The GitHub Repo That Runs Her $100M Startup

Jiaona Zhang (JZ) is the CPO at Laurel, a $100M AI timesheet platform. She has led product at Airbnb, Dropbox, Webflow, and WeWork. Today she runs a product team that ships front-end and back-end features end-to-end. In this episode, she screenshares Laurel's full Company OS live, walks through the agent pipeline, shows how non-technical team members ship to production using AI, and breaks down the 4 levels of AI maturity she uses to assess every candidate she interviews. Full Writeup: https://www.news.aakashg.com/p/how-to-build-an-ai-native-team Transcript: https://www.aakashg.com/how-to-build-ai-native-team/ Laurel: https://www.laurel.ai/ --- Timestamps: 0:00 - Intro 1:46 - Episode begins 2:04 - The Company OS: GitHub structure screenshare 5:40 - The 1% vs 99% problem 9:00 - 3 steps to build your own Company OS 10:05 - Ads 12:30 - Slack automation demo: feature request triage 14:31 - Playbook to agent pipeline 22:51 - Company culture and the companywide hackathon 29:02 - PMs shipping front-end and back-end features 29:44 - The captain model explained 30:34 - Ads 32:37 - Continuation to captain model 37:38 - Two-track product reviews 50:08 - The AI Ops team and the Sasha model 57:59 - The screen-share interview 59:01 - The 4 levels of AI maturity 1:06:08 - Outro --- 🏆 Thanks to our sponsors: 1. Ariso - Ship AI agents and features faster, with fewer regressions - https://ariso.ai/aakash 2. Bolt - Ship AI-powered products 10x faster - https://bolt.new/solutions/product-manager?utm_source=Promoted&utm_medium=email&utm_campaign=aakash-product-growth 3. Pendo - The #1 software experience management platform - http://www.pendo.io/aakash 4. Product Faculty - Get $550 off their #1 AI PM Certification with code AAKASH550C7 - https://maven.com/product-faculty/ai-product-management-certification?promoCode=AAKASH550C7 5. Customer.io - Send smarter messages using your product data - http://customer.io/productgrowth --- Key Takeaways: 1. Every company has a 1% who are AI-native and a 99% who do not know what to use when. The Company OS closes that gap by encoding the 1%'s workflows into skills that anyone can use when they open Claude. 2. Build the ontology before you build the OS. Map every team's work to categories and tasks first. Color-code what should get more human time vs what gets automated. The OS is built from that work map. 3. Even the friction of going to a different interface kills adoption. A separate agent tool in a new tab will not get used consistently. Deliver skills and automations inside Slack and email, where people already are. 4. When AI adoption is everyone's responsibility, it is no one's responsibility. Dedicate one person full-time to AI Operations. Start with one person who demonstrates value. Every other function will want their own version within months. 5. The Company OS turns a 50-page playbook into a set of agents. Write the playbook first. Then audit it. What requires a human? What can be automated? Build the skill files from what remains. 6. The captain model replaces the handoff chain. Every feature has one owner end-to-end. The captain is whoever has the most critical skill for that feature's hardest problem. 7. PMs at Laurel ship front-end and back-end features. Not just growth experiments or copy changes. Core product features deeply integrated with billing systems and time entry logic. One PM who identifies as a designer shipped one of these end-to-end last month. 8. JZ went from hundreds of reports to 5 PMs and 4 designers. They ship more than ever. Adding people adds coordination cost. In a world where one PM can take a feature from discovery to production in a day, large teams cancel out their own capacity gains. 9. The new PM interview is a screen share. JZ asks every candidate to show their actual screen. In 60 seconds she knows their level of AI skills. 10. The PM fundamentals never changed. Problem space first. Know why and for whom you are building before you build. The speed changed dramatically. What you are supposed to be doing at the heart of it did not. --- 👨‍💻 Where to find Jiaona Zhang: LinkedIn: https://www.linkedin.com/in/jiaona/ Reforge: https://www.reforge.com/profiles/jiaona-zhang Laurel: https://www.laurel.ai/ 👨‍💻 Where to find Aakash: X: https://x.com/aakashgupta LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #productmanagement #aipm #claude --- About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. Subscribe and turn on notifications.

Jiaona ZhangguestAakash Guptahost

Jun 15, 20261h 7mWatch on YouTube ↗

EPISODE INFO

Released: June 15, 2026
Duration: 1h 7m
Channel: Aakash Gupta
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

Jiaona Zhang (JZ) is the CPO at Laurel, a $100M AI timesheet platform. She has led product at Airbnb, Dropbox, Webflow, and WeWork. Today she runs a product team that ships front-end and back-end features end-to-end. In this episode, she screenshares Laurel's full Company OS live, walks through the agent pipeline, shows how non-technical team members ship to production using AI, and breaks down the 4 levels of AI maturity she uses to assess every candidate she interviews. Full Writeup: https://www.news.aakashg.com/p/how-to-build-an-ai-native-team Transcript: https://www.aakashg.com/how-to-build-ai-native-team/ Laurel: https://www.laurel.ai/ --- Timestamps: 0:00 - Intro 1:46 - Episode begins 2:04 - The Company OS: GitHub structure screenshare 5:40 - The 1% vs 99% problem 9:00 - 3 steps to build your own Company OS 10:05 - Ads 12:30 - Slack automation demo: feature request triage 14:31 - Playbook to agent pipeline 22:51 - Company culture and the companywide hackathon 29:02 - PMs shipping front-end and back-end features 29:44 - The captain model explained 30:34 - Ads 32:37 - Continuation to captain model 37:38 - Two-track product reviews 50:08 - The AI Ops team and the Sasha model 57:59 - The screen-share interview 59:01 - The 4 levels of AI maturity 1:06:08 - Outro --- 🏆 Thanks to our sponsors:
1. Ariso - Ship AI agents and features faster, with fewer regressions - https://ariso.ai/aakash
1. Bolt - Ship AI-powered products 10x faster - https://bolt.new/solutions/product-manager?utm_source=Promoted&utm_medium=email&utm_campaign=aakash-product-growth
1. Pendo - The #1 software experience management platform - http://www.pendo.io/aakash
1. Product Faculty - Get $550 off their #1 AI PM Certification with code AAKASH550C7 - https://maven.com/product-faculty/ai-product-management-certification?promoCode=AAKASH550C7
1. Customer.io - Send smarter messages using your product data - http://customer.io/productgrowth --- Key Takeaways:
1. Every company has a 1% who are AI-native and a 99% who do not know what to use when. The Company OS closes that gap by encoding the 1%'s workflows into skills that anyone can use when they open Claude.
1. Build the ontology before you build the OS. Map every team's work to categories and tasks first. Color-code what should get more human time vs what gets automated. The OS is built from that work map.
1. Even the friction of going to a different interface kills adoption. A separate agent tool in a new tab will not get used consistently. Deliver skills and automations inside Slack and email, where people already are.
1. When AI adoption is everyone's responsibility, it is no one's responsibility. Dedicate one person full-time to AI Operations. Start with one person who demonstrates value. Every other function will want their own version within months.
1. The Company OS turns a 50-page playbook into a set of agents. Write the playbook first. Then audit it. What requires a human? What can be automated? Build the skill files from what remains.
1. The captain model replaces the handoff chain. Every feature has one owner end-to-end. The captain is whoever has the most critical skill for that feature's hardest problem.
1. PMs at Laurel ship front-end and back-end features. Not just growth experiments or copy changes. Core product features deeply integrated with billing systems and time entry logic. One PM who identifies as a designer shipped one of these end-to-end last month.
1. JZ went from hundreds of reports to 5 PMs and 4 designers. They ship more than ever. Adding people adds coordination cost. In a world where one PM can take a feature from discovery to production in a day, large teams cancel out their own capacity gains.
1. The new PM interview is a screen share. JZ asks every candidate to show their actual screen. In 60 seconds she knows their level of AI skills.
1. The PM fundamentals never changed. Problem space first. Know why and for whom you are building before you build. The speed changed dramatically. What you are supposed to be doing at the heart of it did not. --- 👨‍💻 Where to find Jiaona Zhang: LinkedIn: https://www.linkedin.com/in/jiaona/ Reforge: https://www.reforge.com/profiles/jiaona-zhang Laurel: https://www.laurel.ai/ 👨‍💻 Where to find Aakash: X: https://x.com/aakashgupta LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #productmanagement #aipm #claude --- About Product Growth: The world's largest podcast focused solely on product + growth, with over 200K+ listeners. Subscribe and turn on notifications.

SPEAKERS

Jiaona Zhang
guest
Chief Product Officer at Laurel who teaches product/AI leadership (including at Stanford and via Reforge).
Aakash Gupta
host
Podcast host and interviewer focused on product and AI workflows.

EPISODE SUMMARY

In this episode of Aakash Gupta, featuring Jiaona Zhang and Aakash Gupta, The GitHub Repo That Runs Her $100M Startup explores inside Laurel’s GitHub-based Company OS powering AI-native execution at scale Laurel maintains a companywide GitHub repository structured by function (sales, CS, product, etc.) that stores playbooks, “skill files,” and an ontology of work so teams know exactly which AI-enabled procedure to use when.

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