Testing the framework live in San Francisco with @dghoang Hmu if you want to join the next ai operator cheeky pint night

In a world full of very smart, very kind, very ambitious, and very articulate humans, @amspector100 stack ranks among the top for each. Somehow he combines them all. He even made airplanes flap. I didn't know they could do that! Strong endorsement for placing your talent chips here. signed: admiring friend.

if @Starlink were an airline, I would only fly Starlink

Impeccable vibes at our @a16z consumer dinner tonight ✨ I’ve been investing in consumer for a decade, and I believe we’re now at the beginning of a renaissance. There are going to be some category-defining companies built in the next few years!

The wallet wars are here. Very Good Security chief strategy officer Terry Angelos joins a16z's Alex Rampell, his TrialPay co-founder from back in 2006 (TrialPay was later acquired by Visa), to discuss how agents are learning to spend money. "Agents have all of a sudden become significantly more helpful and useful because they effectively have arms and legs, which are payment credentials." VGS holds the payment credentials behind about 1/3 of all e-commerce, and now it's helping AI agents pay merchants. If you've bought anything online, there's a good chance VGS has already helped keep your card safe. In the last three months, Terry says agents went from "spectators to actors." Once an agent has your payment credentials, it can book the piano teacher it previously could only find and recommend. Now Stripe's Link, Shopify's Shop Pay, and PayPal are racing to connect to agents. It's all headed toward open standards from the card networks: agentic tokens that let an agent pay with your actual card. VGS went from zero agentic tokens to a few million a week in three months. 0:55 From TrialPay to Visa to VGS 2:05 How VGS vaults 1/3 of e-commerce 6:05 Why big merchants use 3-5 processors 9:55 Why AI agents need a payment vault 12:15 Agents go from "spectators to actors" 13:40 The wallet wars, old and new 19:55 Walled gardens vs open standards 23:55 How agents can pay with your real card 26:40 Your saved card goes multiplayer 29:40 How do you trust an agent's purchase? 32:35 Who pays when your agent gets it wrong 35:40 Why Amazon blocks agents 39:50 What's overhyped and underhyped 43:35 When merchants get agents too 45:40 Why agents could break card rewards 47:00 VGS's eras: vault, updates, network @terryangelos @arampell

He’s founding… … The Bill Chen Run Club. Tuesday. 9pm. Embarcadero. 👀

If they invite me, you'll need to make this log scale.

Had early access to Gemini 4 Argon - so I asked for slides on the AI power bottleneck. It synthesized 8 years of 10-K filings, FERC queue data across all 6 US grid operators, 17 gigawatt cluster buildouts, and a decade of GPU thermal specs. And I got this interactive deck 🤯

Incredible time with some of the sharpest minds in tech! @zanelackey has one of the clearest perspectives on where cybersecurity is headed, and @jamdac and @astrange are two of my favorite people to spend time with. Always great conversations!

Can AI Slay the Spire?

Pictured: @vivianmshen and @MilksandMatcha leaving their respective husbands for a SOTA wife instead Sorry @AnjneyMidha @tyler_fong_

Getting hacked at age 12 inspired his career in security. @zanelackey has the best OG stories - “craziest hack you’ve seen” (ask him!) best done over tacos w @jamdac @dhaber

At this point @LosTacosNo1 is the official catering brand of @a16z NYC. Oh and @zanelackey also gave a great chat on all things angel investing to our scout community. 🌮🌮🌮

Another great @GBxGlobal Gala in the books. Thanks to @MarkCharkin and the entire team for making it happen!

Another great piece by @chem_safety .

So excited to back Jennifer Zhou and Ning Cao at @preferencemodel They’re open-sourcing Karotte today, the framework they've used to build RL environments for frontier labs. These RL envs live or die on graders models relentlessly try to game, so Karotte bakes in defenses hardened over 1M eval runs to keep models focused on real tasks instead of loopholes. Preference Model’s target is ML engineering itself, the hardest domain to build envs for and the one every lab wants. Models building models starts here. Shoutout to @Mascobot who was a great partner on this one @chem_safety @Ning_Catsnail

"I'd work with with him in a heartbeat" was what the fund manager who @zainmfj worked for when he was just 14 yo told me. Zain is one of the highest agency founder I have ever met, so I knew I had to work with him. I am incredibly bullish about the future where everyday people own the intelligence stack, starting with the hardware at @ghostai. Knowing where Zain started - building an agentic software product out of a daily-rated Tenderloin bedroom - it's been eye opening to see the migration and expansion of the ambition. Very excited for the launch! 🚀