Join us in the AI Product Kitchen this week as we talk to Nan Yu, Head of Product at Linear. In this episode, we talk about how Linear is transforming product development by turning AI agents into first-class team members and revolutionising how the highest-performing tech teams organise their work. Nan leads product at Linear, the modern issue tracking platform trusted by companies like OpenAI, Scale AI, and Ramp.
Learn about Linear's unique approach to AI product development, from replacing manual taxonomies with intelligent systems to deploying synthetic actors that participate in software workflows just like human colleagues.
In this episode, we dive into:
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Timestamps:
00:00 - Introduction and Guest Welcome
00:28 - What Will Feel Archaic in Five Years
01:00 - Building Better Products vs Shipping More Features
02:05 - Decision Making and Product Clarity
03:07 - High-Performing vs Low-Performing Product Teams
04:23 - The Problem with Traditional Backlogs
07:12 - Understanding Taxonomies and Organization Systems
09:03 - The Journey from Old to New Ways of Thinking
10:27 - Customer Behavioral Shifts and On-Ramps
12:42 - Linear's Engagement Strategy: Distinct Issue Creators
15:16 - AI Strategy Part 1: Sharpening Existing Data
17:02 - AI Strategy Part 2: Synthetic Actors and Agents
18:42 - Which Workflows Will AI Take Over First
20:26 - Barriers to AI Adoption in Development
21:57 - Building AI Products: Augmentation vs Replacement
23:58 - Measuring Success with AI Products
25:10 - Business Model Evolution with AI
26:26 - Low-Cost AI Experimentation Process
28:01 - AI Project Examples: Winners and Failures
30:15 - Integrating AI Without Compromising Simplicity
32:32 - ROI and Impact of AI Products
33:17 - Future Impact on Product Team Structure
37:00 - Starting with Customer Problems in AI Development
39:46 - Customer Development and Beta Testing Process
41:27 - Focusing on Individual Contributors vs Buyers
44:15 - Effective Customer Interview Techniques