Tomasz Tunguz
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San Francisco, California, United States
406K followers
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Articles by Tomasz
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Securing the Agentic Enterprise : Office Hours with Jonathan Jaffe
Securing the Agentic Enterprise : Office Hours with Jonathan Jaffe
Enterprises run on AI agents. So do the attackers.
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All the AI You Need for 8 Ads per Day
All the AI You Need for 8 Ads per Day
One search ad every 40 minutes pays for a trillion-parameter model. One content ad every 3 minutes does the same.
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This Week's Sign the Apocalypse Isn't Upon Us
This Week's Sign the Apocalypse Isn't Upon Us
I remember growing up reading Sports Illustrated. There was a small column called “This Week’s Sign the Apocalypse Is…
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The $112 Billion Quarter
The $112 Billion Quarter
Google Cloud grew 63% year-over-year in Q1 2026. Amazon Web Services posted 28%.
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Darwinian Specialization in AI
Darwinian Specialization in AI
The inference market is the fastest growing market in the world & it’s splitting up. Each modality is developing its…
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The Three Questions in AI Sales
The Three Questions in AI Sales
The old sales motion asked : what’s your software budget for this category? The new motion asks customers three…
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GPU Spot Prices Surge 114% in Six Weeks
GPU Spot Prices Surge 114% in Six Weeks
NVIDIA’s latest GPU rental prices on the Ornn Compute Price Index hit $4.95 per hour this week, up from $2.
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Competitive Strategy in the Age of AI
Competitive Strategy in the Age of AI
Google commoditized its complements : free maps, free email, free browsers, a free mobile OS. They removed every toll…
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Intelligence About Business
Intelligence About Business
“BI became dashboards. And now it is re-expanding to business intelligence.
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A $10b Call Option
A $10b Call Option
SpaceX announced a partnership with Cursor today : a $10 billion collaboration with a $60 billion acquisition option…
21 Comments
Activity
406K followers
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Tomasz Tunguz shared thisEnterprises run on AI agents. So do the attackers. What does it mean to build, secure, and operate AI systems when both sides - defenders and attackers - are automated? Jonathan Jaffe, CISO at Lemonade, is one of the most forward-thinking security leaders in this age of AI, with more than 25 years of experience in technical security roles since 1997. Join us for a conversation covering : When the attacker is an agent, the defender must be too. Traditional security playbooks assume human adversaries at human speed. AI agents require AI defenders by design. Agentic security as a systems problem. How to build, monitor, and operate AI in the enterprise when both sides are autonomous. Trust and oversight at machine speed. Where to draw the line between automation and human judgment when adversaries act in milliseconds. The format. 15 minutes online. One topic. Call-in questions live. No slides. No pre-written questions. Just a real conversation. Register here for Office Hours : Securing the Agentic Enterprise with Jonathan Jaffe. https://lnkd.in/gH5fFBhX
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Tomasz Tunguz shared thisSecuring the Agentic Enterprise The format. 15 minutes online. One topic. Call-in questions live. No slides. No pre-written questions. Just a real conversation with Jonathan J.Securing the Agentic Enterprise : Office Hours with Jonathan JaffeSecuring the Agentic Enterprise : Office Hours with Jonathan Jaffe
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Tomasz Tunguz shared thisOne search ad every 40 minutes pays for a trillion-parameter model. One content ad every 3 minutes does the same. The math on ad-supported AI is better than you think. When Anthropic pulled Claude Code from the $20 plan last month, it signaled an industry assumption : frontier intelligence requires frontier pricing. For open models, the economics flip. A B200 GPU costs $4.50/hour on spot markets. Google Search ads generate $38.40 CPM (cost per thousand impressions), while Google Display runs $3.12. These numbers assume the provider runs 4 B200 Blackwells at 300 users, 50% of the theoretical maximum, leaving headroom for bursts. To support these costs, users would see one ad every 3 to 39 minutes. That is well below what users already tolerate : hyper-casual mobile games show six ads per session, roughly one per minute. There are nuances. Assuming ad fill rates (the share of ad requests that return a paid ad) and ad network revenue share, we can model effective CPMs of $1.50. At that floor, the frequency doubles. One content ad every 90 seconds still covers the cluster, comparable to what mobile users already tolerate. On the other end of the spectrum, rewarded video clears at $40 to $50 CPM with near-100% fill in gaming. A single round of rewarded video across the cluster nearly covers an hour of compute. But there is the question of utilization. All of these figures assume the cluster stays busy. Idle GPUs raise the per-user cost. What about heavier workloads? Agentic coding burns 10 to 20x more tokens than passive chat. At that rate, ad-only models can’t keep up. But a hybrid works : $10/month plus 8 ads per day covers 2 million tokens. It won’t fund a tokenmaxxing habit, but it will keep you shipping. Ad-supported AI is viable : open models, commodity GPUs, and ad frequencies already parallel those of mobile & web.
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Tomasz Tunguz shared thisOne search ad every 40 minutes pays for a trillion-parameter model. One content ad every 3 minutes does the same. The math on ad-supported AI is better than you think. When Anthropic pulled Claude Code from the $20 plan last month, it signaled an industry assumption : frontier intelligence requires frontier pricing. For open models, the economics flip.
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Tomasz Tunguz shared thisCome chat about databases and AI with us during Data Council! With our friends at MotherDuck and LanceDB! luma.com/dxsyixj5
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Tomasz Tunguz shared thisI remember growing up reading Sports Illustrated. There was a small column called “This Week’s Sign the Apocalypse Is Upon Us.” With all the dire predictions about AI, it’s important to also spend time recognizing the tremendous pace of innovation & the impact AI is having broadly. Here’s what it fixed, taught, and discovered in the last two weeks. In medicine - Mayo Clinic validated an AI that detects pancreatic cancer up to 3 years before diagnosis on routine CT scans. - J&J reported AI is halving the time to generate new drug development leads and cut clinical trial report preparation from 700 hours to about 15 minutes. In classrooms - A 2025 Harvard physics study found students using AI tutors learned more than twice as much in less time compared with traditional active learning classrooms. - Thailand upskilled 160,000 teachers in AI, impacting 3.3 million students. On land - Texas A&M demonstrated AI predicting outbreaks of destructive crop pests with ~88% accuracy in open fields. In the stars - Princeton researchers used AI to scan 83 million stars from NASA’s TESS telescope data and identified 10,091 new exoplanet candidates (11,554 total), sorting in seconds what would take astronomers years by hand. In disaster response - Hong Kong launched an AI flood forecasting system with 3D simulations, enabling faster preemptive emergency responses. Reversing the SaaSpocalypse - Atlassian reported Q3 FY26 revenue of $1.79 billion (up 32% year over year), with cloud revenue surging 29% to $1.13 billion. The company raised its full year growth outlook to ~24% from 22%, and shares soared more than 25%. - Twilio posted Q1 2026 revenue of $1.41 billion (up 20%), its highest revenue and gross profit growth rates in more than three years. The company raised its full year forecast. Clearly, there are many risks associated with AI, & it’s important to counterbalance them with some of the tremendous advances that are happening every week.
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Tomasz Tunguz shared thisI remember growing up reading Sports Illustrated. There was a small column called “This Week’s Sign the Apocalypse Is Upon Us.” With all the dire predictions about AI, it’s important to also spend time recognizing the tremendous pace of innovation & the impact AI is having broadly. Here’s what it fixed, taught, and discovered in the last two weeks.
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Tomasz Tunguz shared thisThree AI clouds reported earnings today. Only one hit 63% growth.
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Tomasz Tunguz shared thisThe inference market is the fastest growing market in the world & it’s splitting up. Each modality is developing its own inference stack. NVIDIA’s data center revenue was flat through 2022. Then ChatGPT launched. Three years later : 17x growth. Databases did the same thing. What started as one market fragmented into relational, document, key-value, graph, time series, vector, & others. Each category reflects different workload requirements : real-time transactions vs batch analytics, ACID compliance vs eventual consistency. The inference market is fragmenting for the same reason : workloads are different. Images & video are compute-heavy. Longer context windows demand more memory for KV cache. Edge devices have power constraints. A single architecture can’t optimize for all of them. The model ecosystem reflects this. A few dominant LLMs with long half-lives sit alongside 90,000+ image generation models on Hugging Face, with new variants appearing daily. Each model type has different serving requirements, which fragments the infrastructure. Today, we see these segments : Latency Tiers : Real-Time, Near-Real-Time, & Batch Latency defines three distinct segments. Real-time (sub-100ms) serves voice assistants, live translation, & autonomous vehicles. Users won’t wait, so infrastructure must be geographically distributed with dedicated capacity. Near-real-time (100ms-2s) covers chatbots, code completion, & search augmentation. Most LLM applications today operate here, where batching & queuing optimize throughput without degrading experience. Batch (seconds to hours) handles document processing & content generation at scale. Cost efficiency matters more than speed, so workloads run during off-peak hours on spot instances. Multimodal (Image, Video, Audio) The bottleneck shifts. For chatbots, the problem is memory. The model holds the entire conversation in its head, & that memory grows with every turn. For image & video generation, the problem is raw compute. A single image requires 50 sequential passes through the model. Different architectures, different constraints, different infrastructure. Edge (On-Device & On-Premise) Privacy requirements, connectivity constraints, & latency sensitivity push inference to edge devices. Mobile phones, industrial sensors, medical devices. Apple runs a 3-billion-parameter model on-device for Apple Intelligence. Tesla runs vision models on FSD chips drawing 72 watts. Quantized models, specialized chips, & limited memory create different optimization challenges than cloud inference. The database market produced Oracle, MongoDB, Databricks, & Snowflake. A $100B inference market fragmenting the same way creates room for similar winners.
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Tomasz Tunguz liked thisTomasz Tunguz liked thisJoining MotherDuck wasn't in my plans. But when the stars aligned, one of the reasons I felt sure it was the right choice was due to Margaret Lawrence Rosas' women in data dinners that I'd been lucky enough to have attended. The product speaks for itself, but man, so did those (about MotherDuck culture). Fast forward to now. We're taking over a museum from June 1-3 in SF and are hosting a FULL week of events (from an afterparty with Hex, Braintrust, and Reducto to panels, meetups, and talks). But MY favorite thing on the agenda... our Women in AI panel with Lexi Ross (Anthropic), Fernanda C. (Lovable), Jing Yang (Harvey), and Priya Soman (Notion) Join us at the Dive for a coffee, a stacked afterparty, or a panel to remember- https://lnkd.in/gMqZVh3z (And everyone deserves an events wizard like Carly Spoljaric)
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Tomasz Tunguz liked thisTomasz Tunguz liked thisToday, I'm pleased to announce Refactor 5! 🥳 New fund and new site! (links in the comments) Another $50M fund backing seed-stage hard tech founders. Nearly all Refactor funds have been $50M in size. I bring a new one online every 2.5 years and work with 20-25 companies per fund. Beyond lucky to have a small group of LPs, all US-based, who continue to back me and our companies fund after fund. 🙏🏽 That trust matters more than I can say. 5 funds, 10 years, $300M in AUM, 1 employee. That's the model, and I love it because I spend nearly all my time with founders like Gaurab Chakrabarti, MD, PhD and Sean Hunt at Solugen, John Gedmark at Astranis Space Technologies, Charlie Jarrott at @Hexium, Martin Hermez at Brelle, Dar Mehta and Yue (Kelsie) Zhao Zhao at Causal Labs, Alexander Ksendzovsky and Jonathan Pomeraniec at The Biological Computing Co. (TBC), Halen Mattison and Luke Neise at General Galactic, Rayhan Ahmed at Droyd, Aidin Aghamiri and Mohammad Javanbakht at Inferra, Charles Gertler and Samuel Melton at New Mantle, Ivana Muncie-Vasic at Vitra Labs, Jenny Lesser Herbach at Adventris Pharmaceuticals, Jake Adler at Pilgrim, Akash Bakshi at YourChoice Therapeutics, Danny Wells, and so many more. A quick reminder of what we do: Refactor has invested in the "hard but not impossible" since we launched. In fact, my first check as a GP after leaving a16z was in Astranis, which announced its Series E yesterday, and PathAI was acquired today by Roche! 💪🏽 Which categories? Aerospace, bio, critical materials, energy, robotics. The vast majority have AI at their core, so I'll add "physical AI" for those interested. I just call it hard tech cuz I'm old school. 😎 This is what VCs call a dry close. I'll bring Refactor 5 online next year as I continue to invest $1-2M checks from my current 4th fund. Rya Jetha kindly wrote a nice piece about me and the launch in Business Insider. Take a look in the comments. Founders: reach out on the new site's Contact page or drop me a DM. #BetterCallZal
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Tomasz Tunguz liked thisTomasz Tunguz liked thisToday, Dremio has agreed to join forces with SAP, pending regulatory approval. Together, we will deliver one open platform where agents reason over all enterprise data, decide and act. This acquisition will give us the scale and backing to accelerate our agentic vision at the speed enterprises demand. Once the transaction closes, SAP customers will be able to combine SAP application data with every other source of enterprise data on a single, open, governed platform. SAP and Dremio remain committed to open source Apache Iceberg, Apache Polaris, and Apache Arrow, the open standards enterprises rely on. Read the full story: https://lnkd.in/gitFtvgn
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Tomasz Tunguz liked thisExciting news!!Tomasz Tunguz liked thisToday, Dremio has agreed to join forces with SAP, pending regulatory approval. Together, we will deliver one open platform where agents reason over all enterprise data, decide and act. This acquisition will give us the scale and backing to accelerate our agentic vision at the speed enterprises demand. Once the transaction closes, SAP customers will be able to combine SAP application data with every other source of enterprise data on a single, open, governed platform. SAP and Dremio remain committed to open source Apache Iceberg, Apache Polaris, and Apache Arrow, the open standards enterprises rely on. Read the full story: https://lnkd.in/gitFtvgn
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Tomasz Tunguz liked thisTomasz Tunguz liked thisThe GV (Google Ventures) team is thrilled to co-lead Sierra's Series E! We’ve spent the last 3 years deepening our relationship with Bret Taylor and Clay Bavor - making customer and executive intros, sharing market insights, incessantly texting "Sad Ben Affleck" memes, and once hauling a 6-foot replica of the "Believe" sign from Ted Lasso across town to Sierra's office. Our conviction stems from a simple truth: Clay and Bret are product visionaries. Global brands pour nearly $1 trillion annually into marketing, yet when customers reach out for help, they often encounter long hold times, convoluted IVRs, and the frustration of yelling "representative" at their phones. Sierra is leveraging AI to transform that paradigm for the largest companies in the world, including 40% of the Fortune 50. What started as a way to improve customer satisfaction and resolution rates has evolved into something much larger. Today, Sierra’s Agent OS is helping companies drive sales, manage subscriptions, process payments, and transform contact centers. Sierra is turning one-off conversations into lasting customer relationships. Or, as Bret and Clay say, they are building "The Happy Customer Machine."
Experience
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Co-Author
Winning with Data
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Education
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Thayer School of Engineering
MEM Engineering Management
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Activities and Societies: George Revitz Fellow, Teaching Assistant for Numerical Methods
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Thayer School of Engineering
BE System Identification and Control Systems
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Activities and Societies: Dartmouth Formula Racing
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Dartmouth College
BA Mechanical Engineering
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Activities and Societies: Dartmouth Lightweight Crew (2nd Place US Nationals in the Lightweight 8), Vice President Fire & Skoal, Resident Advisor
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Northern Highlands
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Skills
Patents
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Network Node Ad Targeting
Issued US US 8438062
See patentA patent for using network topology to target ads on social networks.
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Social network user data advertising
Issued US US 8380691 B1
See patentA patent for using data from a social network and the interactions of a user to target ads on a social network.
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Open profile content identification
Issued US US 8341169 B2
See patentA patent on using the unstructured data fields within a social networking profile to improve ad targeting.
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Custodian based content identification
Issued US US 8321462 B2
See patentA patent on using the information within a social networking profile to improve ad targeting.
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Aviel Ginzburg
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Michael Fanfant
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Tony Corbin
I’m thrilled to share that White Star Capital is backing AMI - Advanced Machine Intelligence in their historic $1.03bn seed round 🚀 - Led by the legendary Yann LeCun and Alex LeBrun. AMI isn't building another LLM, they're building World Models. Why this matters: *Beyond Text: Grounded in JEPA architecture to solve physical-world problems. *Global Powerhouse: A dream team from Meta FAIR, OpenAI, and DeepMind. *Sovereign Tech: A credible European-led alternative to US Big Tech. Excited to be part of this journey along with the rest of the WSC team Eric Martineau-Fortin, Matthieu Lattes, Bérénice Moustial and Victoria Pozzi Rocco Belforti. 🌍✨ https://lnkd.in/eiCKZKSQ #VentureCapital #AI
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Paul Perrett
Big milestone for Firmable. We’ve raised $14m Series A led by Airtree. Sales has moved through a few big waves: intuition-led, CRM-led, data-led. We’re now entering the next one – intelligence-led sales. The opportunity isn’t just better data. It’s turning that data into clear direction and action, without adding more work for sales teams. That’s what we’re building at Firmable: a foundation of trusted external data, layered with intelligence that helps sellers know who to focus on and when. Led by Airtree, this round supports our expansion across Asia and into the US – and accelerates the build-out of AI agents that take the admin work off sales teams so they can focus on what they do best. Proud of the team, grateful to our customers and investors. We’re just getting started. Read the exclusive in the AFR. https://lnkd.in/gr66uknb Leigh Jasper | Tara Salmon | Karthik Venkatasubramanian| Chester Thompson| Chath Widanapathirana
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Lakshmi Shankar
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Neal Ghosh
Trying something new this week - a studio industry roundup with my take on what matters. The studio model is no longer an experiment being run in a handful of places. It is infrastructure being built across geographies, sectors, and institutional types. 5️⃣ stories from the past seven days: 1️⃣ OSS Ventures hit a EUR 40M first close on a EUR 75M follow-on fund -- capital raised specifically to back the 30 companies their studio created since 2019. The "build then fund" lifecycle is maturing. B'More Venture Studio with a similar thesis: studio operations first, then dedicated capital to scale what's working. 2️⃣ Delta40 raised $20M from 54 investors across 13 countries to launch Africa's first integrated venture studio and fund. The LP base is almost entirely DFIs and foundations. Impact capital is discovering the studio model as a deployment vehicle, something I seeing across geographies (conversations with Michael Bob Starr and Damias McDonald this week alone) 3️⃣ Start Holdings launched Start.vc out of NYC and Barcelona after a $200M EV infrastructure exit. Another operator-turned-studio-founder. This is the pattern we see quite often in our work at 9point8 -- experienced operators like Jason Goldsmith who've built and exited deciding the studio model is how they want to build next. 4️⃣ UBC HATCH admitted 10 new deep-tech spinouts for Winter 2026 -- mostly climate tech. University venture builders are quietly becoming one of the fastest-growing segments. Follow Evan Allen and Jaimie Testai to keep track of its rapid evolution. 5️⃣ The INVEST Act is advancing through the Senate. If passed, it expands qualifying VC fund size from $10M to $50M and loosens general solicitation rules for accelerator and university events. For studio-funds -- and for folks in the The Venture Studio Forum community tracking policy -- this could be the most significant capital formation legislation since the JOBS Act. If this roundup format is useful, I'll keep it going. What other noteworthy news hit your desk this week, and what stood out to you?
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Chris Gonzales
Summary: The venture firm CRV has raised $750 million for its 20th flagship fund, which will focus on investing in early-stage startups, particularly in the consumer and devtools sectors. Key takeaways: CRV's new fund is smaller than their previous one, but still received strong demand from investors. The firm has a history of successful investments, with 80 startups eventually going public since its founding in 1970. CRV is shifting its focus away from late-stage rounds, citing lower overall returns, and towards seed and Series A investments. Counter arguments: Some may argue that CRV's decision to not raise another late-stage fund could limit its opportunities for growth in the future. The success of the new fund will ultimately depend on the performance of the startups it invests in, which can be unpredictable in the volatile tech industry. #venturecapital #fundraising #startups https://lnkd.in/g8d-N9jX
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Jos White
Today Isembard announced a $50m Series A fundraise led by Union Square Ventures, less than a year after Notion Capital led their Seed round. 💥This is a company right at the intersection of AI & supply chain sovereignty & they’re exceeding even our most optimistic expectations. By the end of the year they will have 25 factories across the UK, US, Germany, France & Ukraine. 💥Isembard is rapidly scaling its network of AI-first factories for precision manufacturing at the same time as market demand is accelerating. Macro forces (reshoring, rising defence spend, concentration risk in Asia, and the growth of neo-primes) are structurally increasing demand for fast, local, flexible manufacturing that the current industry is unable to deliver on. 💥The innovation is in the way the company builds and franchises factories as a product with tightly integrated units of machines, software, robotics, & process intelligence that turn design files into certified components with speed & reliability. 💥Their AI software platform, MasonOS, connects all sites into a single operating system, replacing fragmented shops with standardised, high-performance industrial nodes & enabling real-time quoting, predictable delivery, & low defect rates. By owning the full production stack, Isembard delivers premium manufacturing performance with the scalability & flexibility of a software platform. 💥We are at the top of the AI hype cycle and there are understandable concerns about the ROI on the vast sums of money being invested into this new super-cycle. But, the ROI for Isembard is both clear and compelling. They will deliver components 10x faster and at 50% of the cost of current suppliers. They will also build a de-centralised, global network of factories to meet the growing demand for national or regional sovereignty. 💥This is a company with a clear vision to disrupt a massive, fragmented $1.8tn component manufacturing market. Today marks another huge stride towards that vision. And they are only just getting started. We’re thrilled to be on this journey with Alexander Fitzgerald & the team & we’re also excited to welcome Rebecca Kaden & USV into the investor base. Notion Capital Union Square Ventures Alexander Fitzgerald Rebecca Kaden Maximilian Eichler Stephen Millard Britt Mulder
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