Key Takeaways

• The AI industry is experiencing a significant shift from pre-training models on vast internet data to post-training, which focuses on augmenting and improving existing data with expert-generated content.
• Handshake, a platform for college students to connect with employers, has successfully launched a new business focused on providing high-quality training data for AI labs, achieving rapid revenue growth.
• The demand for AI training data has shifted from generalist tasks to specialized, expert-driven data, creating a significant opportunity for platforms that can access and mobilize expert talent.
• Younger generations, being ‘AI native,’ have a significant advantage in leveraging AI tools, which can enhance their productivity and career prospects, rather than solely leading to job displacement.
• Building a successful new business within an established company requires dedicated teams, clear focus, a metrics-driven approach, and a culture that embraces rapid execution and learning.

Segments

Handshake’s Pivot to AI Data (~00:11:00)

• Key Takeaway: Handshake leveraged its existing network of 18 million professionals, including tens of thousands of PhDs, to create a new business providing high-quality training data for AI labs, achieving rapid revenue growth.
• Summary: Lord details how Handshake identified an opportunity to serve AI labs seeking expert data by utilizing its extensive network of students and alumni, particularly those with advanced degrees. This strategic move led to the rapid launch of a new business that quickly achieved significant revenue milestones.

The Value of Expert Data (~00:17:00)

• Key Takeaway: The AI industry’s demand has shifted from generalist data labeling tasks to specialized work requiring deep expertise, making platforms with access to experts highly valuable.
• Summary: Lord explains that as AI models become more sophisticated, the need for generalist labor for tasks like bounding boxes diminishes. Instead, AI labs require experts in specific domains (like STEM, law, finance) to create and validate data, a niche Handshake is well-positioned to fill.

AI’s Impact on Jobs and Productivity (~00:35:00)

• Key Takeaway: AI is seen as an enabler of human productivity, allowing individuals to achieve more, rather than a direct cause of widespread job displacement, with ‘AI native’ young people having a significant advantage.
• Summary: Lord discusses the tension between AI’s advancement and job security, arguing that AI tools empower individuals to be more productive and impactful. He highlights that younger generations, who are native to these technologies, are better equipped to adapt and thrive in the evolving job market.

Building a New Business Within an Existing Company (~00:48:00)

• Key Takeaway: Successfully launching a new venture within an established company requires dedicated, separate teams, a clear focus on execution, a metrics-driven approach, and strong leadership commitment.
• Summary: Lord shares insights into the challenges and strategies for incubating a new business, emphasizing the need for distinct teams, clear ownership, and a rigorous operational cadence. He highlights the importance of separating resources and maintaining focus to navigate the complexities of rapid growth and innovation.

Handshake’s Competitive Advantage (~01:05:00)

• Key Takeaway: Handshake’s primary competitive advantage in the AI data labeling space is its decade-long built trust and access to a large, engaged audience, leading to no customer acquisition costs and higher conversion rates compared to competitors.
• Summary: Lord contrasts Handshake’s model with competitors who rely heavily on performance advertising and extensive recruitment efforts. He explains that Handshake’s existing brand affinity and direct relationship with millions of users provide a sustainable and efficient way to source high-quality data providers.

The Future of AI Data and Opportunities (~01:25:00)

• Key Takeaway: The demand for AI training data will continue to evolve, requiring new types of data beyond text, such as CAD files, scientific tool usage, and multimodal content, while synthetic data will play a supporting role.
• Summary: Lord discusses the future landscape of AI data, predicting a shift towards more complex data types needed for scientific discovery and automation. He also touches on the role of synthetic data and the ongoing need for human expertise in advancing AI capabilities.

Advice for Aspiring Entrepreneurs (~01:30:00)

• Key Takeaway: Aspiring entrepreneurs, especially in the AI space, should focus on creating value for people and solving societal problems, leveraging AI as a tool to enhance learning and opportunities.
• Summary: Lord shares his passion for entrepreneurship and encourages new founders to focus on building businesses that genuinely help people. He sees AI as a powerful tool that can unlock new ways to improve education and address societal challenges, offering his advice to those looking to start companies.

Key Books and Life Philosophy (~01:35:00)

• Key Takeaway: Garrett Lord recommends foundational business books like ‘Zero to One’ and ‘Shoe Dog,’ and lives by the motto ’leave nothing to chance,’ emphasizing dedication and execution.
• Summary: In the lightning round, Lord shares his favorite books that have influenced his entrepreneurial journey and his personal philosophy of giving his all to every endeavor. He also touches on his recent discovery of the Snoo for his baby and his experience with Game of Thrones.

The Hustle Behind Handshake (~01:38:00)

• Key Takeaway: Early in Handshake’s journey, Garrett Lord demonstrated extreme dedication by showering at university pools to save money and create memorable interactions with potential clients, showcasing a commitment to the business.
• Summary: Lord recounts a story from Handshake’s early days where he showered at a Princeton pool to save money, which inadvertently led to a more engaging meeting with a university contact, highlighting the resourcefulness and commitment required in entrepreneurship.