Welcome to another edition of our Sunday “Resources” stream where we share our most valuable data & resources across four rotating formats:

For 1. and 3., we collaborate with best-in-class partners to ensure you get the highest quality data. For 2. and 4., we leverage our ever-growing product portfolio and share selective snapshots of the most sought-after resources from The Lab.

At the end of this post, you'll find a unique deep dive on "Network Is the New Data: How AI-Powered Relationship Intelligence Drives Alpha" with Ties Boukema (Dawn Capital), Jesse Lott (Affinity), and Ben Orthlieb (Blue Moon).

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Here’s a summary of the best content that I consumed in the previous week..

Rabbi and writer Zohar Atkins applies Jevons Paradox — the economic observation that greater efficiency in using a resource actually increases total consumption of it — to AI and Torah study. His argument: as AI collapses the cost of accessing Jewish texts and legal tradition, the bottleneck shifts from accessing knowledge to generating genuine new insight from it (what the tradition calls chiddush). What was once an elite obligation reserved for the few becomes operationally required of everyone. A rich, wide-ranging piece that uses economics, Talmudic sources, and Kabbalistic parable to make the case that the real work of learning has always been baking bread from wheat, not just gathering the grain.

A short, punchy argument that AI agents are about to make "systems of record" indefensible as moats. Agents can now systematically extract data from any CRM, social graph, or model, making data portability trivially easy. The one thing agents cannot replicate is a live, active user base generating new interaction data. Mignano's conclusion: in an agent-first world, network effects are the only durable competitive advantage. Everything else can be scraped, distilled, or migrated.

A bullish counterargument to AI bubble skeptics, written by a VC at SF1. The core claim: unlike the DotCom era, this cycle has revenue growth, user adoption, capital availability, and founder quality all compounding simultaneously. He points to companies hitting $100M ARR within 12 months of founding, and argues that AI valuations even at "priced to perfection" levels are actually cheap relative to the scale of what's being built. His framing: people are fighting the last bubble they remember. This one is structurally different.

I'm excited to share one of the most discussed sessions from the Virtual DDVC Summit 2026. The cliché is that venture is a people business. The reality, after this panel, is sharper: most firms have no idea what their network is actually worth, and the ones who started measuring it years ago are already pulling away.

That's the gap Ties Boukema (Dawn Capital), Jesse Lott (Affinity), and Ben Orthlieb (Blue Moon) dug into at the Summit. Three perspectives on how AI is turning relationship data into compounding alpha, and what firms starting today can still do about it.

Watch if you want to learn:

Here’s the link to the full panel discussion👇