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…

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...

all the world’s a sim / and all the men and women merely agents

ncaa but for h16n / uatx / thiel fellows / yc / speedrun / 1517 etc who's building this?

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.

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!

it’s the machine age now. plan accordingly.

the datacenter-themed chanel spring summer ‘17 RTW collection. you couldn’t do this kind of thing today, they’d cancel you.

pleased to announce jalapeno chip early access at the a16z office

in true borderless fashion, i just ran into @GEVS94 on his way to the airport

extremely scott kupor voice: the secrets of sfo

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.

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.

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!

a big reason we haven’t seen massive ai-related job losses is because large legacy companies are full of people who derive power from the number of subordinates below them on the org chart and you simply can’t replicate those dynamics with agents (unless you have eg a tokenmaxxing leaderboard…)

there are decades where nothing happens and the three minutes immediately before a zoom call where literally everything happens

something that i've noticed in the ~4 months i've lived in sf is there's a small cohort of founders / engineers / ai researchers who all behave as if they're living 3-5 years in the future. this manifests in a lot of bruce wayne-type behavior. i've seen workflows of engineers who lie supine on the couch as they wisprflow commands to their agent swarms without ever touching a keyboard. i've seen people build out entire second brains that they orchestrate with openclaw / hermes agents. i know guys who spend $1m +/year on tokens. so i think this conversation with alejandro maza, kavak's chief product and ai officer, with @astrange and @GEVS94 is super interesting because it 1) shows us what an entire organization built around living in the future looks like 2) kavak isn't even based in sf (or the us) so it's very cool to see how an organization outside of the bay area approaches ai from first principles. some takeaways: - alejandro's governing question is what kavak would look like in 2035 with much more capable, cheap intelligence. kavak moved from functional specialists and transactions toward a persistent *agent per customer*, with a long-term goal of maximizing that customer’s lifetime value. -every major model release should trigger a fresh model–harness experiment. kavak had developed a multi-agent framework, but a new model release rendered the company's legacy orchestration outdated, so they discarded 2 years of working infra and rebuilt everything around a simpler agent harness. the lesson is to keep asking: what's the minimum scaffolding the newest model needs to express its intelligence safely and at scale? -kavak built an ai ceo for one city, and says it increased profits by 1.5x in its first month. customer satisfaction, inventory rotation, financing penetration, and other KPIs also improved. maza attributes the result to fields medal-level intelligence applied relentlessly to every number and customer: forecasting performance, assigning daily work, and collecting progress reports. -in light of above points, alejandro's deeper thesis is that the organization, not merely the model or individual worker, should self-improve as new intelligence becomes available.