FirstMark

How agents will buy, sell and pay: my conversation with @emilygsands, Head of Data & AI at @stripe As agentic commerce is rapidly shifting from a hypothetical concept to deployed financial infrastructure, is the internet ready for AI agents to take over our wallets and run their own businesses? 01:24 — The rise of agentic e-commerce 02:11 — The spectrum of agent-led purchases 03:16 — How merchants adapt to AI-driven commerce 05:50 — Defining the levels of autonomy in AI shopping 07:08 — What is the Agent E-Commerce Protocol (AEP)? 08:49 — Shared payment tokens and secure AI transactions 09:58 — Who is adopting the Agent E-Commerce Protocol? 11:38 — Can agents negotiate and sell products? 13:32 — The macroeconomic impact of AI agents 14:46 — The boom of solopreneurs and AI-driven business creation 16:56 — Why building trust is the biggest roadblock for AI commerce 20:19 — How link wallets improve payment security 21:21 — Improving the user experience in AI shopping apps 23:16 — How the Link Wallet sets guardrails for AI agents 25:40 — One-time use virtual cards vs flexible AI wallets 28:03 — Unpacking the shared payment token primitive 29:59 — How stablecoins enable profitable AI microtransactions 35:03 — Managing liability: Who is at fault if an agent goes haywire? 36:38 — Why agent payments might be safer than human transactions 37:41 — What is Vibe Deployment? 40:13 — Why Stripe built Stripe Projects for agent deployment 41:22 — Why Stripe cares about orchestrating app deployments 42:50 — How tokens break the traditional SaaS billing model 44:34 — Why AI companies are moving to hybrid and usage-based billing 47:15 — Streaming payments and real-time token tracking 48:42 — The massive data challenge for AI company accountants 50:41 — Token theft: The fastest-growing fraud in the AI economy 52:04 — The cottage industry of free trial and multi-account abuse 54:16 — How fraudsters monetize stolen AI tokens on the dark web 01:00:06 — How Stripe Radar uses network density to fight AI fraud 01:01:15 — Tempo's role in the Agent E-Commerce Protocol 01:04:12 — The AI startup ecosystem is accelerating business creation 01:09:01 — The token cost shock: Are buyers getting carried away? 01:11:19 — 2026 Predictions: Agents running businesses end-to-end

We’re crossing $100M in funding and welcoming @nvidia to our cap table as part of an extension of our seed round. This adds fuel to our momentum: real-time STT and TTS, Gradium Translate, Phonon, all shipped in a few months and with accelerating timelines between releases. It also supports our next step: expanding to San Francisco to work closer to the startups building the future of voice AI. We're hiring there. Come build with us.

Incredibly proud to continue backing this unstoppable team as they build the infrastructure for the next era of B2B events:  firstmark.com/story/vendelux… #Vendelux #SeriesB

Halfway through recording with @kathrynweinmann at @FirstMarkCap, she broke down how @function turned $10,000 of blood testing into a $365 product. Then it got bigger: 1 in 8 American adults have tried a GLP-1. Over 90% are off by year three. And the companies being built for what happens after are growing like crazy. She calls it one of the biggest health tailwinds of our generation. Kathryn is one of the sharpest consumer health investors in NYC. New episode of Venture Grounds is live.👇

@kathrynweinmann @FirstMarkCap @function youtube.com/watch?v=v8k-VC…

More from @amishjani here: firstmark.com/story/vendelux…

Congratulations to @vendelux on raising a $50M Series B, led by our friends at @tribecavp! We are thrilled to continue our participation after leading the Series A in 2023 🚀 Vendelux helps GTM teams identify the right events, find the right buyers, and turn B2B events into a measurable growth channel. Today, the company tracks 250,000+ global B2B events and supports programs influencing billions of dollars in event spend. Proud to keep backing Alex, Stefan, and the @vendelux team as they build the infrastructure for the next era of B2B events.

Inside Nemotron and NVIDIA's AI lab: my conversation with Bryan Catanzaro (@ctnzr). @nvidia is a chip company. So why does it put hundreds of researchers on building AI models - and then give them away for free? We go deep into the Nemotron models, what it takes to build a top AI lab, and the future of frontier AI. 01:33 - Is open source AI catching the frontier? 05:29 - Do closed labs blocking distillation slow open source down? 07:42 - Is the US falling behind China? 10:30 - Why companies actually choose open models 12:39 - A "crazy" 2008 bet: machine learning on GPUs 15:33 - Working with Andrew Ng and Dario Amodei at Baidu 17:41 - Coming back to NVIDIA: DLSS and the birth of Megatron 21:55 - The real reason NVIDIA builds its own models 24:28 - Is Moore's Law really dead? 33:37 - The Nemotron family: Nano, Super, Ultra 35:09 - Built for agents: why NVIDIA bets on speed 36:02 - How you train a 550B model in 4 bits 39:25 - Hybrid Mamba-Transformer, explained simply 42:31 - Mixture of experts, and why NVIDIA built NVL72 around it 47:26 - Why a 1-million-token context window matters 49:26 - Multi-token prediction: how the model predicts 5 tokens at once 52:47 - Multi-teacher distillation: teaching one model from many 58:01 - Where reinforcement learning goes next 01:00:16 - Inside NVIDIA's research org: "the mission is the boss" 01:04:03 - How NVIDIA decides who gets the GPUs 01:10:53 - Why NVIDIA still feels entrepreneurial after 33 years 01:12:58 - Why Bryan doesn't believe in the singularity 01:17:50 - The AI backlash 01:19:18 - The controversial case: open AI is safer than closed

You can just ship things. Live at @vercel Ship NYC! @vverawang

We have been named "IDP Platform of the Year" in the 2026 AI Breakthrough Awards! We are proud to be recognized alongside tech giants like @NVIDIA and @AMD for our work in transforming unstructured documents into ground-truth data for today's enterprise. tinyurl.com/yne8mfpw

We've raised $25M in Series A funding, led by @FirstMarkCap, with participation from @BainCapVC, @DecibelVC, @ZettaVentures, and Step Function. We’re building a hunt-first security analytics platform to help defenders tackle the hardest challenge: threats that don’t trip alerts 🔽

Bots have already won the Internet: my conversation with @eastdakota, CEO of @Cloudflare about agents, edge AI, and the new business model of the Internet (with some wild stories interspersed) 00:00 - Intro 01:27 - The moment bots passed humans online 04:05 - "Agent," "bot," "crawler" -- what they really mean 05:28 - Why your AI agent visits 5,000 sites to do one thing 06:27 - The internet's business model is breaking 06:52 - What happens to "brands" when machines do the buying 08:11 - What Cloudflare actually does, explained simply 10:29 - Hackers, human rights groups & an accidental product-market fit 13:37 - Building a global network (and the Telecom Pakistan cricket story) 21:10 - One hacker, from Turkish escort sites to Eurovision to JP Morgan 30:54 - Fundraising, VCs & an unlikely founding team 37:06 - How Cloudflare became an AI infrastructure company 40:24 - Cloudflare Workers and why the edge wins for inference 44:30 - AI Gateway: auditing, guardrails & runaway costs 47:05 - Why agents need a new kind of compute 52:13 - A "Log4j every week": security in the agentic era 56:03 - Inside Cloudflare: 241 billion tokens and "Cloudflare OS" 01:05:02 - Builders, sellers and "measurers" 01:06:30 - The decision Matthew thinks every company will face 01:11:09 - What to do if AI is coming for your job 01:13:56 - Content Independence Day & the new economics of the web 01:18:27 - Pay-per-crawl, micropayments & out-scaling Visa 01:20:20 - A better internet: Spotify, local news & "holes in the cheese"

Agents can use tools. Agents can use computers. But agents can't use MetaMask. Until now. Introducing Beam. The agentic CLI for Ethereum. • x402 & MPP built-in • Agentic spend controls • Conditional approvals • Sandboxed App Store • Supports every EVM chain • Secure key management • Private transfers

Wallets were built for humans. Beam was built for agents. Built by Payy, but works everywhere.

AI has rewritten the attacker playbook. The gap between amateur hackers and nation-states is collapsing. The most dangerous attacks now look routine: stolen credentials, valid tokens, normal-looking sessions. That’s why we’re thrilled to announce FirstMark’s investment in @nebulocksec, led by @DavidWaltcher. We’re excited to partner with Founder @abcbyDamien and the entire Nebulock team as they build the foundational security analytics stack. Join the hunt 🎯

Damien Lewke (@abcbyDamien) is the epitome of founder market fit. Couldn’t be more excited to be working with him and the wildly talented team at @nebulocksec. AI has rewritten the attacker playbook. The gap between an amateur hacker and a nation-state has alarmingly compressed, and the most dangerous attacks now look completely routine: stolen credentials, valid tokens, and sessions that slip past every tool trained to known-bad signatures. Nebulock flips the model: Vespyr, its autonomous threat hunting agent, works continuously across identity, endpoint, and cloud telemetry to hunt for how adversaries actually behave, already running 300M+ investigations and surfacing 4,000+ high-confidence findings that existing tooling missed, often within hours, in environments running best of breed detection / prevention tooling. What's in front of this team is even bigger: they’re building the foundational security analytics stack, baselined on every identity, endpoint, and resource, with agents that get smarter as the collective intelligence grows. Join the hunt 🎯 @sullivan @rak_garg @dannguyenhuu

Congratulations to @dataiku on FIVE YEARS IN A ROW as a Leader in the Gartner Magic Quadrant 🚀 firstmark.com/story/five-yea…

Dataiku has been named a Leader for the 5th time in the 2026 Gartner® Magic Quadrant™ for AI Platforms for Data Science & ML. We believe scaling AI takes the right people, orchestration, & governance — the Formula for AI Success — to turn ambition into impact. More to come.

State of AI compute 2026: my conversation with @stephenbalaban of @LambdaAPI on the neocloud boom, data centers, GPUs and what's ahead 00:00 — Cold open 01:21 — Why GPU compute was never a commodity 02:45 — The H100 price index and what it gets wrong 04:02 — The real moat: technology or financing? 05:57 — Winner-take-all, or room for many neoclouds 06:48 — Are we overbuilding or underbuilding AI compute? 09:26 — What if AI gets 10x more compute-efficient? 10:44 — The real bottleneck: land, power, and shell 11:38 — The backlash against data centers — and the misinformation 15:00 — Opening the hood: from photons to tokens 17:11 — Extracting more value from the same chip 19:26 — Frontier inference and distributed training, explained 23:26 — What actually drives compute cost 25:21 — Lambda's chip stack and the NVIDIA relationship 26:17 — A multi-silicon world? CUDA, CUDNN, and NVIDIA's real moat 28:59 — Networking, storage, and the one-click cluster 34:46 — Renting vs. owning, and full vertical integration 36:24 — How global is Lambda? Does location still matter? 38:44 — The financing stack: off-take agreements, SPVs, and credit 41:16 — Why a 2023 GPU leases for more today 42:36 — A futures market for compute? 43:54 — Origin story: facial recognition, Perceptio, and Apple 47:03 — The Lambda hat and Dream Scope 48:59 — The $60K bet that became a cloud business 52:00 — Holding the team together through the hard times 54:30 — Bringing on a new CEO; Stephen as CTO 57:33 — Matching xAI on high-velocity deployment 59:29 — "AI won't write software — it will become the software" 01:01:30 — Neural software vs. vibe coding 01:04:25 — Do agents change the compute layer 01:06:14 — Self-assembling software inside Lambda 01:08:18 — Gigawatt-scale AI factories 01:08:57 — One person, one GPU 01:12:04 — Hot takes: overrated and underrated in AI