Cyberattacks now outpace the defenses of even well-resourced organizations. Factory can help. Introducing Factory Wargames: We will simulate a nation-state level attack on your company's infrastructure and cover the cost. Apply below and if selected, we'll run the simulation, share our learnings, and Droids will help with the fix for free.

Four years ago a few of us at a16z started @speedrun to back founders at the earliest stages. A year ago I left to become one. Today I can share what we’ve been building at LionBio: a nasal spray GLP-1 backed by a $6M pre-seed from SPC.

I want to build The Office of The Future which is just a regular office but with microphones and cameras everywhere. You just talk to your colleagues all day then everything gets recorded and transcribed for agents who complete your tasks and show you results on big TV screens.

Today, @humanlayer_dev is joining Factory. HumanLayer is a multiplayer coding agent IDE and cloud for running agents locally or in the background. Together, with @dexhorthy and @0xblacklight we're building the future of software factories for entire engineering teams.

The demand for Compute is the hottest topic in tech right now @SPC NYC is has a stacked panel on this this week! @carmenli (@silicondata) @absurdistphil (Compute Trading Lead @jumptrading) @brexton (Global Head Compute @ Cantor Group) Moderated by @unhedged21 (@eqxlabs)

okay public speaking is hard, apologies for the folks who showed up to watch me overheat and bomb, so here’s all the stuff i meant to explain right now you are being asked for a near 100% prepayment because neither you nor the cloud is considered credit worthy, and so nobody can get debt. As ai scales, we are asking the credit markets to take on a massive single sector deployment of capital. More money deployed, more scared everyone gets. this problem will flow down into the token layer. Every inference provider or model lab struggles to be credit worthy enough to get compute, and their lever to improve their situation is to lock in big prepayments from their customers or long term contracts from credit worthy customers. So this problem doesn’t just effect compute buyers, it effects token buyers. We’re entering a world where fortune 500s can very quickly deploy huge token spend ON CREDIT where the startup will need to raise capital. Startups got to exist because human capital could leave a firm and get ahead of the big firm by exploiting a combination of incentive misalignment, speed, and taste. You probably have the hidden assumption that the fortune 500 is slow and incapable of competing with your ultra fast startup. This belief does not necessarily hold in the case where the agent does the thing. the “market” is working on solving it. We know, because we are the market, and we’re working on it. sfcompute is working on ways of firming up the collateral of the loans, which makes it safer to lend to a startup. this is basically the whole reason we exist, the problem everyone is experiencing now is the problem junelark, our little ai lab years ago, hit however, we won’t succeed in time. so, in the short term, startups and venture firms should learn to protect themselves. we are mostly watching startups and investors make unforced error after unforced error, because this is not a simple subject. first, venture firms need to understand that they are in the compute business now and deploying capital to pay for a 100% prepayment for 10 startups where 6 of them die and 4 of them make 50% margins on that capital is basically locking in non-venture returns. many funds, via low understanding of the space, are wrecking their funds. there’s an economic solution for vc’s and it is owning the compute and trading equity for gpu/hrs. If the company dies, you keep the residual value. Each of you are looking to capture the next anthropic or openai, but the only way these companies scaled was by trading compute for equity. meanwhile, startups have three options in a credit crunch. The first is to raise a wild amount of capital, enough to pay for your deployments with far larger prepayment or to survive until things chill out. theres a reason we’re seeing a number of multi-billion dollar rounds simultaneously. The second is to design your business model to support variable priced tokens and compute. As the financial ecosystem builds around compute, you will be able to trade “lower up front payments” for “variably priced compute or tokens”. Your business will get tailwinds from the infra under you if you setup your business model such that YOUR customers have variable prices and you’re just adding a % take rate on top of the underlying floating price. Every year, you will become more and more capital efficient. The economic winners in ai & inference are firms that make lower and lower margin every year, but become more capital efficient & scale faster every year, making their gross profit increase. The third option is asynchronous or interrupted products. If you have a variable cogs, but a fixed rate card for your customers, it can’t have 100% availability or you’ll go bankrupt. But it is totally possible to design your product such that customers like this.

Hi, I'm Euwyn. Going to start posting here again, so a quick reintroduction. I'm the founder of Orbital. We're building AI data centers in space. A few things about me: In 2010, I moved to Silicon Valley to join YC (S10) to build my first startup. In 2017, I co-founded Spin, the first micromobility company in the US. In 2018, Ford acquired Spin for close to $100M. Over the following years, we scaled it to 1,800 employees, deployed 250,000+ vehicles and expanded into 100+ markets. In 2026, I founded Orbital. We raised funding from a16z speedrun, Human Interest, Basis Set, Anti Fund, and others. The team has decades of experience building satellites at Amazon Leo, Lockheed Martin, Northrop Grumman and other aerospace companies. Our mission is to solve one of AI's biggest problems: the electricity shortage. AI demand is growing exponentially and we can't build enough power plants and grid capacity to match it. Data centers in space is the solution. I'll be sharing what we're building, what we're learning and why I believe space will play a huge role in the future of AI. If you're interested in AI, space, data centers and the future of computing, you'll probably enjoy what I post here. Follow along for the journey.

my unfiltered thoughts on the data industry right now: there are too many brokers in the data space. in the last 4 months this industry has become the new equivalent to dropshipping. i have no issue with that. but if your entire moat is spam calling smb owners all day and begging them to license their data for a micro1 referral fee, you are not going to make it, and you are not the next mercor. most of you are not building anything at all. to everyone reading this, and the hundreds of other posts on your timeline from 18 year old sf kids claiming $200m run rates please ignore them. these are the modern day elizabeth holmes’. they're taking one day of contracted (not paid) revenue and multiplying it by 365. the worst i've seen is someone who made $100k off a micro1 referral fee in 6 hours and claimed they're at a $73m run rate (12 (daily working hours) / 6 x $100k x 365). this is literal fraud, especially if you raise money off of this claim. you see this in a lot of yc companies in recent batches. the only businesses i see surviving this are the giants that already exist (mercor, micro1, surge ai, turing) and the non consensus bets: consumer data collection apps like kled, robotics data collection companies like build ai and meckaai, etc. tldr: don’t believe everything you read, and just brokering company data is not a venture scale business and should not be claimed as such.