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113 afleveringen, van nieuw naar oud
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European Defense Sovereignty Starts in the Factory: Stark’s Uwe Horstmann and Johannes Schaback
28 oktober 2026 · 44 min
Two years after its founding, Stark has roughly 700 employees and strike drones in the field in Ukraine. CEO Uwe Horstmann and CTO Johannes Schaback argue that the real lesson of that war is not any single weapon: the innovation ecosystem behind it is the wonder weapon. They explain why Stark designs every system for mass manufacturing from day one, runs 10 to 15 programs like a venture portfolio, and views the staff sergeant who operates a system as just as important as the general who buys it. Johannes recounts the publicly reported failed trial that became a forging moment, as engineers worked around the clock at a freezing test range until they landed three consecutive hits. They discuss NATO’s principles of responsible AI use and the hard-coded constraints in Stark’s autonomy stack. And Uwe lays out his next big idea: defense contracts structured like cloud contracts with surge capacity built in, so production itself becomes deterrence. Lees meer
Hosted by Pat Grady and Luciana Lixandru, Sequoia Capital
Chapters
0:00 – Introduction
1:03 – Billions in contracts in 18 months: Stark's four-part playbook
2:28 – The staff sergeant matters as much as the general, and wood beats plastic
7:42 – Why Europe is ready for a neo prime, and why procurement reform will last
11:45 – Startup DNA, venture-style programs, and "as complex as a washing machine"
16:27 – Born out of fire: the failed trial and the round-the-clock comeback
21:13 – Where Stark finds talent, and why defense is no longer off-limits
23:48 – Anatomy of a strike, from the wooden crate to the kill zone
27:22 – Vertical integration, multiple domains, and shifting left on manufacturing
32:53 – After the Hugging Face hack: guardrails on autonomous weapons
35:56 – Matching the primes on R&D and scaling to 700 people in two years
39:24 – Deterrence by contract, and Europe's next chapter with the US
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Inside the Robot Data Factory: Mecka's Josh Gao on Sensorizing Humans to Train Robots
20 oktober 2026 · 45 min
Robotics never got the internet's gift of free training data, so someone has to manufacture it. Josh Gao, founder and CEO of Mecka AI, runs one of the largest robot data factories, and he explains what that actually involves: custom baseball caps and tactile gloves because nothing off the shelf captures force, 100-gigabit upload lines to move hundreds of petabytes, and custom quality gates. Josh lays out the training recipe the industry is converging on (roughly a million hours of egocentric human data, tens of thousands of hours of robot data, and a few hours of in-domain teleop ) and why tactile and simulation data still have to enter the "data pot of soup." He argues the field is still orders of magnitude behind Tesla's FSD, which spent a decade on two degrees of freedom while a robot hand has dozens. His take: there won't be a single GPT-3 moment for robotics, but a steady unlock of commercial tasks, starting with constrained industrial work and ending, he hopes, with robots mining asteroids. Lees meer
Hosted by Sonya Huang, Sequoia Capital
0:00 – Introduction
1:46 – What Mecka is: pixels, actions and logic
2:45 – Is robot data economically feasible without the internet?
4:15 – Teaching robots about carbon life
5:27 – Cloud kitchens, stablecoins and the path to robotics
7:03 – Entering robotics with a fresh lens
8:45 – What egocentric data is and why Mecka bet on it
10:09 – The first pilot: aunties and uncles with a mobile app
10:42 – Force data and tactile gloves
11:55 – Inside the operations of a data factory
14:41 – Heat-mapping the taxonomy of human work
15:42 – Quality gates, fraud and the McDonald’s POV videos
17:44 – Earning a margin as a data intermediary
19:33 – Millions of hours vs. Tesla’s decade
20:55 – Why it isn’t binary: unlocking commercial tasks along the way
22:02 – Home data is plentiful; home robots are the hardest
23:24 – Useful robots can be deployed today
24:35 – When robotics gets an FSD-style flywheel
26:42 – Deployment diffus…
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David Silver and Lasse Espeholt of Ineffable Intelligence: A Superlearner for the Age of Experience
13 oktober 2026 · 1 uur 8 min
David Silver spent two years building AlphaGo on human data. When he removed human data altogether building AlphaGo Zero, the AI surpassed AlphaGo in under two days. He left DeepMind to run that same bet in pursuit of superintelligence. David and Lasse Espeholt, co-founders of Ineffable Intelligence, explain their plan to build a “superlearner”—an agent that starts knowing nothing and discovers science, mathematics, and language for itself by direct experience instead of through a pre-training run. Silver argues that human-language reasoning is a ceiling, not a foundation, that alignment via chain-of-thought monitoring is already reaching its limits, and that the science of how superintelligences coexist should be worked out in simulation before anything touches the real world. Espeholt describes the GPU cluster and the lineage from IMPALA and SEED RL that makes the experiment possible. Silver’s forecast: strong evidence within a year, superintelligence in three. Lees meer
Hosted by Sonya Huang, Sequoia Capital
0:00 – Introduction
1:09 – What held true from Go to today, and what the LLM era changed
3:35 – Why leave DeepMind to start a new lab
5:58 – Why "Ineffable" (and the secret second reason)
7:03 – Lasse's path: scaling RL at DeepMind and Google Brain
9:31 – Defining a super learner and first contact
12:35 – Super learners vs. LLMs that make discoveries
13:59 – Day to day: the RL stack, crucibles and human-journey milestones
16:13 – Don't breadcrumb the objective: simple rewards, emergent complexity
21:16 – What a crucible looks like
24:14 – Go: one agent is boring, two is infinite
25:41 – Will agents rediscover language?
27:22 – Removing human priors: AlphaGo to AlphaZero
32:05 – Keeping human bias out of the crucibles
33:35 – Confidence, timing and super forecasting
36:24 – Is compute the driver?
38:13 – The ceiling on simulation and Rich Sutton's objection
43:44 – Alignment and the science of superintelligence
47:45 – Monitoring agents that don't t…
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Google's AI Infrastructure Chief, Amin Vahdat, on the Physics & Economics of Frontier AI
6 oktober 2026 · 1 uur 4 min
At 100,000-accelerator scale, something fails multiple times an hour, which is why Google's Chief Technologist for AI Infrastructure Amin Vahdat thinks FLOPS is a vanity metric. The metric that matters is what he calls goodput: the useful work a workload actually delivers through real failures. Amin walks through the calculus that split the TPU line into 8i and 8t for the first time, why the TPU's core primitives haven't changed since v1, and how Google and DeepMind co-design in the same rooms, intercepting chip architectures mid-flight before tape-out. He explains why long-horizon agents are sending demand for CPUs and storage through the roof alongside accelerators, how optical circuit switches reroute light to a spare rack in milliseconds, and why Google would rather wait on a utility than build its own gigawatt. We also cover orbital data centers and the multi-megawatt rack of 2036. Lees meer
Hosted by Sonya Huang, Sequoia Capital
0:00 – Introduction
1:47 – What makes a data center an AI data center
5:30 – Goodput, not FLOPS: holding yourself accountable when something fails every hour
11:52 – Doubling token capacity every six months, and where the gains actually come from
15:32 – The TPU bet: from a contrarian call in 2013 to splitting 8i and 8t
23:30 – The case for and against co-design
26:11 – Shoulder to shoulder with DeepMind: intercepting chips mid-flight
34:16 – Long-horizon agents change the shape of the data center
37:50 – Optical circuit switching and the state of networking
42:35 – Power is the binding constraint: utilities, gigawatts, and sizing a data center
49:23 – Training vs. serving clusters, seven-year-old TPUs, and open standards
58:29 – Orbital data centers and the supercomputer of 2036
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Box's Aaron Levie: On Reinventing Yourself in the AI Age and Enterprise Diffusion
15 september 2026 · 1 uur 5 min
Starting a company is hard. Reinventing your company for AI as a public company with quarterly earnings results is even harder. Aaron Levie has pulled off the transition with Box and offers hard-won advice for founders. The cofounder and CEO of Box argues the value isn't only in the model; it's in the bridge from a model's raw capability to the actual workflow inside a bank, a law firm, or a pharma company. That's the case for the application layer, and Box is building it: an agent harness tuned so tightly to its own file system, permissions, and search that it beats handing the raw API to Claude or ChatGPT on both accuracy and latency. Aaron explains why token subsidies from the labs can't last, why you want a model-agnostic company routing your tokens rather than the one selling them, and why coding diffused fast while the rest of knowledge work won't. (There's no "give us your GitHub" for a sales rep.) His prediction: within five years, 90% of enterprise tokens go to work no human user ever initiated. Lees meer
Hosted by Sonya Huang, Sequoia Capital
0:00 – Introduction
1:55 – Are application companies the hottest neolabs?
6:56 – Will the labs move up the stack?
12:34 – Box and betting the company on AI
16:50 – Hero use cases: reading a million contracts and long-running agents
18:42 – Work slop: why AI code is embraced but AI content isn't
24:08 – Building Box's agentic harness and the evals that matter
27:23 – The state of the model race
29:25 – Open-weight model adoption in the enterprise
32:34 – Memory, continual learning, and what belongs in the weights
37:29 – Box Labs and systems of record in a world of agents
44:55 – Will chat be the dominant UI for enterprise AI?
48:00 – Why coding diffused fast and the rest of knowledge work hasn't
54:31 – Staying wired in, making a company AI-first, and what it takes to win
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Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
1 september 2026 · 52 min
Most public safety technology companies grow by collecting more data. Peregrine inverted the model: no sensors, no new data, a business built on connecting the data and information cities already own. Co-founders Nick Noone and Ben Rudolph received more than two dozen no's before San Pablo PD let them in the door in February 2018. Today, Peregrine powers law enforcement, emergency medical services, fire and rescue, and other services in more than 400 cities and communities globally. Nick and Ben explain their north star for data sovereignty, and discuss how Peregrine's philosophy and privacy-first approach to data access and ownership preserves individual privacy and cities' sovereignty. They walk through how AI and long-horizon agents are being deployed: a cold case agent that reproduced an exoneration detectives had reached by hand, a Wisconsin county that placed a suspect using cell records buried in 300GB of evidence, identifying threats to a synagogue, root-causing an escalation in weather-related incidents, and more. Lees meer
00:00 Introduction
02:07 What Forward Deployed Engineering Means
03:58 What Silicon Valley Gets Wrong
05:23 UNHCR, Dimagi And Downstream Data Problems
08:25 Why Cities, Why Safety
10:45 Two Dozen Nos And San Pablo PD
14:19 Building Through Defund The Police
18:16 The Inversion Of The Collection Model
21:20 Data Ownership And Governance
22:57 From Nice Search To Deep Analysis
29:59 Agents Writing The Integrations
31:45 The Cold Case Agent
35:02 The Anti-Network-Effect Proposition
38:40 Facial Recognition And Hard Decisions
40:48 Technology For The Underdogs
42:54 Trusting The Individual Contributor
48:50 Ten Thousand Cities
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Parallel’s Parag Agrawal: Building a New Web for AI Agents
25 augustus 2026 · 55 min
Parag Agrawal is making a bet that goes against two decades of web search: agents will query the web a thousand times more than humans ever have, and the infrastructure built around human clicks is wrong for them. The former Twitter CEO, now founder and CEO of Parallel Web Systems, explains why Parallel treats human click data as a bug and trains on agent feedback instead. He unpacks the counterintuitive choice to ship a search agent before a search engine, building an index incrementally, and how the new Turbo product cut agentic search to 200 milliseconds. But the problem Parag keeps returning to is economic: the ad-supported internet collapses when agents show up instead of people. His fix draws on Shapley values to pay content owners for the value their pages provide agents, with real dollars reaching publishers, he predicts, within 12 to 24 months. Lees meer
Hosted by Sonya Huang and Andrew Reed, Sequoia Capital
00:00 Introduction
03:25 What Is Web Search
05:17 Why Start a New Index
07:52 Search Agents First
10:17 Not a Neolab
13:14 Agents vs Google Search
19:38 Inside the Search Stack
28:59 Search Multipliers With Agents
30:21 Meeting Prep Agent Workflows
31:46 Quality Cost Latency And Turbo
32:42 Are Agents Overtaking Humans
34:28 Ads Model Meets Agent Web
37:20 New Incentives For Content
40:48 Shapley Values Attribution
47:46 Parallel Web And Future Vision -
Rich Sutton and Khurram Javed: Why AI Models Stop Learning, and How to Start It Again
18 augustus 2026 · 54 min
Rich Sutton, who helped pioneer reinforcement learning and wrote the seminal AI essay The Bitter Lesson, has now cofounded Oak Lab with his former student Khurram Javed. Their goal: to build agents that continuously learn from their own experience rather than from us. Rich doesn't think he holds a radical view: "I'm not weird. The field is weird." He says all learning is continual, and the field is the one that needed a new name for it. Rich and Khurram argue synthetic data is "a big mistake." Their "big world hypothesis" is that the world is massively more complex than any agent or simulator, so approximations have to be updated continuously rather than frozen at deployment. Rich calls LLMs an unanticipated scientific breakthrough, but says they represent roughly a quarter of intelligence. He says catastrophic forgetting is "totally curable" with the ideas behind their continual backprop algorithm. Khurram explains why the frontier labs can't follow: they sit in a local minimum where a new paradigm gets worse before it gets better. Their target, five to ten years out, is a trillion-parameter mind that keeps learning, stays coherent, and runs on 20 watts. Lees meer
Hosted by Sonya Huang and Alfred Lin, Sequoia Capital
00:00 Introduction
02:10 An AI winter, a cancer diagnosis, and the move to Alberta
07:07 Writing "The Bitter Lesson," and what people get wrong
09:53 Are LLMs a positive or a negative example of it?
11:03 Synthetic data is "just a big mistake," and the Big World Hypothesis
18:01 AlphaGo, human priors, and why prior knowledge and learning should be friends
22:37 "Their weights never change": do LLM assistants actually learn?
26:09 Babies, squirrels, and why no animal learns by supervised learning
32:02 Rockets, imagination, and where paradigm shifts come from
36:42 The Alberta Plan and its 12 steps
38:53 Catastrophic forgetting and the cure
43:43 Oak's biggest ambition: a self-maintaining mind
47:56 Why the big labs are stuck in a local minimum
49:13 If everyt… -
Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem
4 augustus 2026 · 47 min
Most people treat biology as a bespoke, messy science. Josh Meier and Matt McPartlon, co-founders of Chai Discovery, treat it as an engineering problem. They make the case that drug design obeys the bitter lesson: scale data, models, and compute, and the model can learn what a hand-built pipeline simply couldn't capture. The results are concrete: Chai-2 pushed de novo antibody design from a sub 0.1% hit rate to 16%, turning a needle-in-a-haystack search into something more like designing a key to fit a lock. Josh argues, counterintuitively, that biology is more verifiable than code, and explains why the goal should be more lab experiments, not fewer. Their bet: a design suite that collapses drug discovery from nine months to nine days, and arms the pharma industry rather than competing with it. Lees meer
Hosted by Pat Grady and Sonali Singh, Sequoia Capital
00:00 Introduction
01:52 From Discovery to Design
03:25 Protein AI Breakthroughs Timeline
06:04 Why Start in 2024
10:13 Diffusion Models Intuition
11:41 Building the Avengers Team
15:22 Hit Rates and Scaling Laws
25:01 Molecular CAD Vision
25:24 Faster Design Loops
26:32 Future Drug Discovery
28:37 Platform Business Model
31:14 Partnering Reality Check
33:44 Data Flywheel Explained
37:16 Staying Ahead at Scale
39:44 Culture and What's Next -
Building the Automated AGI Lab: Core Automation's Jerry Tworek and Rohan Anil
29 juli 2026 · 49 min
Jerry Tworek led reasoning at OpenAI, convinced that scaling reinforcement learning was the path to AGI. Rohan Anil co-led Gemini pre-training and built the Shampoo optimizer. Now they've teamed up at Core Automation on a contrarian premise: the transformer has carried us as far as it can, and the bottleneck to smarter systems is no longer scale — it's the architecture itself. The missing capability is continual learning, models that adapt at test time, which transformers can't do. In-context learning taps out fast (Codex needs compacting after ~20 minutes) and fine-tuning invites catastrophic forgetting. Rohan argues pre-training and RL should be optimized end-to-end, and that transformers spend computation inefficiently. They lay out why the largest labs won't chase alternatives while locked in the coding-agent race, and why building the world's most automated lab starts with automating kernel generation—the one place frontier models still lose to a high-taste human. Lees meer
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
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Factory's Matan Grinberg: The Coming ‘Dark Factory’ Where Software Builds Itself
21 juli 2026 · 52 min
Factory started building fully autonomous coding agents in April 2023, two years before enterprises were ready. Matan Grinberg now says this is indistinguishable from being wrong. The Factory co-founder and CEO explains how the company survived its "journey in the desert," including the decision to hand nearly all of its revenue back to customers when the product wasn't making developers obsessed. Matan makes the contrarian technical case that a model-agnostic harness beats the model-and-harness co-design that labs like OpenAI and Anthropic favor, because exposing a harness to many models keeps it from overfitting to any single one. He argues open-weight models like GLM will capture the majority of tokens by staying one generation behind the frontier at a fraction of the cost, and that CIOs will soon justify every incremental token the way they justify headcount. Looking ahead, he predicts 90% of coding tokens will run asynchronously—the "dark factory" where software builds itself. Lees meer
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
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Anthropic's Katelyn Lesse & Angela Jiang: Building an Ecosystem, not a Walled Garden
14 juli 2026 · 49 min
Katelyn Lesse and Angela Jiang lead the team building Anthropic's developer platform - the layer that both outside builders and Anthropic's own products run on top of. Angela frames the platform as a three-layer stack: knowledge, execution, and coordination. She argues the real leverage is what’s at the top: "strategies," or meta-harnesses that give each token a different job, from advising to executing to reflecting to memory. On the question of open ecosystem vs. walled garden, they say they aren't precious about owning the stack. Katelyn points to Anthropic's self-hosted sandboxes with partners like Modal, Vercel, and Cloudflare. Whether the work runs on Anthropic's infrastructure or someone else's, what really matters to them is that the architecture is sound. The deeper bet is standards: they hand skills and MCP to the whole industry, build connectors on the MCP spec, and help agents (Claude and non-Claude) work together. The one place they stay closed is model routing: they argue harnesses should be tuned to a model family, so they're designing for Claude rather than routing across models. Angela's frame for the ecosystem bet is electricity: transformative only because everyone could plug in, and no company wired it alone.Hosted by Sonya Huang and Lauren Reeder, Sequoia Capital Lees meer
00:00 Introduction
01:49 Two North Stars
02:27 External Builders And Primitives
03:54 What To Externalize
06:00 From Messages To Agents
08:19 Managed Agents Adoption
09:07 Three Layer Cake
10:22 Execution Harnesses Explained
11:09 Coordination Strategies Roadmap
12:13 Ecosystem Standards And Safety
15:39 Open Ecosystem Not Walled
17:12 Vertical Products And Form Factors
22:26 Claude Tag Under The Hood
26:04 Harness Best Practices
38:13 Token Costs And Whats Next
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Inside Zipline's Autonomous System: 140M Miles, Zero Incidents
7 juli 2026 · 55 min
The largest commercial autonomous system on earth isn't a robotaxi fleet — it's Zipline, which has flown 140 million autonomous miles with zero safety incidents. Co-founder Keller Rinaudo Cliffton and Eric Watson, who leads systems engineering and safety, explain why the drone itself is only 15% of the solution. The rest spans inventory management, air traffic integration, and engineering systems such as a dual flight computer failover protocol that recently saved a delivery mid-flight. They trace Zipline's path from launching blood delivery in Rwanda in 2016 (when drone delivery was illegal in the US) to a 51% reduction in maternal mortality in that country, a $550 million commercial diplomacy partnership with the State Department, and a cost curve that fell from $300 per delivery to $12. Zipline is now racing toward a million deliveries a day, and a quiet inflection point when autonomous delivery becomes cheaper than sending a car. Lees meer
Hosted by Alfred Lin and Pat Grady, Sequoia Capital
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Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
30 juni 2026 · 1 uur 10 min
Dylan Patel, founder of SemiAnalysis, argues the biggest gains in AI don't come from faster chips, they come from software-hardware co-design. Optimizing the model, the kernels, and the silicon together turns a 2x here and a 2x there into 100x. He explains why DeepSeek's experts were shaped for Nvidia's Hopper (and why TPUs struggle to run it), why OpenAI's sparser models and Anthropic's denser ones pull them toward different hardware, and why the so-called CUDA moat was never really about CUDA. Dylan breaks down InferenceX, his living benchmark that runs the latest models on over $50M of donated hardware daily, tracking a roughly 60x annual drop in cost per unit of quality. He makes the case that inference will be a bigger market than oil, that the compute crunch persists because models expand the value of useful work faster than compute grows, and why Jensen Huang is bankrolling neoclouds to engineer a multipolar world. Lees meer
Hosted by Shaun Maguire and Sonya Huang, Sequoia Capital
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Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin
24 juni 2026 · 45 min
Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and continual learning, which they call two sides of the same coin. Their contrarian premise: instead of stuffing ever-larger prompts into the context window or bolting on RAG, bake a team's knowledge directly into the model's weights, so it knows your company the way an employee of several years does. Lees meer
The payoff: matching or beating frontier models while consuming up to 100x fewer tokens. Working with partners like Microsoft, Notion, and Harvey, the team draws on roots in computational neuroscience and state-space architectures to attack what they see as the real bottleneck in AI — not raw intelligence, but memory and continual learning. In contrast to the frontier labs' race toward one ever-bigger model and AGI, Dan and Jessy imagine a world where everyone has their own model — privately trained, always learning, and good at the things you actually care about. The real ChatGPT moment for memory, they argue, is the day your model feels like an intern that genuinely got smarter overnight.
Hosted by Sonya Huang and Shaun Maguire, Sequoia Capital
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Simulating Humans at Scale: Simile's Joon Sung Park
16 juni 2026 · 39 min
The race to build superintelligence is producing models that keep getting better at objective problems, but not at behaving like actual people. Joon Sung Park, founder and CEO of Simile and creator of Stanford's "Smallville" generative agents study, argues that simulating human society requires a fundamentally different kind of model. He frames today's frontier models as the "CPU of intelligence"—rational, superhuman at problems with right answers—and Simile as creating the "GPU of intelligence," built to encode the diversity of people's values, preferences, and tastes. It simulated 1,000 Americans and predicted their behavior 85% as accurately as people reproduce their own answers. CVS uses it for concept testing; some customers simulate their own earnings calls. Joon's larger bet: a "CERN of human society" that could one day model bank runs, climate cooperation, or the early signals of a collapsing democracy. Lees meer
Hosted by Sonya Huang, Sequoia Capital
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Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness
11 juni 2026 · 51 min
The entire startup ecosystem is racing to build agent harnesses. Logan Kilpatrick, who leads Google AI Studio and the Gemini API, argues that scramble has a roughly 12-month shelf life. Models will absorb the scaffolding and run it natively, so the edge moves elsewhere. Google's own bet runs in parallel: a single agent harness, born from the Windsurf team and now called Antigravity, has become the connective tissue across search, the Gemini app, Cloud, and AI Studio — the role Gemini-the-model used to play. Logan makes the case that coding already feels like narrow superintelligence, and that "jagged" vertical superintelligence (in math, finance, and science) will arrive well before AGI. He argues Google's real goal is maximizing outcomes for users, not eyeball time. He unpacks Omni, the single model built to replace multiple separate systems Google once trained for text, audio, music, image, and video. His throughline: AI is an accelerant for human ambition, not a substitute for it. Lees meer
Hosted by Sonya Huang, Sequoia Capital
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LIVE: Jensen Huang on Building the Dynamo of the Intelligence Age
10 juni 2026 · 41 min
Jensen Huang, founder and CEO of NVIDIA, makes the case that computing is undergoing its biggest shift in 60 years: from retrieval, where data centers store files we look up, to generation, where every word, image, and video is produced in real time and customized for whoever is asking. He explains why NVIDIA's AI factories are the dynamos of this era: machines that take in electrons and send out tokens of intelligence, just as Siemens' dynamo once turned motion into electricity. Jensen frames intelligence as the third force to "cocoon" the planet after electricity and the internet. He describes the five-layer cake of AI investment—energy, chips, infrastructure, models, applications—and dismantles the fear that AI will erase jobs, using radiology and software engineering to show how automation raised labor demand instead of killing it. His bottom line: you won't lose your job to AI, but you might lose it to someone who uses AI. Lees meer
Hosted by Konstantine Buhler, Sequoia Capital
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Knowing What Your Customers Want, All the Time: Listen Labs' Alfred Wahlforss
2 juni 2026 · 40 min
Alfred Wahlforss, co-founder and CEO of Listen Labs, is building an AI agent that interviews your customers at a scale no focus group ever could—thousands of voice conversations at once, drawn from an audience of 30 million people. A year after launch, Listen serves hundreds of Fortune 100s to Startups including Microsoft, Google, NBC Universal, P&G, Anthropic, Cursor, and Cognition. Alfred explains the counterintuitive finding underneath it all: people are often more honest with an AI than a human interviewer, opening up to a non-judgmental entity that costs less and never makes them feel rushed. He walks through why interview transcripts—not credit card data or behavioral logs—turn out to be the richest fuel for predicting how customers will behave, how Listen back-tests its simulations to know which questions it can and can't answer, and why 80% of the company's engineering goes into building the right audience. As AGI makes building trivial, Alfred argues the scarce resource becomes knowing what to build. That's the loop Listen wants to own. Lees meer
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How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL
26 mei 2026 · 46 min
Cursor's Federico Cassano and Fireworks' Dmytro Dzhulgakov explain how they collaborated to build Composer as a specialized foundation model. The core insight: models have finite capacity in their weights, and allocating all those bits to the singular task of software engineering in Cursor frees the model to be both better at the task and far more efficient at inference. Rather than start from pre-training and work up, they took an unconventional top-down approach — mid-training and RL on top of an open-source base to get a useful model into users' hands fast, then specializing the model around real Cursor usage. With Fireworks providing distributed infrastructure, Composer delivers frontier-class coding performance with the speed of a much smaller model. Lees meer
Hosted by Sonya Huang, Sequoia Capital
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Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch
19 mei 2026 · 38 min
Jake Stauch, founder and CEO of Serval, is building a ServiceNow for the AI era. His most contrarian bet is that the product should look like boring old enterprise software, but with unlimited intelligence. Serval's architecture splits work between two agents: an admin agent that uses code generation to spin up workflows from natural language, and a help desk agent that can only act through the tools admins explicitly approve. Jake explains why his team uses OpenAI models for end-user interaction and Anthropic models for code generation, why new model releases sometimes have to be rolled back when prompt tuning breaks, and why he's not worried the foundation labs will come downmarket. He also makes the case for "fewer, better" hiring as the only durable moat in a world where products may need to be rebuilt every six months. Lees meer
Hosted by Pat Grady, Sequoia Capital
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Suno's Mikey Shulman: Everyone Can Make Music Now
13 mei 2026 · 35 min
Most music platforms assume you're a listener. On Suno, 90% of daily users make something. Founder and CEO Mikey Shulman explains why that flips the model: the act of creating IS the entertainment, with closer parallels to gaming and Claude Code than to Spotify. He breaks down the technical bets that got them here — modeling raw sound waves instead of encoding music theory, choosing autoregression over diffusion to prioritize full songs over crisp clips, and why music isn't a scale problem the way LLMs are. He also shares why partnering with Warner matters more than disrupting the record labels, what a truly interactive Coachella might look like, and why he thinks the digital music experience is finally due for its first real change in 25 years. Lees meer
Hosted by Sonya Huang, Sequoia Capital
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ElevenLabs' Mati Staniszewski: How Voice Becomes the Interface for Everything
8 mei 2026 · 27 min
Mati Staniszewski, co-founder and CEO of ElevenLabs, joins Sequoia partner Andrew Reed at AI Ascent 2026 to talk about how a four-year-old company built a frontier audio AI business with just over 400 people and over $400M in revenue. He explains why audio was overlooked in 2022 when the rest of AI was chasing text and images, why ElevenLabs chose to monetize from day one rather than raise indefinitely, and why he believes voice will be the primary interface for agents, robots, and the next generation of computing. Also: why emotional intelligence is the next frontier in voice, and what happens when one voice agent realizes it's talking to another. Lees meer
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Anthropic's Boris Cherny: Coding's Printing Press Moment
5 mei 2026 · 25 min
Boris Cherny, creator of Claude Code at Anthropic, joins Sequoia partner Lauren Reeder at AI Ascent 2026 to talk about where coding goes from here. He explains why he hasn't written a line of code in 2026, why he now ships dozens of PRs a day from his phone, and why he believes coding is effectively solved — at least for the code he writes. Also: why loops are the future, why he thinks Claude Code itself may be 100 lines of code a year from now, and why the invention of the printing press is the right analogy for what's about to happen to software. Lees meer
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Waymo's Dmitri Dolgov: 20 Million Rides and the Road to Full Autonomy
4 mei 2026 · 27 min
Dmitri Dolgov, co-CEO of Waymo, joins Sequoia partner Konstantine Buhler at AI Ascent 2026 to talk about the 20-year arc from the DARPA Grand Challenge to fully autonomous service in eleven cities and counting. He explains how Waymo persisted through every AV hype cycle by treating safety as the non-negotiable foundation, why exponential scaling is finally here (10 of Waymo's 20 million autonomous rides have happened in the last seven months), and how the Waymo Foundation Model — a multimodal world action model that powers the driver, the simulator, and the critic — actually works under the hood. Also: why Waymo is now 13x safer than human drivers, and the moment a Waymo detected a pedestrian behind a city bus by reading the LiDAR returns of their feet. Lees meer
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OpenAI's Greg Brockman: Why Human Attention Is the New Bottleneck
1 mei 2026 · 28 min
Greg Brockman, co-founder and president of OpenAI, joins Sequoia partner Alfred Lin at AI Ascent 2026 for a conversation that spans the full OpenAI stack. He explains why the company will never have enough compute, why he believes we're 80% of the way to AGI, and why the agentic coding tools that wrote 20% of your code last December are now writing 80% of it. Also: why human attention is becoming the scarcest resource in AI-augmented work, and what it might be like to one day run an organization of 100,000 agents. Lees meer
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Demis Hassabis on Building DeepMind, AlphaFold, and the Final Stretch to AGI
30 april 2026 · 27 min
Demis Hassabis, co-founder and CEO of Google DeepMind and 2024 Nobel laureate in chemistry for AlphaFold, joins Sequoia partner Konstantine Buhler at AI Ascent 2026 for a wide-ranging conversation about the path to AGI and what comes after. He explains why he believes AGI is achievable by 2030, why drug discovery could collapse from ten years to days, and why we should think of information, not matter or energy, as the most fundamental substance in the universe. Also: what Einstein would tell us about the limits of today's models, and why the next year or two will be critical for humanity. Lees meer
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Andrej Karpathy: From Vibe Coding to Agentic Engineering
30 april 2026 · 30 min
Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, and now founder of Eureka Labs) talks with Sequoia partner Stephanie Zhan at AI Ascent 2026 about what's changed in the year since he coined "vibe coding." He explains why he's never felt more behind as a programmer, why agentic engineering is the more serious discipline taking shape on top of vibe coding, and why we should think of LLMs not as animals but as ghosts: jagged, statistical, summoned entities that require a new kind of taste and judgment to direct. He also touches on Software 3.0, the limits of verifiability, and why you can outsource your thinking but never your understanding. Lees meer
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From SEO to Agent-Led Growth: Profound’s James Cadwallader
14 april 2026 · 31 min
James Cadwallader, co-founder and CEO of Profound, makes the case that we are living through the biggest platform shift in marketing history. The front door of the internet hasn't changed, but the visitor walking through it has. Where consumers once clicked blue links, AI agents now crawl the web on their behalf, synthesizing answers and steering purchase decisions at scale. Lees meer
James explains why Gemini, ChatGPT, and Claude all recommend brands differently, why mapping AI visibility onto traditional SEO is the wrong instinct, and why the real imperative is to equip a superintelligent agent with original insight it couldn't find anywhere else. He also digs into the dead internet theory – the possibility that human browsing could largely cease within three years – how AI advertising may become the most effective form the world has ever seen, and why agent-led marketing isn't just automation of the old work, but an entirely new capability.
Hosted by Sonya Huang, Sequoia Capital
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How Autonomous Labs Will Transform Scientific Research: Ginkgo Bioworks’ Jason Kelly
24 maart 2026 · 58 min
Jason Kelly founded Ginkgo Bioworks in 2008 with a simple but radical idea: DNA is code, and cells are programmable. Sixteen years later, AI is finally making that vision real in ways that could reshape science itself. Jason describes a landmark collaboration with OpenAI in which a reasoning model with access to a robotic lab beat the state of the art in biochemistry by 40% - not by being smarter than scientists, but by running experiments 24 hours a day and sharing data across a hundred parallel hypotheses simultaneously. He argues that the biggest inefficiency in science isn't intelligence, it's manual labor. Once AI helps scale research, the cost of discovery collapses and breakthroughs follow, with profound implications for biopharma, national competitiveness, and human health. Lees meer
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
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Greetings, Earthlings: Philip Johnston of Starcloud on Data Centers in Space
17 maart 2026 · 44 min
Philip Johnston, founder and CEO of Starcloud, explains why space will become the primary location for AI compute infrastructure within the next decade. After witnessing SpaceX's massive manufacturing scale at Starbase, Philip realized that declining launch costs would make space-based data centers cheaper than terrestrial ones. He breaks down the physics of heat dissipation in vacuum, the economics of solar power without atmosphere, and why the marginal cost of space infrastructure decreases while Earth-based costs increase. Philip previews a future where close to a trillion dollars per year in CapEx flows to space compute. And, yes, we get his take on aliens. Lees meer
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital.
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Physics Gets a Vote: Nominal Cofounders on Hardware Development in an AI World
10 maart 2026 · 41 min
Nominal’s cofounders (Cameron McCord, Jason Hoch and Bryce Strauss) realized that the new age of reindustrialization requires a new approach to hardware engineering and testing that’s closer to how software is developed. They founded Nominal with the insight that while SpaceX, Tesla, and Anduril built proprietary internal platforms for hardware testing, the thousands of new hardware entrants can't afford to replicate that work. Lees meer
Nominal serves as the system of record for hardware testing, helping companies move from PDF-based workflows to modern data infrastructure that catalogs telemetry from sensors producing millions of data points per second.
The platform enables engineers to author validation logic that follows hardware systems from initial testing through manufacturing and field deployment. We discuss their belief that all hardware companies will become physical AI companies, and why they think Nominal's role as the verification layer will be critical - because unlike a video game, physical products require rigorous validation before they enter the real world.
Hosted by: Alfred Lin and Sonya Huang, Sequoia Capital
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Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann
10 februari 2026 · 45 min
Will Brown and Johannes Hagemann of Prime Intellect discuss the shift from static prompting to "environment-based" AI development, and their Environments Hub, a platform designed to democratize frontier-level training. Lees meer
The conversation highlights a major shift: AI progress is moving toward Recursive Language Models that manage their own context and agentic RL that scales through trial and error. Will and Johannes describe their vision for the future in which every company will become an AI research lab. By leveraging institutional knowledge as training data, businesses can build models with decades of experience that far outperform generic, off-the-shelf systems.Hosted by Sonya Huang, Sequoia Capital
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What’s the Future of Vertical SaaS in an AGI World? Jamie Cuffe, CEO of Pace
3 februari 2026 · 52 min
Jamie Cuffe is solving one of AI's hardest problems: getting conservative, regulated industries to trust autonomous agents with mission-critical work. At Pace, he's building AI that replaces traditional BPOs in insurance, handling everything from email triage to claims processing with 50-75% cost savings. Drawing on his experience at Retool, Jamie emphasizes the importance of "closing the distance" with customers through forward-deployed engineering and being "the rock" that clients can rely on. He shares how focusing on top-tier insurance carriers and maintaining exceptionally high standards is enabling Pace to capture a meaningful share of the $400 billion BPO market while building a durable business model - at AI-native velocity. Lees meer
Hosted by Lauren Reeder and Pat Grady, Sequoia Capital
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Making the Case for the Terminal as AI's Workbench: Warp’s Zach Lloyd
27 januari 2026 · 48 min
Zach Lloyd built Warp to modernize the terminal for professional developers, but the rise of coding agents transformed his company's trajectory. He discusses the convergence of IDEs and terminals into new workbenches built for prompting and agent orchestration, and why he thinks "coding will be solved" within a few years, making human expression of intent the ultimate bottleneck. Zach explains how Warp competes against subsidized tools from Anthropic and OpenAI, and why the terminal's time-based, text-oriented format makes it perfect for managing swarms of cloud agents. Lees meer
Hosted by Sonya Huang, Sequoia Capital
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Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase
21 januari 2026 · 40 min
Harrison Chase, cofounder of LangChain and pioneer of AI agent frameworks, discusses the emergence of long-horizon agents that can work autonomously for extended periods. Lees meer
Harrison breaks down the evolution from early scaffolding approaches to today's harness-based architectures, explaining why context engineering - not just better models - has become fundamental to agent development.
He shares insights on why coding agents are leading the way, the role of file systems in agent workflows, and how building agents differs from traditional software development - from the importance of traces as the new source of truth to memory systems that enable agents to improve themselves over time.
Hosted by Sonya Huang and Pat Grady
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How Ricursive Intelligence’s Founders are Using AI to Shape The Future of Chip Design
14 januari 2026 · 37 min
Anna Goldie and Azalia Mirhoseini created AlphaChip at Google, using AI to design four generations of TPUs and reducing chip floor planning from months to hours. They explain how chip design has become the critical bottleneck for AI progress -- a process that typically takes years and costs hundreds of millions of dollars. Now at Ricursive Intelligence, they're enabling an evolution of the industry from “fabless” to "designless," where any company can create custom silicon with Ricursive Intelligence. Their vision: recursive self-improvement where AI designs more powerful chips, and faster, accelerating AI itself. Lees meer
Hosted by Stephanie Zhan and Sonya Huang
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Training General Robots for Any Task: Physical Intelligence’s Karol Hausman and Tobi Springenberg
6 januari 2026 · 1 uur 2 min
Physical Intelligence’s Karol Hausman and Tobi Springenberg believe that robotics has been held back not by hardware limitations, but by an intelligence bottleneck that foundation models can solve. Their end-to-end learning approach combines vision, language, and action into models like π0 and π*0.6, enabling robots to learn generalizable behaviors rather than task-specific programs. The team prioritizes real-world deployment and uses RL from experience to push beyond what imitation learning alone can achieve. Their philosophy—that a single general-purpose model can handle diverse physical tasks across different robot embodiments—represents a fundamental shift in how we think about building intelligent machines for the physical world. Lees meer
Hosted by Alfred Lin and Sonya Huang, Sequoia Capital
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Why the Next AI Revolution Will Happen Off-Screen: Samsara CEO Sanjit Biswas
16 december 2025 · 38 min
Sanjit Biswas is one of the rare founders who has scaled AI in the physical world – first with Meraki, and now with Samsara, a $20B+ public company with sensors deployed across millions of vehicles and job sites. Capturing 90 billion miles of driving data each year, Samsara operates at a scale matched only by a small handful of companies. Sanjit discusses why physical AI is fundamentally different from cloud-based AI, from running inference on two- to ten-watt edge devices to managing the messy diversity of real-world data—weather, road conditions, and the long tail of human behavior. Lees meer
He also shares how advances in foundation models unlock new capabilities like video reasoning, why distributed compute at the edge still beats centralized data centers for many autonomy workloads, and how AI is beginning to coach frontline workers—not just detect risk, but recognize good driving and improve fuel efficiency. Sanjit also explains why connectivity, sensors, and compute were the original “why now” for Samsara, and how those compounding curves will reshape logistics, field service, construction, and every asset-heavy industry.
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
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The Rise of Generative Media: fal's Bet on Video, Infrastructure, and Speed
10 december 2025 · 1 uur 2 min
fal is building the infrastructure layer for the generative media boom. In this episode, founders Gorkem Yurtseven, Burkay Gur, and Head of Engineering Batuhan Taskaya explain why video models present a completely different optimization problem than LLMs, one that is compute-bound, architecturally volatile, and changing every 30 days. They discuss how fal's tracing compiler, custom kernels, and globally distributed GPU fleet enable them to run more than 600 image and video models simultaneously, often faster than the labs that trained them. The team also shares what they’re seeing from the demand side: AI-native studios, personalized education, programmatic advertising, and early engagement from Hollywood. They argue that generative video is following a trajectory similar to early CGI—initial skepticism giving way to a new medium with its own workflows, aesthetics, and economic models.Hosted by Sonya Huang, Sequoia Capital Lees meer
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Why IDEs Won't Die in the Age of AI Coding: Zed Founder Nathan Sobo
2 december 2025 · 40 min
Nathan Sobo has spent nearly two decades pursuing one goal: building an IDE that combines the power of full-featured tools like JetBrains with the responsiveness of lightweight editors like Vim. After hitting the performance ceiling with web-based Atom, he founded Zed and rebuilt from scratch in Rust with GPU-accelerated rendering. Now with 170,000 active developers, Zed is positioned at the intersection of human and AI collaboration. Nathan discusses the Agent Client Protocol that makes Zed "Switzerland" for different AI coding agents, and his vision for fine-grained edit tracking that enables permanent, contextual conversations anchored directly to code—a collaborative layer that asynchronous git-based workflows can't provide. Nathan argues that despite terminal-based AI coding tools visual interfaces for code aren't going anywhere, and that source code is a language designed for humans to read, not just machines to execute. Lees meer
Hosted by Sonya Huang and Pat Grady, Sequoia Capital
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How End-to-End Learning Created Autonomous Driving 2.0: Wayve CEO Alex Kendall
18 november 2025 · 42 min
Alex Kendall founded Wayve in 2017 with a contrarian vision: replace the hand-engineered autonomous vehicle stack with end-to-end deep learning. While AV 1.0 companies relied on HD maps, LiDAR retrofits, and city-by-city deployments, Wayve built a generalization-first approach that can adapt to new vehicles and cities in weeks. Alex explains how world models enable reasoning in complex scenarios, why partnering with automotive OEMs creates a path to scale beyond robo-taxis, and how language integration opens up new product possibilities. From driving in 500 cities to deploying with manufacturers like Nissan, Wayve demonstrates how the same AI breakthroughs powering LLMs are transforming the physical economy. Lees meer
Hosted by: Pat Grady and Sonya Huang
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How Google’s Nano Banana Achieved Breakthrough Character Consistency
11 november 2025 · 44 min
When Google launched Nano Banana, it instantly became a global phenomenon, introducing an image model that finally made it possible for people to see themselves in AI-generated worlds. In this episode, Nicole Brichtova and Hansa Srinivasan, the product and engineering leads behind Nano Banana, share the story behind the model’s creation and what it means for the future of visual AI. Lees meer
Nicole and Hansa discuss how they achieved breakthrough character consistency, why human evaluation remains critical for models that aim to feel right, and how “fun” became a gateway to utility. They explain the craft behind Gemini’s multimodal design, the obsession with data quality that powered Nano Banana’s realism, and how user creativity continues to push the technology in unexpected directions—from personal storytelling to education and professional design. The conversation explores what comes next in visual AI, why accessibility and imagination must evolve together, and how the tools we build can help people capture not just reality but possibility.
Hosted by: Stephanie Zhan and Pat Grady, Sequoia Capital
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OpenAI Sora 2 Team: How Generative Video Will Unlock Creativity and World Models
6 november 2025 · 1 uur
The OpenAI Sora 2 team (Bill Peebles, Thomas Dimson, Rohan Sahai) discuss how they compressed filmmaking from months to days, enabling anyone to create compelling video. Bill, who invented the diffusion transformer that powers Sora and most video generation models, explains how space-time tokens enable object permanence and physics understanding in AI-generated video, and why Sora 2 represents a leap for video. Thomas and Rohan share how they're intentionally designing the Sora product against mindless scrolling, optimizing for creative inspiration, and building the infrastructure for IP holders to participate in a new creator economy. The conversation goes beyond video generation into the team’s vision for world simulators that could one day run scientific experiments, their perspective on co-evolving society alongside technology, and how digital simulations in alternate realities may become the future of knowledge work. Lees meer
Hosted by: Konstantine Buhler and Sonya Huang, Sequoia Capital
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Nvidia CTO Michael Kagan: Scaling Beyond Moore's Law to Million-GPU Clusters
28 oktober 2025 · 42 min
Recorded live at Sequoia’s Europe100 event: Michael Kagan, co-founder of Mellanox and CTO of Nvidia, explains how the $7 billion Mellanox acquisition helped transform Nvidia from a chip company into the architect of AI infrastructure. Kagan breaks down the technical challenges of scaling from single GPUs to 100K and eventually million-GPU data centers. He reveals why network performance—not just compute power—determines AI system efficiency. He discusses the shift from training to inference workloads, and his vision for AI as humanity's "spaceship of the mind," and why he thinks AI may help us discover laws of physics we haven’t yet imagined. Lees meer
Hosted by Sonya Huang and Pat Grady
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Securing the AI Frontier: Irregular Co-founder Dan Lahav
21 oktober 2025 · 44 min
Irregular co-founder Dan Lahav is redefining what cybersecurity means in the age of autonomous AI. Working closely with OpenAI, Anthropic, and Google DeepMind, Dan, co-founder Omer Nevo and team are pioneering “frontier AI security”—a proactive approach to safeguarding systems where AI models act as independent agents. Lees meer
Dan shares how emergent behaviors, from models socially engineering each other to outmaneuvering real-world defenses like Windows Defender, signal a coming paradigm shift. Dan explains why tomorrow’s threats will come from AI-on-AI interactions, why anomaly detection will soon break down, and how governments and enterprises alike must rethink defenses from first principles as AI becomes a national security layer.
Hosted by: Sonya Huang and Dean Meyer, Sequoia Capital
00:00 Introduction
03:07 The Future of AI Security
03:55 Thought Experiment: Security in the Age of GPT-10
05:23 Economic Shifts and AI Interaction
07:13 Security in the Autonomous Age
08:50 AI Model Capabilities and Cybersecurity
11:08 Real-World AI Security Simulations
12:31 Working with AI Labs
32:34 Enterprise AI Security Strategies
40:03 Governmental AI Security Considerations
43:41 Final Thoughts -
Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone
14 oktober 2025 · 45 min
Ping Wu built Google's contact center business before becoming CEO of Cresta, where he's pioneering a unique approach to contact center transformation. Rather than full automation Ping advocates a dual approach, automating what's ready while using AI to assist humans with the rest. He makes the case for an abundance mindset—imagining new customer experiences like talking to airline apps or turning synchronous interactions asynchronous. Ping breaks down the technical challenges of deploying Contact Center AI at scale, from solving latency to orchestrating 20+ models in real-time. Sequoia’s Doug Leone shares his framework for building AI companies at speed and why he believes we're at the front end of an Industrial Revolution 2.0. Lees meer
Hosted by: Sonya Huang and Doug Leone, Sequoia Capital
00:00 Introduction
01:13 The Evolution of Contact Centers
02:05 Debating AI's Impact on Call Centers
04:07 Challenges and Opportunities in Contact Centers
08:14 Technological Waves in Contact Centers
11:10 AI vs Human Agents: The Future
13:35 Customer Experience and AI
16:33 The Role of Data in AI Automation
19:05 Competing in the AI Space
22:34 Building a Company in the AI Era
24:05 Instilling Speed in AI Companies
24:53 Management Experience and Growth Challenges
26:01 Identifying Leadership Potential
26:37 Cresta's Leadership Transition
28:34 Future Goals for Cresta
29:56 AI Market Cycles and Investment
35:38 Cresta's Technical Stack
45:11 AI's Impact on Business Communication
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Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent
30 september 2025 · 1 uur
As CTO of Block, Dhanji Prasanna has overseen a dramatic enterprise AI transformation, with engineers saving 8-10 hours a week through AI automation. Block’s open-source agent goose connects to existing enterprise tools through MCP, enabling everyone from engineers to sales teams to build custom applications without coding. Dhanji shares how Block reorganized from business unit silos to functional teams to accelerate AI adoption, why they chose to open-source their most valuable AI tool and why he believes swarms of smaller AI models will outperform monolithic LLMs. Lees meer
Hosted by: Sonya Huang and Roelof Botha, Sequoia Capital
Mentioned in the episode:
goose: Block’s open-source, general-purpose AI agent used across the company to orchestrate workflows via tools and APIs.
Model Context Protocol (MCP): Open protocol (spearheaded by Anthropic) for connecting AI agents to tools; goose was an early adopter and helped shape.
bitchat: Decentralized chat app written by Jack Dorsey
Swarm intelligence: Research direction Dhanji highlights for AI’s future where many agents (geese) collaborate to build complex software beyond a single-agent copilot.
Travelling Salesman Problem: Classic optimization problem cited by Dhanji in the context of a non-technical user of goose solving a practical optimization task.
Amara’s Law: The idea, originated by futurist Roy Amara in 1978, that we overestimate tech impact short term and underestimate long term.
00:00 Introduction
01:48 AI: Friend or Foe?
03:13 Block's Journey with AI and Technology
04:47 Block's Diverse Product Range
07:04 Driving AI at Block
14:28 The Evolution of Goose
27:45 Integrating Goose with Existing Systems
28:23 Goose's Learning and Recipe Feature
29:41 Tool Use and LLM Providers
31:40 Impact of AI on Developer Productivity
34:37 Block's Commitment to Open Source
39:09 Future of AI and Swarm Intelligence
43:05 Remote Work at Block
45:15 Vibe Coding and AI in Development
48:43 Making Goose More Access…
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Why Businesses Are Rejecting the AI They’ve Asked For: Agency CEO Elias Torres
23 september 2025 · 45 min
Elias Torres has been building AI systems since 1999, from chatbots at IBM to co-founding Drift and now Agency. He believes businesses are caught in an expectation mismatch—demanding AI while rejecting it due to imperfection anxiety. Drawing from his experience scaling HubSpot, Elias explains why human-led customer experience doesn’t scale and how Agency is building AI-first solutions that work autonomously. His contrarian approach focuses on the back-end customer experience rather than front-end AI SDRs, aiming to “deprogram the entire business world” from inefficient human-dependent processes. Lees meer
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital
Mentioned in the episode:
Lookery: David Cancel’s first startup that Elias joined after IBM; shut down in 2009
Performable: Elias and David’s second startup, acquired by HubSpot in 2011
Drift: Elias and David Cancel’s third startup, merged with Salesloft in 2024
Klaviyo: B2C CRM company started by Andrew Bialecki after working with Elias at HubSpot
Secret: Short-lived anonymous messaging app that inspired one of Drift’s early iterations
Tatajuba: Kitesurfing destination in Jericoacoara, Brazil where Elias (briefly) considered retirement
00:00 Introduction
01:50 AI and Customer Expectations
03:36 Managing Emails with AI
07:21 Elias' Personal Journey
11:27 Early Career
14:28 Joining HubSpot and Scaling Challenges
16:31 Hiring Exceptional Talent
18:53 Founding Drift
20:27 Pivoting to Success with Drift
21:41 Drift's Chatbot Innovation
22:09 Challenges and Limitations of Drift
22:37 The Struggle with Customer Knowledge
23:09 Scaling Challenges and Lessons Learned
25:58 Rediscovering Purpose Post-Drift
28:55 The Birth of Agency
29:42 AI's Role in Customer Experience
35:13 Building a Sustainable Business Model
37:06 The Vision for Agency
38:22 Challenges and Opportunities with AI
41:22 Deprogramming and Embracing Change
43:23 Optimism for the AI Future
44:15 Closing Thoughts -
Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI
9 september 2025 · 43 min
Thomas Wolf, co-founder and Chief Science Officer of Hugging Face, explains how his company is applying the same community-driven approach that made transformers accessible to everyone to the emerging field of robotics. Thomas discusses LeRobot, Hugging Face's ambitious project to democratize robotics through open-source tools, datasets, and affordable hardware. He shares his vision for turning millions of software developers into roboticists, the challenges of data scarcity in robotics versus language models, and why he believes we're at the same inflection point for physical AI that we were for LLMs just a few years ago. Lees meer
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital