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Inside the expert network training every frontier AI model | Garrett Lord (Handshake CEO)

Garrett Lord is co-founder and CEO of Handshake, which started as a career network for college students and new grads but recently discovered something extraordinary: they were sitting on the world’s largest network of academic experts—exactly what frontier AI labs desperately needed. With 500,000 PhDs and 3 million advanced degree holders creating training data, in just eight months they’ve built a new business that hit $50 million in revenue in its first four months and is on track to blow past $100M in the first 12 months.
What you’ll learn:
1. How Handshake found an opportunity to leverage their proprietary network of experts to launch a data-labeling business that’s on track to blow past $100 million ARR in 12 months
2. Why AI models need human experts (e.g. physics PhDs) to improve, and what this “data labeling” actually involves
3. Inside the actual work: what a biology PhD does for 8 hours that makes GPT-5 smarter
4. The playbook for building a startup inside a startup: separate teams, separate offices, separate everything
5. Why the shift from “generalist” to “expert” data labeling created a once-in-a-lifetime business opportunity
6. Why AI won’t eliminate entry-level jobs—it’s creating “Iron Man suits” that make junior employees 10x more productive

Brought to you by:
CodeRabbit—Cut code review time and bugs in half. Instantly: https://coderabbit.link/lenny
Orkes—The enterprise platform for reliable applications and agentic workflows: https://www.orkes.io/
Claude.ai—The AI for problem solvers and enterprise: http://claude.ai/

Where to find Garrett Lord:

Where to find Lenny:

In this episode, we cover:
(00:00) Introduction to Garrett Lord
(05:00) Understanding data labeling and its importance
(13:08) The role of experts in AI model training
(15:35) The future of AI and human collaboration
(24:17) Why AI won’t eliminate entry-level jobs
(27:58) The continuous improvement of AI models
(33:05) The emergence of Handshake’s new business model
(37:07) Incubating new ideas in established companies
(40:42) Handshake's competitive advantage
(45:43) Scaling up and meeting market demand
(48:38) Overcoming challenges and adapting
(53:08) The importance of separate teams and ownership
(57:26) The future of job matching with AI
(01:00:30) The biggest bottlenecks to advancing models further
(01:02:37) Lightning round and final thoughts

Referenced:
• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai
• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons
• General Motors: https://www.gm.com/
• Francisco “Paco” Guzman on LinkedIn: https://www.linkedin.com/in/guzmanhe/
• Avery Yip on LinkedIn: https://www.linkedin.com/in/averyyip/
• Careers at Handshake: https://joinhandshake.com/careers/

Recommended books:
Zero to One: Notes on Startups, or How to Build the Future: https://www.amazon.com/Zero-One-Notes-Startups-Future/dp/0804139296
The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers―Straight Talk on the Challenges of Entrepreneurship: https://www.amazon.com/Hard-Thing-About-Things-Building/dp/0062273205

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
Lenny may be an investor in the companies discussed.


To hear more, visit www.lennysnewsletter.com