Layers of the AI stack and timing

What happens when the marginal cost of intelligence approaches zero? David Weisburd speaks with Richard Socher about building U.com, the evolution of AI search and agents, and why infrastructure—not hype—will determine AI’s real economic impact. Richard shares a first-principles view on where AI creates value, how enterprises are deploying agents today, and what long-term shifts in labor, productivity, and education may follow.

Highlights:

• Building You.com and focusing AI search on accuracy and data quality
• Why AI agents depend on strong search and infrastructure layers
• Early enterprise use cases across coding, legal, healthcare, and research
• The idea of intelligence becoming cheap and its second-order effects
• Why AI adoption is gradual but structurally inevitable
• Jobs, agency, and the fallacy of fixed labor supply
• How AI changes access to tutoring, healthcare, and personal assistance
• Investing in AI from first principles: data availability and timing
• Where regulation matters and where it risks overreach
• Why computer science remains foundational in an AI-driven world

Guest Bio:

Richard is the Co-Founder and Managing Director at AIX Ventures and Co-Founder and CEO of You.com, the leading AI search infrastructure for enterprises. At AIX Ventures, he has led early investments into several fast growing and category defining AI startups including Hugging Face, Weights and Biases, Athelas, Profluent, Parallel Bio, and Assured Robot Intelligence (ARI).

Richard previously served as the Chief Scientist and EVP at Salesforce. Before that, Richard was the CEO/CTO of AI startup MetaMind, acquired by Salesforce in 2016. Richard received his Ph.D. in computer science from Stanford University in 2014 and later served as an adjunct professor. He is widely recognized as having brought neural networks into the field of natural language processing, inventing the most widely used word vectors, contextual vectors, and prompt engineering. He is one of the top-five most-cited researchers in NLP, with over 230,000 citations.

Our Podcast now receives more than 300,000 downloads a month. Are you interested in sponsoring an episode? Please email David Weisburd at david@weisburdcapital.com.

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X/Twitter: @dweisburd LinkedIn: https://www.linkedin.com/in/dweisburd/ Weisburd Capital: https://www.weisburdcapital.com/

Stay Connected with Richard Socher:

LinkedIn: https://www.linkedin.com/in/richardsocher/

Questions or topics you want us to discuss on How I Invest? Email us at david@weisburdcapital.com.

Disclaimer:

This podcast is for informational purposes only and does not constitute investment, financial, legal, or tax advice. Nothing in this episode should be interpreted as an offer to buy or sell any securities or to participate in any investment strategy. All opinions expressed by the host and guests are their own and do not represent the views of Weisburd Capital. Participants may hold positions or have financial interests in the companies, funds, or investments discussed. Any references to specific investments are for illustrative purposes only. Investing involves risk, including the potential loss of capital. Past performance is not indicative of future results, and any forward-looking statements are subject to risks and uncertainties. Any third-party data or opinions have not been independently verified. Listeners should conduct their own research and consult their own advisors before making any investment decisions.

(0:00) Introduction (1:05) AI in enterprises and its impact on job markets (4:22) Predictions for the economic impact of AI agents (7:34) AI's role in evolving local news and early enterprise use cases (8:49) AI investment strategies and Richard Socher’s fund principles (14:06) AI regulation, comparison with crypto, and geopolitical aspects (18:45) AGI, ASI, and AI's influence on math and programming (21:14) Balancing AI optimism with potential risks and existential concerns (25:01) Preparing future skills for AI-driven industries (26:15) Interdisciplinary approach combining computer science (27:09) Richard Socher's personal life insights (28:13) Closing remarks