How Amplitude built an internal AI tool that the whole company’s obsessed with (and how you can too)

Wade Chambers, Chief Engineering Officer at Amplitude, shares how his team built Moda—an internal AI tool that gives employees access to enterprise data across multiple systems, enabling faster product development and decision-making while fostering cross-functional collaboration. *What you’ll learn:* 1. How Amplitude built a powerful internal AI tool in just 3 to 4 weeks of engineers’ spare time 2. A social engineering approach that made their AI tool go viral company-wide in just one week 3. How product managers use AI to analyze customer feedback across multiple data sources and identify key themes 4. A streamlined workflow that compresses research, PRD creation, and prototyping into a single meeting 5. Why role-swapping exercises with AI tools build empathy and cross-functional fluency across product, design, and engineering teams 6. How AI tools are helping engineering teams tackle persistent tech debt challenges more effectively *Brought to you by:* CodeRabbit—Cut code review time and bugs in half. Instantly: https://coderabbit.link/howiai Vanta—Automate compliance and simplify security: https://www.vanta.com/howiai *25k giveaway:*  To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway. *Where to find Wade Chambers:* LinkedIn: https://www.linkedin.com/in/wadechambers/ Amplitude: https://amplitude.com/blog/meet-the-team-wade-chambers *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) Introduction to Wade Chambers (02:53) The build vs. buy decision for internal AI tools (04:55) What Moda is and how it works (07:19) The social engineering approach to adoption (09:17) Demo of Moda in Slack (10:58) Data sources Moda has access to (12:43) Analyzing customer feedback themes with Moda (17:41) Behind the scenes: how Moda works technically (23:24) Creating a PRD from a single customer insight (27:30) How teams actually use AI-generated PRDs (29:09) Impact on product development velocity (32:37) Engineers, designers, and PMs swapping roles (34:38) Recap of creating Moda (36:00) Lightning round and final thoughts *Tools referenced:* • Glean: https://www.glean.com/ • ChatGPT: https://chat.openai.com/ • Cursor: https://cursor.com/ • Bolt: https://bolt.new/ • Figma: https://www.figma.com/ • Lovable: https://lovable.dev/ • v0: https://v0.dev/ *Other references:* • Amplitude: https://amplitude.com/ • Slack: https://slack.com/ • Confluence: https://www.atlassian.com/software/confluence • Jira: https://www.atlassian.com/software/jira • Salesforce: https://www.salesforce.com/ • Zendesk: https://www.zendesk.com/ • Google Drive: https://drive.google.com/ • Productboard: https://www.productboard.com/ • Zoom: https://zoom.us/ • Asana: https://asana.com/ • Dropbox: https://www.dropbox.com/ • GitHub: https://github.com/ • HubSpot: https://www.hubspot.com/ • Abnormal Security: https://abnormalsecurity.com/ _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._