Tony explains why AI is fundamentally changing the cost of intelligence, how agentic systems could reshape software and labor markets, and why the current AI buildout may differ from past tech cycles. The discussion also dives into where we are in the AI cycle, how to think about the Mag 7, and what investors may be missing across the tech stack.
T. Rowe Price Science and Technology Fund
https://www.troweprice.com/financial-intermediary/us/en/investments/mutual-funds/us-products/science-and-technology-fund.html
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Topics Covered
* What it means to invest in “inevitabilities” and separating signal from noise in markets
* Why AI and compute demand represent a structural shift similar to past tech waves
* The rise of agentic AI and how it could transform software and productivity
* Whether AI is underappreciated or already priced into markets
* The “multiple moons” idea and why AI may not be a winner-take-all market
* How AI could reshape the labor market, productivity, and economic growth
* The AI CapEx debate and why this cycle may differ from the dot-com buildout
* Where we are in the AI cycle: training vs inferencing and deployment phase
* The impact of AI on software companies and the innovator’s dilemma
* How semiconductors, memory, and infrastructure remain key bottlenecks
* The changing nature of the Mag 7 and capital intensity in AI
* Tony’s portfolio construction framework across compounders, emerging tech, and value
* How he generates ideas using S-curve adoption and economic bottlenecks
* Position sizing, risk management, and balancing growth with drawdown control
* Sell discipline: valuation, fundamentals, and market signals
Timestamps
00:00 Introduction and Tony Wang overview
01:05 Investing in inevitabilities and long-term thinking
03:00 Differentiating inevitability from hype and consensus
04:45 AI inevitability and the rise of agentic systems
07:00 Cost of intelligence and productivity implications
08:00 Real-world examples of AI adoption (customer service, agents)
09:00 Is AI underappreciated by markets?
11:15 AI as a “space race with multiple moons”
13:30 AI as the dominant driver of markets today
15:00 AI’s impact on jobs, productivity, and the economy
18:30 Creativity, judgment, and the future of work
20:45 Physical AI and robotics opportunity set
22:30 AI CapEx debate vs the dot-com era
25:30 Semiconductors vs software in the AI stack
28:15 AI disruption risk for software companies
31:00 Cyclicality in semiconductors and how AI changes it
33:30 The evolving role of the Mag 7 in AI
36:30 Competition, startups, and AI democratization
38:00 Where we are in the AI cycle today
40:00 Idea generation and S-curve adoption framework
42:30 Case study: memory and AI bottlenecks
44:45 Example position: optical networking and infrastructure
46:40 Portfolio construction and position sizing
49:00 Sell discipline and managing valuation risk