Anthony Pompliano and Logan Kilpatrick of Google DeepMind dig into one of the biggest strategy questions in AI: will people use a few general-purpose AI products or thousands of specialized ones? Logan shares a thought exercise he poses internally, whether Google will have 10,000 products or just two or three in the next five to ten years, and explains why people are wired to reach for the right tool for each job.
Logan argues that startups can almost always beat a big company in a vertical because they are more focused. Pomp shares how Silvia uses model routers and specialized workflows, and...
What Anthony Pompliano said
Written from the verified transcript and checked against it. Every figure links to the moment it was said.
Pompliano discussed AI strategy with a Google executive, focusing on the choice between general intelligence and specialized workflows. He noted that startups like his own Silvia and Harvey are finding traction in specialized workflows, while Google must make this decision across multiple applications. The Google executive argued that vertical applications will persist due to user behavior patterns, comparing them to using a fly swatter for a fly rather than an all-encompassing tool. Pompliano highlighted the challenge of model routing, questioning whether Google would route queries to competitors like OpenAI or Anthropic, and noted the difficulty of predicting consumer adoption. He shared his personal use of Grok Bot for professional tasks and Instinct for personal ones, despite their overlap, and discussed the importance of memory and network effects in user adoption. The conversation concluded with the executive predicting that messaging apps would become the dominant AI form factor, with Apple, Android, and WhatsApp poised to integrate agents.
Key takeaways
Pompliano believes specialized workflow startups like Silvia and Harvey are gaining traction against frontier labs pursuing general intelligence.
He questioned whether Google would route queries to rival models from OpenAI or Anthropic, suggesting it's unlikely but not impossible.
Pompliano uses Grok Bot for professional work and Instinct for personal questions, despite their functional overlap.
The Google executive predicted messaging apps would become the dominant AI form factor, with Apple, Android, and WhatsApp leading.
Numbers and commitments
Figure
What it refers to
Type
At
10,000 products or two or three products
Google's potential product count in five to ten years
Startups are always worried about, oh, is the big company going to come after me? And it's like, you can always do a better job than the big company, with very few exceptions, because you're focused.
One of the aspects of the AI industry that is just intellectually stimulating, I think, for you, me, many other people, is there's a level of strategy that is being played out. So it's not just like, can you get the hardware and the software to do certain things, kind of create magic or turn sand into intelligence? Like, that is obviously very difficult and there are plenty of challenges there. But the strategy side, you know, we were talking previously that most of the frontier models are pursuing general intelligence some form or fashion, right? But then there's a bunch of startups that are saying, well, what if I take a specialized workflow approach? And if you think of what we've been building with Silvia, you know, this idea of, well, if we go and we build a bunch of proprietary technology, from model routers to harnesses to data pipelines and our own models, etc., it does feel like there's almost a point on each application of AI where you kind of have to decide: do we go after general intelligence or do we go after the specialized workflows? And Harvey, Silvia, you know, there's many players, I think, that are seeing a lot of traction in specialized workflows. But what I find fascinating about Google is you guys have multiple applications where you have to make that decision over and over again. Like, do we go and build the specialized workflows, or can we just use the general-purpose model? How are you navigating that? Like, for each one of these use cases, it's almost like you guys may be making that decision more than anyone else in the world.
3 more exchanges in this transcript
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Pompliano, A. (2026, October 22). Why Google Won't Chase Every AI VERTICAL [Interview transcript]. Anthony Pompliano Clips. CEOInterviews.AI. https://ceointerviews.ai/interview/3112814/
MLA
Anthony Pompliano. "Why Google Won't Chase Every AI VERTICAL." Anthony Pompliano Clips, 22 Oct. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/3112814/.
BibTeX
@misc{pompliano2026_3112814,
author = {Anthony Pompliano},
title = {Why Google Won't Chase Every AI VERTICAL},
howpublished = {Interview transcript, Anthony Pompliano Clips. CEOInterviews.AI},
year = {2026},
month = {oct},
url = {https://ceointerviews.ai/interview/3112814/},
note = {Speaker-attributed transcript with timestamps}
}
