Design

Analyzing post-launch UX metrics inside-the-design-workflow

Connect Claude to Amplitude dashboards to ask structured questions about adoption, retention, segment differences, and trends without context switching, tying analytics back to design decisions during post-launch iteration.

Why the human is still essential here

A human must interpret causality, consider confounds, and decide what changes to make; AI helps surface patterns and summarize metrics faster.

How people use this

Funnel drop-off diagnosis by segment

Query analytics to compare where specific cohorts drop in a funnel and get a concise explanation of likely UX friction points to investigate.

Amplitude / Claude

Retention analysis with plain-language readout

Ask AI to summarize week-over-week retention changes and highlight which behaviors correlate with improved retention for a redesign hypothesis.

Mixpanel / ChatGPT

Feature adoption trend monitoring

Generate a weekly narrative summary of adoption, activation, and key events and link takeaways back to recent UI changes and releases.

Google Analytics 4 / ChatGPT

Community stories (1)

Medium

7 min read

How I Use AI to Scale Design Impact

AI didn’t change what I design. It changed how I design.

Over the past several months, my design process hasn’t just evolved — it’s been fully restructured. My AI tool stack isn’t something I use occasionally; it is an operational layer embedded into my day-to-day and across discovery, ideation, prototyping, validation, and delivery.

This article outlines how I structure projects using AI models — primarily Claude and ChatGPT — alongside specialized tools such as Figma Make and Amplitude.

Yuliia GalytskaProduct designer

Feb 27, 2026