How are big tech companies and VCs changing their approach to AI investments?

Big tech companies and VCs are shifting their approach to AI investments by cooling their initial exuberance and focusing on sustainable growth. They are moving past the peak of inflated expectations and are now navigating towards practical applications and long-term value.

The Shift in AI Investment Strategies

In recent months, there's been a noticeable change in how big tech and venture capitalists talk about AI. Brad noted that the rhetoric from CEOs and VCs has shifted significantly from bold predictions to more tempered expectations. "Six months ago, the CEO of Anthropics was saying that 90 percent of all code would be written by AI," Brad recalled, "but he's not saying that anymore" ▶ 1:21. This change in tone reflects a broader industry trend where the initial hype is giving way to a more cautious and realistic approach.

Scott added that the industry might be moving into what is known as the "trough of disillusionment" in the hype cycle, where inflated expectations are replaced by a more sober assessment of what AI can realistically achieve. "I think we're past the peak of inflated expectations," Scott said, suggesting that the industry is now on a long journey to find real value ▶ 2:20.

Real-World Examples and Economic Impacts

The economic impact of AI investments remains substantial, as Brad highlighted: "Fifty percent of GDP growth in the first half of 2025 was AI data centers for our whole country" ▶ 6:25. This indicates that while the hype might be cooling, the financial commitment to AI infrastructure is still significant. However, this investment comes with complexities. Brad described the financial churn among big tech companies investing in AI, where money seems to cycle between companies without real economic growth, likening it to a "friends cycling on top of each other type thing" ▶ 7:41.

Scott pointed out that despite the cooling hype, there are tangible advancements in AI applications. He shared an example from radiology: "They got all these models and they thought radiologists were going to all get fired because the computers were going to be doing it" ▶ 12:29. Instead, AI has enhanced efficiency, allowing radiologists to perform their tasks more effectively.

Navigating the AI Hype Cycle

The discussion also touched on the broader implications of AI's place in the hype cycle. Scott compared the current AI landscape to the early days of the internet, suggesting that while the initial hype has faded, the long-term potential remains significant. "It's going to be a decade-long grind of finding the value in it," Scott remarked, drawing parallels to the internet's gradual integration into everyday life ▶ 3:40.

Brad and Scott also explored the idea that the AI bubble might not have fully burst yet. Brad speculated that the intertwined investments of major players could lead to a "too big to fail" scenario, where the industry is propped up by its own momentum rather than genuine breakthroughs ▶ 9:13.

The Role of AI in Engineering and Development

On the development front, Scott shared an example from TaskRabbit, where an engineer used AI to quickly build an API client. "One of our engineers in like less than an hour with three prompts essentially built an API client," Scott recounted, highlighting how AI can accelerate development processes ▶ 18:03.

Brad noted that AI tools are increasingly being used to improve code quality and development efficiency. He observed that commit messages and PR descriptions are now often written by AI, reflecting a shift in how engineers are leveraging AI to enhance their workflows. "I'm just seeing the engineers that I work with on a really regular basis, they are more and more up-leveling their game by pushing the way the AI tools that they're using to be better written AI code" ▶ 19:38.

Conclusion

The conversation between Brad and Scott reveals a nuanced picture of the current state of AI investments. While the initial hype has cooled, the commitment to AI remains strong, with big tech and VCs navigating towards sustainable growth and practical applications. As the industry moves through the hype cycle, the focus is shifting from inflated expectations to finding real value and integrating AI more deeply into various sectors. This transition marks a critical phase in the evolution of AI, where the promise of technology begins to align more closely with its practical potential.