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In 2008, I joined Foundation Capital as a General Partner because I thought it would be a…
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Ashu Garg posted thisThe idea that you can map out your life's work at 22 is a fiction. When I left IIT, I had never met a tech entrepreneur, and I had no idea what venture capital was. I found my way to it by doing. The jobs you'll hold in 5 years, let alone 10 or 20, likely doesn’t exist yet. Even people in stable professions today will have to keep reinventing what they do. A helpful way to think about your career is as a prototype: something you build in order to learn from, rather than something you have to get right on the first try. The best teacher is contact with reality and the feedback only it can give you. Your prototype can start out small. You take a job, and you begin to notice things: what energizes you, what drains you, the skills you pick up faster than the people around you, and the projects you pour far more into than they demand, simply because you love the work. A sense of purpose rarely arrives as a grand, all-consuming mission, fully shaped and waiting for you at 22. More often it builds from small, repeated moves toward what interests you, the kind that add up over time into something far larger than you could have planned. Put otherwise, purpose is often a verb long before it becomes a noun. The best way to discover what you're meant to do is to start, and keep adjusting as you go.
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Ashu Garg posted thisMany founders start with a shiny new technology and go looking for a problem it can solve. The ones who build companies that last do the opposite. They start with a problem they understand deeply and reach for whatever tools, new and old, best solve it. This discipline matters more now than ever, because the leverage available to one person has never been higher. We're entering an era where 10 people can do what used to take 10,000. The more any one person can do, the more it matters what they choose to do with it. The obvious thing to do with your leverage is spend it on volume: ship more code, launch more features, send more outreach, generate more of everything. That confuses speed with velocity. Speed is pure motion. It's seductive because it's the easiest thing to measure and the easiest to mistake for progress. Velocity is motion with direction. It reveals itself over time, in whether your motion brought you closer to a goal worth reaching. A startup sprinting in 10 directions at once can feel enormously productive while going nowhere. To win the race, you have to run quickly *and* in the right direction. One of the biggest jobs of an early-stage founder is figuring out which direction that is. The best thing to spend your leverage on is ambition, on projects you would never have had the resources, expertise, or confidence to attempt before. But ambition needs a direction too. The right one is a problem that genuinely matters to you: one whose solution would mean something to a few people you know, and ideally to many. That’s where the best founders begin: with the problem itself, before any particular tool. The tools change by the week, but the problems worth solving change at human pace.
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Ashu Garg shared thisMany graduates I talk to are asking some version of the same question: is the game over? It’s a fair fear. AI writes 75% of new code at Google and north of 90% at Anthropic. The on-ramps that used to look safe - first-year tracks in banking, consulting, law, and programming - no longer do. Computer science enrollment just posted its steepest drop on record. But the frontier always looks claimed to the people standing closest to it. Consider the class of 2002. The dot-com bust had just happened, and Yahoo, AOL, eBay, and Amazon looked like they had absorbed all the available oxygen. The smart move was to go to business school or get a “real job” in finance. Then came Facebook in 2004, YouTube in 2005, the iPhone in 2007, and Airbnb, Uber, Instagram, Stripe, and Databricks soon after. Most of the companies that defined the internet for two decades were built by people who, in 2002, were told they were too late. Twenty years from now, people will look back on this stretch of AI the way we look back on dial-up. You are earlier than you think. More on what that means for the class of 2026: https://lnkd.in/gdEixXjEYou’re earlier than you think - Foundation CapitalYou’re earlier than you think - Foundation Capital
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Ashu Garg reposted thisPlaying it safe is itself a bet, and usually a worse one than it looks. This matters most if you just graduated, because the math tilts hardest toward taking risks in the years right after school. Loss aversion is a powerful force, but over the course of a career, risk and return are tightly correlated. Consistently choosing the higher-upside path is one of the biggest determinants of how far you will go. What you want to look for is convexity: risks whose downside is capped and whose upside is unbounded. Joining a startup that folds often teaches you more than it costs. Sending a thoughtful email to someone you admire invites nothing worse than silence. That asymmetry will never tilt further in your favor than it does right after graduation, when you have the least to lose, the most time to recover, and the longest runway for good decisions to compound. Taking risks also improves your luck. Luck is a collision, an unplanned moment when a person, idea, or opportunity crosses your path. These collisions aren't completely random: you can engineer far more of them than you think. A few ways to do this: Work for people who attract talent, because their orbit will become yours. Share what you're learning in public to draw like-minded people toward you. Be useful before you're asked, so you build a reputation for taking initiative. And follow up after you've been ignored: a surprising number of connections happen on the second, third, or even fourth attempt. Each of these habits puts you in the path of more collisions. Over time, that widens the surface area of your luck.
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Ashu Garg posted thisPlaying it safe is itself a bet, and usually a worse one than it looks. This matters most if you just graduated, because the math tilts hardest toward taking risks in the years right after school. Loss aversion is a powerful force, but over the course of a career, risk and return are tightly correlated. Consistently choosing the higher-upside path is one of the biggest determinants of how far you will go. What you want to look for is convexity: risks whose downside is capped and whose upside is unbounded. Joining a startup that folds often teaches you more than it costs. Sending a thoughtful email to someone you admire invites nothing worse than silence. That asymmetry will never tilt further in your favor than it does right after graduation, when you have the least to lose, the most time to recover, and the longest runway for good decisions to compound. Taking risks also improves your luck. Luck is a collision, an unplanned moment when a person, idea, or opportunity crosses your path. These collisions aren't completely random: you can engineer far more of them than you think. A few ways to do this: Work for people who attract talent, because their orbit will become yours. Share what you're learning in public to draw like-minded people toward you. Be useful before you're asked, so you build a reputation for taking initiative. And follow up after you've been ignored: a surprising number of connections happen on the second, third, or even fourth attempt. Each of these habits puts you in the path of more collisions. Over time, that widens the surface area of your luck.
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Ashu Garg shared thisIt’s commencement season, and it’s a strange world to be graduating into. A few thoughts on what it means to graduate into the world AI is making, and whether there’s room in it for you. The short answer: you are not too late. I know it doesn’t always feel that way. The on-ramps that used to count as "safe" for new graduates - first-year tracks in programming, banking, consulting, and law - no longer do. AI is changing knowledge work faster than the institutions preparing students for that work can adapt. But every frontier looks claimed to the people standing near it. It looked that way after the dot-com bust, and in 2026 with AI. My advice: Start before you feel ready. Experiment with the tools. Treat your career as a prototype, not a test you have to ace on the first try. Take asymmetric risks while your downside is still low. Guard your attention fiercely. Build around your strengths. Find specific people with specific problems, and be useful to them. You don’t need to know your life’s work at 22. Most people don’t. You find it by making contact with reality, noticing what gives you energy, and continuing to move in a direction that becomes increasingly your own. The world is changing quickly, but it's full of opportunities. You’re earlier than you think.
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Ashu Garg shared thisAshu Garg shared thisCongratulations to our General Partner Steve Vassallo on being named to this year’s Forbes Midas List! This recognition reflects the extraordinary founders Steve has had the privilege to back and build alongside. We’re proud to celebrate him, and even prouder to stand beside the founders who make Foundation Capital possible. https://lnkd.in/eGQM5EpV
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Ashu Garg shared thisSecurity and governance concerns are a big reason why AI pilots stall. You need to have visibility into what the hundreds of agents at your organization are doing, and what they might unintentionally have access to. This is compounded by the fact that every legacy enterprise application was designed around a human interface. When agents replace that interface, the architecture of enterprise software has to be rethought from the ground up—permissions, security, even UX. I’m excited to see where that leads us. More thoughts in my newsletter: https://lnkd.in/g8u8FphS
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Ashu Garg shared this“A procurement decision about a software is actually a group decision,” shares Sumit Johar, CIO at BlackLine. When selling software, get familiar with a company’s procurement process so you know which stakeholders need to get on board. It might be more people than you think. See what other CIOs—including Karthik Chakkarapani (Zuora) and Saket Srivastava (Asana)—have to say about the selling tactics that actually move the needle: https://lnkd.in/guUnbfeK
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Ashu Garg liked thisAshu Garg liked thisSuper excited to share that I've joined Salesforce as EVP & GM of Data Management. It’s an incredible opportunity to take on this role at such a time of change in the industry driven by AI. Software and applications will change in a few years in ways we can't fully imagine right now. But two things feel certain. There will always be a need for an AI infrastructure layer, and there will always be a need for the data layer. AI ready data will drive practical, positive change in the world, at scale. Combine that with the prospect to help build on one of the most iconic brands and platforms in the world, alongside some of the brightest minds in the industry - it became a once-in-a-lifetime chance to influence at the heart of the AI transformation. Deep gratitude to the leaders who placed their trust in me: Rahul Auradkar, Muralidhar Krishnaprasad (MK), Miguel Milano, Srini Tallapragada, Marc Benioff, and Steve F.. Thank you for the opportunity. And to the mentors who shaped how I lead along the way — Mark Barrenechea, Rory Read, and so many others — thank you. I carry your lessons into this next chapter. Energized for what we build next. Informatica, Salesforce
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Ashu Garg liked thisSuch a cool blog! This describes the essence of what we’re doing Unconventional AI…using the physical world to do computing. Computing is not an artificial thing; nature has discovered this concept over and over again. We’re building something that can harness nature to compute with the lowest possible energyAshu Garg liked thisMost real-world systems are dynamic. So why do we still treat computation as static? Our latest blog by Sara Achour and Matthew Bull explores computation through motion using gyroscopes, rods, springs, and ordinary differential equations to perform handwritten digit classification. A deep dive into: • dynamical systems as compute • differentiable ODE solvers • physics-inspired machine learning • emergent computation through interaction Read here: https://lnkd.in/gWPrdmbp
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Ashu Garg liked thisAshu Garg liked thisI'm hiring a Director of Sales, EMEA at Arize AI! We're the leading AI engineering and evaluation platform, trusted by 150+ enterprises like Booking.com, Uber, and PepsiCo. EMEA is our biggest growth opportunity, and I'm looking for someone to help build it — building the team, the playbook, and the market across Europe and the Middle East! More details here: https://lnkd.in/ejTxFtM2 Know someone great? Tag them or send them my way.
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