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Gamma’s head of design on using AI to synthesize feedback and generate on-brand imagery | Zach Leach

Zach Leach, head of design at Gamma, reveals how his small team uses AI to analyze global feedback, create on-brand imagery, and maintain design quality while serving users in more than 60 countries. *What you’ll learn:* 1. How Gamma analyzes feedback from their 60% international user base using ChatGPT’s deep research capabilities 2. How to transform hundreds of multilingual feedback items into actionable design insights 3. A simple workflow for creating on-brand imagery using Midjourney-style references 4. How to use AI to maintain brand consistency across a globally distributed product 5. The secret to removing image backgrounds instantly using Replicate 6. How to create consistent, high-quality job descriptions in minutes using AI templates *Brought to you by:* WorkOS—Make your app enterprise-ready today: https://workos.com?utm_source=lennys_howiai&utm_medium=podcast&utm_campaign=q22025 Retool—AI that’s designed for developers and built for the enterprise: https://retool.com/howiai *Where to find Zach Leach:* LinkedIn: https://www.linkedin.com/in/zleach X: https://x.com/thisiszach *Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo *In this episode, we cover:* (00:00) Intro (02:42) Building the Gamma AI image editing feature (05:25) Using ChatGPT’s deep research for feedback analysis (09:10) How feedback was analyzed before AI tools (10:10) Benefits of deep research vs. basic scripting (12:40) Insights from ChatGPT's deep research (16:41) Demo of Midjourney workflow for creating on-brand art (23:54) Using Replicate for background removal (25:40) Style references (SREF) and brand consistency in Midjourney (29:19) An AI workflow for creating consistent job descriptions (32:27) Conclusion and final thoughts *ChatGPT feedback prompt:* “This is some feedback we’ve received about our AI image editing feature. I want you to analyze the feedback and find where we are doing poorly and where we are doing well. Break down for our product team what kinds of things we are doing well and why, and what kinds of things we are doing poorly and why. What do people love? What do people hate? Where can we improve?” *Tools referenced:* • Gamma: https://gamma.app/ • ChatGPT: https://chat.openai.com/ • Midjourney: https://www.midjourney.com/ • Midjourney Style Reference (SREF): https://docs.midjourney.com/hc/en-us/articles/32180011136653-Style-Reference • Replicate: https://replicate.com/ • Figma: https://www.figma.com/ • Claude Projects: https://claude.ai/projects • GPT 4o image model https://openai.com/index/introducing-4o-image-generation/ *Other reference:* • LaunchDarkly: https://launchdarkly.com/ _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

Claire VohostZach Leachguest
Jun 9, 202536mWatch on YouTube ↗

Episode Details

EPISODE INFO

Released
June 9, 2025
Duration
36m
Channel
How I AI
Watch on YouTube
▶ Open ↗

EPISODE DESCRIPTION

Zach Leach, head of design at Gamma, reveals how his small team uses AI to analyze global feedback, create on-brand imagery, and maintain design quality while serving users in more than 60 countries. *What you’ll learn:*

  1. How Gamma analyzes feedback from their 60% international user base using ChatGPT’s deep research capabilities
  2. How to transform hundreds of multilingual feedback items into actionable design insights
  3. A simple workflow for creating on-brand imagery using Midjourney-style references
  4. How to use AI to maintain brand consistency across a globally distributed product
  5. The secret to removing image backgrounds instantly using Replicate
  6. How to create consistent, high-quality job descriptions in minutes using AI templates

*Brought to you by:* WorkOS—Make your app enterprise-ready today: https://workos.com?utm_source=lennys_howiai&utm_medium=podcast&utm_campaign=q22025 Retool—AI that’s designed for developers and built for the enterprise: https://retool.com/howiai *Where to find Zach Leach:* LinkedIn: https://www.linkedin.com/in/zleach X: https://x.com/thisiszach *Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo *In this episode, we cover:* (00:00) Intro (02:42) Building the Gamma AI image editing feature (05:25) Using ChatGPT’s deep research for feedback analysis (09:10) How feedback was analyzed before AI tools (10:10) Benefits of deep research vs. basic scripting (12:40) Insights from ChatGPT's deep research (16:41) Demo of Midjourney workflow for creating on-brand art (23:54) Using Replicate for background removal (25:40) Style references (SREF) and brand consistency in Midjourney (29:19) An AI workflow for creating consistent job descriptions (32:27) Conclusion and final thoughts *ChatGPT feedback prompt:* “This is some feedback we’ve received about our AI image editing feature. I want you to analyze the feedback and find where we are doing poorly and where we are doing well. Break down for our product team what kinds of things we are doing well and why, and what kinds of things we are doing poorly and why. What do people love? What do people hate? Where can we improve?” *Tools referenced:*

*Other reference:*

• LaunchDarkly: https://launchdarkly.com/ _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

SPEAKERS

  • Claire Vo

    host
  • Zach Leach

    guest

EPISODE SUMMARY

In this episode of How I AI, featuring Claire Vo and Zach Leach, Gamma’s head of design on using AI to synthesize feedback and generate on-brand imagery | Zach Leach explores gamma design leader uses AI for feedback synthesis and branding Zach Leach (Head of Design at Gamma) shows how he uses AI as a research assistant to digest large volumes of messy, multilingual product feedback—about 550 responses in a week—without manually translating or sampling only a small subset.

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