The smallest technical decisions become humanity's biggest pivots:
The same-origin policy—a well-intentioned browser security rule from the 1990s—accidentally created Facebook, Google, and every data monopoly since. It locks your data in silos—and you stayed where your stuff already is. This dynamic created aggregators.
Alex Komoroske—who led Chrome's web platform team at Google and ran corporate strategy at Stripe—saw this pattern play out firsthand. And he's obsessed with the tiny decisions that will shape AI's next 30 years:
Whether AI keeps memory centrally or user-controlled?
Is AI free/ad-supported or user-paid?
Should AI be engagement-maximizing or intention-aligned?
How should we handle prompt injection in MCP and agentic systems?
Should AI be built with AOL-style aggregation or web-style openness?
This is a much-watch if you care about the future of AI and humanity.
If you found this episode interesting, please like, subscribe, comment, and share!
Want even more?
Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Sponsors:
Google Gemini: Experience high quality AI video generation with Google's most capable video model: Veo 3. Try it in the Gemini app at gemini.google with a Google AI Pro plan or get the highest access with the Ultra plan.
Attio: Go to https://attio.com/every and get 15% off your first year on your AI-powered CRM.
Timestamps:
- Introduction: 00:01:45
- Why chatbots are a feature not a paradigm: 00:04:25
- Toward AI that’s aligned with our intentions: 00:06:50
- The four pillars of “intentional technology”: 00:11:54
- The type of structures in which intentional technology can thrive: 00:14:16
- Why ChatGPT is the AOL of the AI era: 00:18:26
- Why AI needs to break out of the silos of the early internet: 00:25:55
- Alex’s personal journey into systems-thinking: 00:41:53
- How LLMs can encode what we know but can’t explain: 00:48:15
- Can LLMs solve the coordination problem inside organizations: 00:54:35
- The under-discussed risk of prompt injection: 01:01:39
Links to resources mentioned in the episode:
