Alex Komoroske (Common Tools)

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Sep 10, 2025

Join Alex Komoroske, co-founder and CEO of Common Tools, who previously led projects at Google and Stripe, as he shares insights on the transformative power of emergence in technology. He discusses how individual user behaviors can lead to significant collective outcomes and the importance of data-driven decision-making. The conversation dives into the complexities of AI and its security risks, urging the need for awareness around data policies and the potential dangers of an AI monoculture. Alex's perspective on the evolution of collaborative platforms like Wikipedia is equally captivating!

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ADVICE

Rethink Product Economics With LLMs

Re-evaluate product assumptions because LLMs change software economics: ideas once expensive are cheap to build.
Expect marginal-costs and distribution mechanics to reshape viable business models.

INSIGHT

Separate Models From Applications

Separate model layer from app layer to enable pluralism, swapability, and competition.
Alex prefers apps that own data while models remain replaceable commodities.

INSIGHT

Chat Is A Feature, Not The Whole Paradigm

Chat is a feature not the dominant paradigm for structured, long-lived tasks.
GUIs and structured data remain Lindy and better suited for many workflows.

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In this episode of The Slow Hunch, I spoke with Alex Komoroske, the co-founder and CEO of Common Tools. Alex has spent his career thinking about how individual incentives can add up to significant collective outcomes.

Before starting Common Tools, he spent more than a decade at Google leading product management for the Chrome web platform, ambient computing, AR, and Search, and later served as Head of Corporate Strategy at Stripe.

We traced his slow (emergent) hunch from an early fascination with Wikipedia, through his years building internet-scale systems at Google, to his current work rethinking how AI is architected.

A big part of our conversation centered on emergence: why the most durable systems grow from the bottom up, and what that means for product design, org culture, and the future of technology - especially AI.

We also spoke about the hidden security risks in today’s AI ecosystem: why “chat” may not be the defining paradigm for complex work, how fusing data to apps risks locking us into an AI monoculture, and why policies should travel with data if we want healthier emergent effects.

It’s always fun catching up with Alex. Hope you enjoy!

Chapters:

00:00:00 Cold open: the inevitability of transformers
00:03:32 Why emergence is so powerful
00:08:49 Alex’s early influences
00:10:35 The emergent dynamics of Wikipedia
00:13:15 The role of “folksonomies”
00:17:33 Concave systems vs convex systems
00:20:41 Alex’s time at Google
00:24:27 How small signals scale
00:28:58 Evolutionary algorithms in AI
00:30:52 Understanding data bias and rethinking how AI is architected
00:41:02 The same-origin trap and the limits of app-centric software
00:47:42 The future of contextual apps
00:49:03 Aggregators and the tyranny of the marginal user
00:52:08 Why prompt injection is so dangerous
00:55:23 The inherent security risks of MCP and vibe coding
00:59:32 A new constitution for AI: policies attached to data
01:03:17 The promise of confidential compute
01:11:00 Why Alex is optimistic about AI's Future