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this is why i wish the tech/sci fi film canon were wider. im tired of references to Her and Bladerunner and The Social Network etc. in 2026 you should be watching: -Demonlover -Until the End of the World -Videodrome -World on a Wire -Solaris -The 10th Victim -Megalopolis -Stalker -Run, Lola, Run -Seconds -and so many more…
films set the ideas and narratives that kick-off passions and careers
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when we think about ai in the physical world, we usually default to thinking about humanoids or self-driving cars or or models helping scientists discover new drugs and materials. but there’s another version of physical-world ai that i think deserves more attention: using intelligence to orchestrate all the benign-seeming things that have to happen for something to get built. which is especially important because the physical world is this wildly chaotic unpredictable place. what happens when the physical world refuses to cooperate. your shipment falls off a ship. or a strait closes. where, exactly, can an agent intervene? this is the problem we get into in my conversation with @askvladi, cofounder of lio, and @seema_amble. lio builds ai agents for procurement, in other words the work of figuring out what a company needs to buy, finding suppliers, negotiating terms, and making sure the right things arrive. when you’re building an aircraft or a data center, those decisions connect engineering, logistics, and finance in very consequential ways. vlad’s answer to the question of how to wrangle the physical world was about probability. suppliers have different records of reliability and routes have different risks. understanding those things in concert changes what you should buy / what you should pay: a cheap component that holds up an entire project can become a very expensive component. this all requires a much richer understanding of the world than the price and delivery date sitting in an enterprise database. i think this is a very compelling application of ai. a lot of our ability to build more ambitious things depends on making thousands of these decisions well. robots justifiably get a lot of attention; getting everything required to build them in the same place at the right time is just as important!
Lio co-founder and CEO Vladimir Keil joins a16z's Seema Amble and Elena Burger to discuss where AI-native startups have an advantage when incumbent software companies already own the customer, the data, and the system of record: Their answer comes down to the work that happens outside those systems. In procurement, a final price in an ERP can hide hundreds of emails, spreadsheets, supplier conversations, engineering analyses, and decisions across legal, finance, and operations. Vlad explains how Lio uses multi-agent systems to take on more of that end-to-end work, from sourcing and RFQs to negotiation, shipment tracking, and invoices. They also discuss how enterprises learn to trust agents with increasingly consequential decisions, why the last 20% of an internal AI build can require most of the effort, and what happens when both buyers and suppliers have agents working on their behalf. 00:58 Why AI startups still beat incumbents 04:19 The hidden work behind an $8K line item 06:18 Retrieval, process, policy, principal 09:27 The incumbent's internal conflict 14:48 What procurement actually looks like 21:13 Procurement at Boeing-scale 28:03 A bolt order, end-to-end 37:57 What a durable vertical AI company looks like 44:46 When both sides deploy agents YouTube: piped.video/OTQ-lFsq7zA @askvladi @seema_amble @VirtualElena
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my proposal for “pacing the frontier” is that model releases should be limited to 2x/year and coordinated as staggered seasonal collections, like fashion week.
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openai actually has the right idea with a september dev day but the other labs dont sufficiently respect the calendar
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so excited to see this launch. @eriktorenberg and @david__booth have been laser-focused on networks and founder ecosystems for their entire careers, and the startup world is better because of it. @cosign is the culmination of this work, but also still just the beginning...
Excited to introduce @Cosign: the curated professional network for the startup community: cosign.co Our goal is to create the following: - A comprehensive startup directory of investors, companies, and operators, including what they worked on and who they worked on it with. - Cosign graph: Who shaped your career? Who were you actually in the trenches with? Who would work with you again? Who thinks you’re someone to watch? - Durable reputation: Great endorsements happen every day on X and disappear into the feed. Cosign attaches those signals permanently to people and companies. - Discovery: Who are the best fintech angels? Which AI companies should I watch? Who are the best designers? - Intent network: Privately signal “I’d invest in them,” “I’d hire them,” “I’d work with them,” or eventually even “I’d acquire this company.” Match people when interest exists on both sides. Imagine if Wikipedia, LinkedIn, and OG AngelList had a baby. Though Cosign is a community, not a business. In order to join, you need to be cosigned. Or you can apply directly. David Booth and I started this idea 7 years ago but didn’t have the firepower to make it work. Now we do. No one has really touched LinkedIn in 20 years. Excited to take a swing. cosign.co
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all the world’s a sim / and all the men and women merely agents
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ncaa but for h16n / uatx / thiel fellows / yc / speedrun / 1517 etc who's building this?
do you think that the a16z college and the joe lonsdale college are football rivals
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in 1882, thomas edison's pearl street power station (the first commercial power plant in the us) began serving 59 customers in lower manhattan. that same fall, mit introduced the country's first electrical engineering curriculum. this co-evolution of enterprise on one side, and pedagogy on the other is one of the many forces that brought america firmly into the industrial era in the late 1800s/early 1900s. i think this is useful context for the conversation between @eriktorenberg @bhorowitz @gaganbiyani about what education for the ai era should look like. the institutions we now treat as permanent fixtures had to make decisions about emerging technologies and whether it was worth teaching a field whose applications were still being discovered. in this pod announcing horowitz andreessen academy (@theacademysf), ben makes the case that a technological change on the scale of ai should prompt a similarly ambitious rethinking of education. one of my favorite details is ben recounting a conversation with stanford's dan boneh about making problems hard enough that students *need* ai to solve them. that seems like a much more interesting educational ambition than spending the next decade trying to establish whether someone used a chatbot on their homework. there's something very regressive about knowing young people have access to tools that can help them do unprecedented things, and then evaluating them entirely on what they can do without them. we should all be excited to see what happens when a school like haa takes the opposite approach, and prepares students for the machine age.
Gagan Biyani with Erik Torenberg and Ben Horowitz on HAA: The Horowitz Andreessen Academy HAA is a private, full-time, in-person school in San Francisco for young people coming out of high school. Its mission is to nurture the best young people in the world, and equip them with the tools to shape it. The Industrial Revolution rewrote how we train young people. It's time for a new model for the AI era. HAA is project-based – less lecture time, more time with tools and AI, structured social life, co-ops/internships, with students embedded alongside working adults. Founding Partners include Anduril, Anthropic, Coinbase, Google, Meta, NVIDIA, OpenAI, Palantir, Replit, and Stripe. It's the best time in history to be 18. The vision is grads with careers they love or their own companies founded, and hopefully other schools copying the model down the road. 0:55 Why a16z is backing a school 4:40 Why other college alternatives failed 6:55 AI is this era's Industrial Revolution 9:35 The model: live in SF, intern at top startups 12:10 Ben: the best time in history to be 18 15:25 No big idea at 18? Join someone who has one 17:40 People skills come from reps, not lectures 23:15 Why it has to be San Francisco 26:45 Why it's a separate, for-profit company 31:00 Every curiosity becomes a project 33:30 Main character or NPC? 35:15 You can't learn to be a CEO from a book 37:30 Picking a problem, and failing the right way 40:30 What success looks like in five years YouTube: piped.video/Z4x71naDx1Q @gaganbiyani @bhorowitz @eriktorenberg
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one of the more reliable rules of the internet is that if a sufficiently committed group of people in silicon valley decides something is good/bad/going to change the world/kill us all, you will inevitably learn all about it (and then form an opinion about it yourself). this has been a law that governs everything from ai discourse to health/biohacking to what you eat to how to track your body’s functions. i think people are only just beginning to appreciate just how culturally influential the bay area is. a funny byproduct of this phenomenon is that sf people will sometimes take credit/co-opt cultural trends they aren’t even directly responsible for. so i talked with @being_on_line about how to disentangle a true bay area export from a hijacked narrative, and more generally how to figure out what is actually happening in the world. an unsurprisingly tall task. sf sometimes encounters a subculture years after it’s been incubated, and immediately claims and mainstreams it. chinese peptides are a particularly good example: earlier this year, a lot of writng/blogging about peptides attempted to paint it as a sf-exported phenomenon, but it was really a trend that started in the south and midwest, among the bodybuilding community. a 2013 DOJ case even documents an illinois distributor importing them in 2010–11 for the bodybuilding market. sf is ofc capable of homegrown culture (and productive neuroses). last year, nat friedman's plasticlist project spent about $500k over six months testing 296 food products for 18 plastic-associated chemicals. (specifically chemicals like phthalates and bisphenols). i personally believe this kind of citizen science / gonzo testing is only going to become more in-demand as people increasingly care about food provenance/toxins. i think this is why these trends are worth paying attention to even when parts of them look ridiculous. a small group can change what gets tested, funded, packaged, and eventually made easy for everyone else to do. i also don't think the endpoint of the current body-optimization boom is that everyone gets conventionally hotter and starts to look like clavicular. i think people are going to do increasingly specific, strange things to themselves, depending on what they personally think is worth optimizing (an example of this is that people are now working on wearables to achieve the equivalent of a full night’s sleep in four hours). full convo below!
How do you differentiate a real cultural shift from a manufactured one? Cyber ethnographer Ruby Justice Thelot studies culture through TikToks. He scores thousands of them by category and sentiment to measure what people do versus what they post. In this conversation with a16z's Elena Burger, they point that method at the wellness boom: why Silicon Valley gets credit for a peptide trend it did not start, what 400 years of thinness reveals about what we value, why the people who quantified everything are turning to energy healing and acupuncture, and why the body is the last thing left to optimize once AI handles the rest. 00:00 Intro 01:45 How to spot a fake trend 04:55 Silicon Valley did not invent peptides 10:15 The ten-to-one rule of trends 12:12 Why you know Ozempic and not the company 14:00 How to determine a trend's life stage 16:31 Why watching something feels like doing something 19:22 How thin became a sign of intelligence 23:08 How a beauty standard goes mass market 25:10 The body ideal follows the economy 26:46 Why biohacking went mainstream 29:28 When the Bay Area decides something is bad 33:14 Two signs a trend has peaked 36:38 Your tracker can make you feel worse 39:15 Sleeping four hours and feeling rested YouTube: piped.video/watch?v=HKZdte6e… @being_on_line @VirtualElena
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greg brockman says “we’re now in the AGI era.” one of the most interesting things about this conversation with @bhorowitz and @eriktorenberg is how long he’s been thinking about when that would happen. at the beginning of the pod, @gdb recalls doing some math on compute with ilya around 2016/2017. following the trajectory of moore’s law, they thought agi might be about 15 years away. if you were willing to build enormous supercomputers and spend hundreds of billions of dollars, maybe you could get there in 10. the accelerated scenario they were envisioning a decade ago is roughly the one we’re living through now. the faster timeline depended on people deciding to build an enormous amount of infrastructure. greg describes the present moment as a lot of long-running forces coming together: “it kind of makes sense it’s happening now.” im the kind of person who resists the idea that it’s possible to predict the future, but if you were reading the right research papers 10 years ago, there were a lot of things you could extrapolate out and be roughly right about a decade later. brockman remembers openai discussing agents that could use a screen, keyboard, and mouse at an offsite in napa in 2015. he also points back to 2017/2018-era ideas for how humans might supervise systems that are smarter than they are. put differently, people were thinking about app-layer innovations like computer-use, and ai safety long before capabilities existed. greg now thinks astra is reasonably described as agi, while acknowledging that its abilities remain uneven. in a recent essay of his titled “the defenders window” he describes safety requirements during training and evaluation, and getting powerful defensive tools into the hands of organizations before comparable capabilities spread to attackers (there is now a $ 1bn fund for this, seeded by oai). a personal illustration of this is his own website. after the hugging face incident, greg asked an agent to check his simple blog and got back 13 security vuln findings. then it went into his cloudflare dashboard, changed settings, migrated the site, checked its work, and scheduled a follow-up to finish the email protections. there was still a bunch of ordinary preparation to do on the personal website of someone who had spent a decade thinking about agi. which is kind of funny. you can have a pretty good sense of when the technology/agi will arrive and still have an enormous amount of work to do to get the world ready for it. greg’s account brings those two timescales together: the decade spent building toward this moment, and the relatively shorter window to act on what is now possible.
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full pod here
Greg Brockman: "We're now in the AGI era." Ten years ago, OpenAI worked out the compute curves and landed on fifteen years to AGI, or ten if the world was willing to build the machines and spend the hundreds of billions to do it. In 2026, GPT-6 Astra manages 24 hours of coherent operation, 10,000 agents worked together to solve Navier-Stokes, and a model ingeniously chained together exploits to break containment at Hugging Face. @gdb joins @bhorowitz and @eriktorenberg on what the AGI era asks of us: why safety and alignment now set the pace, what happens to work, and why AI sentiment is lowest in the country building it. 00:00 Intro 00:52 15 years, or 10 if you spend enough 02:24 Pacing the frontier 03:55 Safety ideas from before the models 08:42 Lessons from Hugging Face 10:20 The defender's window 12:46 10,000 agents on Navier-Stokes 14:50 Formally verifying all software 17:10 Cancelling his holiday for GPT-3 18:42 Codex found 13 holes in 15 minutes 20:41 Why Astra earned the GPT-6 title 24:25 Employment keeps going up 29:39 America has the lowest AI sentiment 31:10 The benefits don't make the news 33:26 Banning data centers exports them 35:50 $1 billion for frontline defenders 38:15 Astra cleared the bar for AGI 40:18 1.5 billion people churned ChatGPT 43:25 Killing Sora 47:45 The AGI era YouTube: piped.video/watch?v=IJn8cagM…
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one of my favorite weekly habits is reading lunch with the ft. so i made a world of lunches every single "lunch with the ft" mapped, built in 3 hours with astra and minimal supervision lunch-atlas.pages.dev/
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some takeaways from running a sota llm on a decade worth of lunches: - noted X anon @litcapital had the 4th most expensive meal on record - noted economist and MMT enthusiast @StephanieKelton had one of the cheapest - the most common restaurant was clarke's in london - and perhaps unsurprisingly, london was the most common city
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the datacenter-themed chanel spring summer ‘17 RTW collection. you couldn’t do this kind of thing today, they’d cancel you.
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pleased to announce jalapeno chip early access at the a16z office
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in true borderless fashion, i just ran into @GEVS94 on his way to the airport
Over 40% of the a16z Apps team's investments over the last two years went to international founders. Half are headquartered outside the US. Angela Strange and Gabriel Vasquez own the bet behind that number, a bet that the best founders can come from anywhere. In Poland, ElevenLabs became the national AI champion. In Spain, Supersonik landed Salesforce as its first design partner. In Colombia, Angela's first check went to Addi, which now serves a quarter of the country and recruits Capital One's best credit talent to Bogotá. In this episode, they sit down to discuss the playbook: why AI opens every market but concentrates the epicenter in the Bay Area, and why country diasporas beat elite alumni networks. 00:00 Intro 00:54 From a WhatsApp group to a global strategy 05:29 Why AI pulls founders to the Bay Area 10:29 Defining the borderless founder 12:29 How diaspora networks help companies scale 18:11 The three advantages of borderless founders 22:36 Preferential attachment across borders 25:11 The bridge to Silicon Valley works both ways 27:11 Mapping and building global ecosystems 33:15 Backing repeat founders 40:31 Silicon Valley speed and global ambition piped.video/watch?v=0t3TpJXa… @astrange @GEVS94 @VirtualElena
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in my mid-20's, a time when about half of my friends hated their jobs (a very normal phenomenon if you're in your mid-20s), i noticed a group of people my age who looked extremely happy and actualized at work. and all of these people somehow seemed to work at stripe. i'll call out @tamarawinter and @orbuch specifically as some of the first people who made me realize that it was possible to be 25 years old and do *singular* work every day, and not just whatever garden-variety boilerplate the company demands. this podcast with @gaybrick and @DavidGeorge83 helps explain why this was, and still is, the case. will says stripe increasingly is a platform for founders internally, just as it's always been a platform for founders externally. he wants each employee to feel like an “auteur”: an engineer, product thinker, and creative person with enough context and authority to make something real. we're now seeing a new generation of this pattern, with stripe's support of stuff like tempo (a team that might have one of the highest concentrations of founder-mindsetted people im aware of? cc @gakonst @dwr @varunsrin @liamihorne etc) the embrace of teams like privy and bridge, and other incubated initiatives like minions. stripe is trying to make employees more founder-like while preserving a shared standard of quality (one of my favorite details on this point: stripe creates simulated customer accounts so teams can experience realistic UIs for disputes and refunds before exposing products to real users). this is something that's actually very tough to do well, so it's very cool to hear will talk about it on this pod.
Stripe's Will Gaybrick: "Build everything" Against an industry that sees agents as a way to cut costs, Stripe is using them to build more: agents wrote 30% of code in a week, global tax filing shipped in 1/3 the time the US version took, and after AI made sellers 20% more productive, Stripe hired even more sellers. President of Technology & Business @gaybrick sits down with a16z's David George to cover why there's no one left for Stripe to copy, why checkout pages will disappear, how agents plus stablecoins make micropayments real, and why tokens are becoming a currency worth protecting like dollars. 00:00 Intro 01:00 From payments to 30 products 02:30 1 in 6 free trials abused 05:50 Win the startups, then win them again 09:40 Borrowing from Google, Apple, and Ford 14:30 Minions: 7K one-shot PRs a week 18:45 Building everything vs. cutting costs 26:00 Why timelines keep compressing 29:50 What replaces the checkout page 34:20 The case against $9.99 subscriptions 37:20 Stablecoins solve a political problem 41:35 Tempo, a payments-only blockchain 43:10 Tokens are money now 49:00 How Stripe scales taste piped.video/watch?v=P5iICDVn… @gaybrick @DavidGeorge83
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back in 2017 i was interning as an equities analyst at a fund in nyc, which had a 9am morning call every weekday. the purpose of this call was to discuss quarterly earnings or current events or whether we should be buying nvidia (at the time, on a tear because of the '17 crypto boom), but one morning in june the call opened with a bunch of people freaking out because some guy named "travis" had resigned. after a couple of rounds of "travis is gone" "did they fire him" "bloomberg says he resigned," i was especially confused because the firm had a portfolio manager named travis, and i looked over at his desk and he was still sitting there, not being escorted out by security or anything. who was travis? it was only after things had calmed down that i realized the people on this call were talking about *travis kalanick* of uber, a figure who loomed so large in the minds of wall street investors that even *two years before* uber ipo-ed, the news of his departure was treated like a six sigma event. everyone wanted to know: if travis was gone, what would happen to his company? even in his uber days, travis was the bits and atoms guy (watch the video clipped in the first ~2 minutes of the below podcast for proof of that). and in order to be a bits and atoms guy - as in, the kind of guy who's so discontent with the slow, staid, schlerotic state of things that he has to painstakingly reorchestrate the physical world with computers, perhaps pissing off some powerful interests along the way - some people might call you difficult. some people will not understand your vision. some people will try to get you fired. but if you're a bits and atoms guy, you never stop being one. you might retreat into near-obscurity, or spend years wandering in the wilderness, biding your time in exile. but you will not stop building. and one day you will return triumphant like a modern-day charles de gaulle, even better than ever, and ready to prove wrong everyone who didn't understand the first time around. being in a room with travis leaves you pretty pumped up. you can see why he's such a rallying leader, and why (by my count) at least six top uber execs have chosen to follow him to his new company, atoms. it isn't simply that the job isn't finished (although that's a big part of it, as travis attests). it's also because it's clear that there are very few leaders like travis out there: people who have such a holistic worldview that they can get people who would otherwise be founders themselves to join the ride and help build an extremely specific vision for the future. here are some things that stood out to me from this event: -travis is a branding/comms mastermind. he deploys memorable phrases like “food computer,” “wheelbase for robots,” “atoms as bits” and describes his vision for cheap meal delivery as "autonomous burritos." you can see why people get excited for his vision for the future. there's extraordinary complexity in what atoms is trying to do, but travis makes each step along the way feel manageable because he can distill these ideas into extremely concrete images. -atoms is building full-stack autonomation for three different divisions: food, mining, and transportation. food supplies the real estate, software, robotics, and logistics laboratory; mining supplies a commercially deployed autonomy business; and transport is intended to become the reusable movement platform connecting multiple physical industries. travis argues humanoids make sense for diverse, low-volume work in spaces designed for people. but at industrial scale (which atoms is doing), purpose-built machines should win on throughput, space, cost, and reliability. -the best way to get over your last company may be the same as the best way to get over your ex: fall in love again. travis says anger and fear of failure can carry a founder through years of pain, but they also produce long nights where very little gets done and sharp elbows felt by everyone around you. atoms is what happened when he learned to build toward a future rather than against an enemy. -doing hard things is a reminder you can do more hard things. in the q&a ben remembers travis describing attacks by chinese ride-sharing companies as proof that, if he could survive china, the rest of the world would be manageable. travis still deliberately creates problems when things become easy. but the rate of problem creation cannot exceed the organization’s rate of problem-solving. such a fun talk and q+a with @travisk @bhorowitz @eriktorenberg ! check it out.
Travis Kalanick: "A lot of folks think I'm back. I've been working my ass off the whole time. I just haven't been talking about it." Eight years, thousands of employees, multiple industries, none of it on LinkedIn, and now the biggest check Ben Horowitz has ever written. @travisk joins @bhorowitz and @eriktorenberg for a fireside chat to discuss Atoms: an industrial AI company that sees manufacturing, real estate, and logistics as the CPU, storage, and network of the physical world: 00:00 Intro 01:30 The Uber video from 10 years ago 04:26 Bits, atoms, and the three computing primitives 07:37 Can a delivered meal cost less than the grocery store? 10:16 Standing next to a TCP packet 11:59 Ride-sharing was the gold medal. Transport is full of silver 13:59 Resistance to change is the final boss 22:22 Why he didn't buy Lyft 24:09 Best idea wins 28:13 Blood, sweat, and ramen 32:32 When it gets easy, push harder 36:18 Showing up to the fundraise like a guy selling watches 45:46 Dirty fuel vs. falling in love again 48:31 Be uniconic
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i've always enjoyed reading about the dot com era and its direct aftermath. it's a great reminder that tech cycles are long, unpredictable, and full of troughs of disillusionment before things that feel "inevitable" ever really come to pass. it's particularly funny to think about the crop of stanford kids graduating in '01-'05 (which includes a list of guys like balaji, stephen cohen, joe lonsdale, temporarily sam altman, and ofc garry tan) who started out when most people thought tech was deeply uncool and perhaps even completely over. so i really love the way this pod begins - with @garrytan recounting what it was like graduating in '03, taking a job at microsoft because it was the practical thing for a young guy with student loans to do, turning down an early offer at palantir (which he eventually did accept as employee #10) then heading deeper into the world of startups and yc. this podcast hosted by anish (@illscience) is actually a great study in how to get ever-closer to yourself and trusting your gut. there's also (this being anish and garry) a lot about building very useful ai products and living 3-5 (or in garry's case 20) years in the future. doing what you instinctively know is right, being unhedged, being earnest, or in garry's words, not LARPing, isn't the fastest but it's undoubtedly the best path toward actually having an impact. this conversation is basically an instruction manual in how to do that in all areas of life - from career decisions, to building, to local politics (we probably have garry and a handful of other people to thank for the fact that sf is now a nicer city to live in than nyc). good pod! check it out! enjoy!
Garry Tan on YC, First Principles Thinking, and Progress in the Age of AI Silicon Valley's advantage is that it gives weird, ambitious outsiders permission to try, find one another, and become insiders through building. Garry Tan learned this firsthand throughout his career at companies like Microsoft, Palantir, and YC. AI may now extend the power of Silicon Valley much further. Garry joins a16z’s Anish Acharya to cover the turns that shaped him, why founders should trust direct experience over consensus, how AI is allowing small teams to do more with less, and why he's deeply optimistic about AI-native companies and the future of SF: 00:00 Intro 00:26 Getting into tech 04:45 Silicon Valley culture & finding your people at the fringe 10:59 What makes YC great: a birthright for tech outsiders 13:54 Solo founders, vibe coding, and founders being 400x themselves 21:05 Business loops: skillifying every task into a markdown file 23:03 Tokenmaxxing: how to live in 2028 today 28:09 Using AI to make conflict constructive 33:10 The torture of the white-collar job & life above the API line 39:08 Why bureaucracy is a whitepill 41:33 What the next computer looks like: voice, memory & the harness wars 44:44 Local politics & making SF a beacon piped.video/watch?v=fsTtKywm… @garrytan @illscience
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