.
At the same time, generative AI was proving effective at idea generation and content creation. GoDaddy also had a broad portfolio of products and customer data to learn from, creating an opportunity to apply AI in a practical, customer-facing way. Speed mattered. The market was moving quickly, and waiting meant falling behind.
The real question was whether AI could meaningfully help customers move forward faster without creating confusion, distrust, or low-quality results.
We needed to understand:
Could AI perform reliably at the scale GoDaddy required?
Was the output genuinely useful, not just impressive?
Would customers trust and enjoy interacting with it?
Could it measurably improve onboarding and engagement?
If the answer to any of these was no, it wasn’t worth shipping.
I helped lead the design effort across this initiative, working closely with product and engineering partners across more than ten teams.
My focus was on:
Shaping the problem and defining what “good” looked like
Assembling a multi-disciplinary design team across UX, content, and UX engineering
Establishing a single source of truth in Figma to support rapid iteration
Keeping the team focused on learning and validation rather than polish
This work sat squarely between strategy and execution.
We prioritized learning over polish
We focused first on interaction patterns and feedback loops. Branding and visual identity came later, once we validated that the experience worked.
We optimized for speed, not completeness
Roughly six months of roadmap was executed in six weeks, with design completed in about four. This required daily communication, frequent demos, and comfort with changing scope.
We designed for trust, not magic
Early testing showed customers were afraid of losing work when interacting with AI. We introduced non-destructive patterns so exploration felt safe and reversible.
We planned for imperfect output
AI doesn’t always produce good results. We designed clear recovery paths so customers weren’t stuck or confused when the output missed the mark.
This pace and mode of working was effective for discovery, but not sustainable long term.
The impact was immediate and measurable.
Customer interaction and engagement increased by removing the blank-page problem
AI doubled the number of customers successfully onboarding into GoDaddy
The work established a first-mover advantage and enabled rapid iteration
The initiative evolved into Airo, now a broader suite of AI-powered tools with a dedicated team
The release materially shifted market perception of GoDaddy’s products and capabilities
This work demonstrated how emerging technology, paired with disciplined design leadership, can translate into real customer and business value under tight constraints.
This project showed that AI could be applied in a practical, human way to solve a real customer problem. More importantly, it demonstrated how design leadership, tight collaboration, and disciplined decision-making can turn emerging technology into shipped value under real constraints.