How Linear Built a $1.25B Unicorn with Just 2 PMs
Product Growth Podcast
Building AI Agents: Insights and Challenges
This chapter explores the development of AI agents within a new platform, detailing the evolution of the concept based on user feedback and the integration of AI features. The discussion highlights challenges such as the need for human oversight and the operational differences between AI and traditional computing. It also provides insights into the unique hiring practices and collaborative dynamics in a successful startup environment.
Nan Yu shares Linear's proven product-building method that helped them took Linear to a $1.25B product with just 2 PMs.
You’ll learn:
- How top companies like Linear are actually building AI features
- Secrets to building a lean product that users genuinely love
- Nan Yu’s advice for landing top PM jobs.
- The Linear method in detail
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Timestamps:
Preview – 00:00:00
Why are all the GIANTS using Linear? – 00:02:09
Linear's Core Functionality – 00:04:07
Ad (AI Evals) – 00:04:44
Ad (Vanta) – 00:05:44
Linear Method: How They Build Product – 00:06:36
Principles of the Linear Method – 00:09:16
Saying No to Busy Work / Busy Work Is a Result of “Lack of Clarity” – 00:12:14
Linear's Roadmap Planning Horizon – 00:14:43
Ad (AI PM) – 00:15:06
Ad (Maven) – 00:15:53
Planning Process – 00:16:41
Linear's Take on OKRs – 00:19:13
Setting The Bar High – 00:26:06
Story: Building The Smallest Version Possible – 00:28:49
Public Roadmaps are DANGEROUS – 00:34:20
Applying Linear Method to AI Features (Agents as Users) – 00:38:18
Mantra: Solve Real Problems for Real People – 00:43:08
Landing a Head of Product Role at Linear – 00:46:08
Story: How the Initial Contact with Linear Happened – 00:48:16
Advice for Aspiring PMs at Linear – 00:49:50
Making it to unicorn status with 2 PMs & 40 engineers – 00:53:18
Everlane's Pricing Strategy (Cost-Plus) – 00:53:44
Shift from B2C Retail to Product-Led B2B SaaS – 00:55:10
Can Today's PMs Shift Industries? – 00:57:22
Closing Notes – 00:59:49
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Key Takeaways:
Takeaways:
1. Don't Chase AI Hype, Solve Real Pain: Instead of building flashy AI features (that no one needs), Linear observes where users are actually struggling (like juggling many AI tools for async work) and builds direct solutions. It's about fixing real problems, not just jumping on trends.
2. Your Users Aren't a Feature Checklist. Listen intently to user feedback, but don't take every request literally. The goal is to understand their core frustrations and goals, not just to say "yes" to every demand that could lead to bloat.
3. Purpose Over PR Stunts. Forget building the "loudest possible feature." Linear's core mantra is to solve real problems for real people. Focus on making the most useful thing, and the noise will follow.
4. Run Marathons, Not Sprints. Sustainable momentum beats endless "sprints" every DAMN time. Find a comfortable pace you can maintain not just tomorrow, but a year from now. Burnout is a warning sign, not a badge of honor.
5. Scope Small, Ship Often. Unshipped code is debt. By making tasks as tiny as possible, you get the reward of shipping constantly. This creates tangible proof of work, gets immediate user feedback, and keeps the motivation high.
6. Quality Isn't a Side Quest. Bugs aren't "minor." They're either critical or high priority. A "little bug" seen a hundred times tells customers you don't care. Quality work is baked into every feature, because a feature isn't done until it's high quality.
7. Clear Talk, Clear Work. Ban jargon. LITERALLY. Words should have one meaning. If "issue" refers to a task in your product, it only refers to that. This ruthless clarity eliminates misunderstandings and speeds up collaboration.
8. Ditch Old-School User Stories. Traditional "As a user, I want X" stories often hide context and slow things down. Everyone understands software now. Cut the BS. Be direct and state the desired outcome clearly.
9. Build to Learn, Not to Delay. Excessive data collection or endless A/B tests shows lack of decision making. Instead, build a smaller version of your idea quickly, put it out there, and let the market tell you if you're right or wrong. Learn fast, move faster.
10. Forget Personas, Find Mike. Stop building for abstract personas. Identify the real people you're working with – "Mike from Brex," "Sarah from Acme Corp." Knowing them by name deepens empathy and leads to better solutions.
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Check it out on Apple, Spotify, or YouTube.
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Related Podcasts:
Complete Course: AI Product Discovery
"Most Product Managers are Bullsh*t Managers" -2x CPO
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