Articles by Shishir
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Shishir Mehrotra shared thisI was in Berlin last week for the opening of our new hub. Our Berlin team has grown consistently for the last four years. The new space reflects that growth and sets us up for what's next. It's spacious, modern, and designed to be a place where our teams can come together. You can definitely see that it's built for collaboration, from how the space flows to the little details that make a difference in our day-to-day work. It's important to us to have hubs that match the caliber of our teams, and I'm excited to be in a space that does exactly that. It's already a place where people want to be. A huge thank you to everyone who invested time and energy into building this from scratch. You can see the care that went into every decision.
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Shishir Mehrotra posted thisThis week, we're hosting another global SuperHack (what we call hackathons), with team members participating in Berlin, Kyiv, San Francisco, and remotely. It's no secret that SuperHack is one of my favorite rituals, and I've enjoyed watching it evolve over the last year. We're challenging our teams to hack in a quick 24-hour sprint, encouraging exploration over production. To help everyone feel ready before hack day, we've hosted a HackAcademy prep week with tiered sessions for every level of technical proficiency and AI fluency. We want team members to have training on every tool they might need. That includes Superhuman Go's agent builder, plus sessions from OpenAI, Anthropic, and Cursor. I look forward to every SuperHack, especially when we get to welcome a new team into this ritual. I can't wait to see what the Fathom.ai team brings to the table. I'm even known for getting in on the action and submitting a project!
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Shishir Mehrotra posted thisI keep hearing some version of the same question: Shouldn't our headcount be growing more slowly now that we have all these AI tools? I think of this as the employee headcount debate, but it’s more of a debate about dreamers vs. optimizers. AI is so often seen as replacing human jobs, but I think a power tool is a much better analogy. When power tools showed up, they didn't put builders out of work. They let one crew take on jobs that used to need 10 and tackle projects that would've been impossible before. I had an interesting conversation about this with Bret Taylor, CEO of Sierra. He posed the question: If you give two companies the same tool, and one uses it to build new things while the other uses it to do the same work with fewer people, who wins? In my view, it's the company that dreams bigger. Because AI is leveling the playing field, efficiency doesn't really give you an edge. If your competitors have the same tools that you do, your capacity to dream becomes the differentiator. Rather than asking whether AI investments mean fewer employees, ask: What would you build if your team could suddenly do 10 times more?
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Shishir Mehrotra shared thisSuperhuman users have been asking us for a notetaker for a long time. Meeting notes are one of the clearest, most valuable places where AI can help, and it’s a category I’ve spent a lot of time with. That’s part of what led us to Fathom. And today, I’m excited to share that Fathom.ai is now part of Superhuman. Richard White and the Fathom team have built an excellent product and a team with deep expertise in this category. What’s especially interesting to me is where meeting notes can go next. The value isn’t only in capturing and summarizing a conversation. It’s in making what was discussed, decided, and committed to useful in the work that follows. That fits naturally with what we’re building at Superhuman. Fathom adds meeting context to the context already available across email, calendar, docs, and other places people work. We’re already working together on what comes next, and I believe we have an opportunity to set a new bar for the category. I’m very excited to welcome the Fathom team to Superhuman.
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Shishir Mehrotra posted thisThere's a particular flavor of AI anxiety I run into all the time: companies feel like, no matter what they do, they're falling behind the AI curve, and the only way to catch up is to adopt another tool. Sales adopts one thing, engineering another, and before you know it, your AI stack is unwieldy, and the ROI is murky. The number of AI tools you've adopted isn't a reliable measure of how much value you're actually deriving from AI. This reminds me of something my dad said when I was offered a research job in college at MIT's AI lab, and I called him to ask what he thought. He immediately said, "Why would you do that? AI is where all good technology goes to die." His point was simple: "The moment something works, we stop calling it AI." That still feels true. Ask a company which AI they use, and you'll hear about the newest model or whatever a vendor demoed last quarter. But the AI they actually depend on is the invisible kind that they don't consider to be AI. Think about your email inbox. For the past 20 years, it's been using machine learning to decide what is and isn't spam. Yet, nobody thinks, "I'm using AI right now" when they skim their junk folder. Something doesn't need to look obviously like AI to be worth adopting. And how much AI you can point to in your tech stack isn't really the thing to track. Instead of worrying about being behind on AI, know that the most effective AI doesn't announce itself, which means it's probably already running in your business, and you're just calling it something else.
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Shishir Mehrotra shared thisToday we're launching a completely redesigned Superhuman Mail for mobile.📱 Ever since we debuted the new Superhuman design system last fall, we've taken a thoughtful approach to unifying our products visually, in how they work together, and in how intelligence flows across them. It's great to see the Mail brand identity join the family, along with the updated mobile experience they've created, which is faster, more intuitive, and unmistakably Superhuman. Congrats to Rahul Vohra, Levi Hamilton, and the entire team who brought this to life. 🎉We redesigned Superhuman Mail for iOS and Android 📱We redesigned Superhuman Mail for iOS and Android 📱
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Shishir Mehrotra posted thisOne of the concerns underlying a lot of AI predictions is the assumption that there's only so much work to go around, and that the human share is decreasing. But I think that's a limited view on the potential for human creativity and imagination. When a technology this big arrives, some work may change or go away, but it also creates opportunities beyond what anyone could have imagined before. In his book "Age of Revolutions," Fareed Zakaria writes about two of the great disruptions of the late 19th century, the railroad and electricity. The railroad changed everything about how goods and people moved, especially for those whose livelihoods depended on that movement. But wagon drivers didn't become train conductors. A lot of them found work that the previous economy hadn't needed, like factory jobs and the whole business of importing and exporting goods. When electricity arrived, lamplighters found themselves in a similar spot to the wagon drivers. Their work got replaced, but they found new work that hadn't existed before. And there are plenty of modern examples of this: 20 years ago, nobody was planning a career around becoming a YouTuber or influencer, because the category just wasn't there to plan around. We're repeating history in the assumptions we're making about AI. We watch a model pick up some task a person used to do, and we decide that the job is disappearing. Sometimes the role really does shift. But what we almost always miss in the moment is all the work that doesn't exist yet. AI may eliminate some jobs, and I don’t think anyone’s really arguing otherwise. I just think we should start paying more attention to the ones it’s about to invent.
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Shishir Mehrotra posted thisMy daughters are heading back to college and to senior year of high school right now, so the question of what AI means for students is one I'm getting from every direction these days, at the dinner table and at the office. And it's not just a conversation in my house. We recently ran a survey with Talker Research, and students told us they're worried about finding a job after graduation. I want them to know that the jobs are out there, but the work will look different. For a long time, entry-level work followed a similar pattern. You likely started your job with some baseline skills from your degree, but mostly you showed up, did the grunt work, and learned the craft slowly through experience. At some point, you worked your way up to managing other people and hiring more entry-level workers similar to your past self. I don't think that path survives contact with AI. That grunt work that used to build instincts is now being handed to a frontier model. This means that the judgment you could previously absorb by osmosis while doing your job, you now have to build on purpose. Mostly, this means caring more about the quality of the work than the speed and volume. The skill that will make all the difference after you graduate is the ability to look at 10 different AI outputs, be able to tell which one is actually good, and say why. That's taste, and taste comes from closely studying what's great and forming your own opinions about it. It has nothing to do with prompting. I also encourage students to use AI in ways that make them think more. Treat AI like a sparring partner—something to argue with and pressure-test your ideas against. These skills are still making their way into syllabi. But if I were to start college today, I'd worry less about out-producing the machines—it can't be done—and put that energy into building the judgment that can point the machines in the right direction. That's a skill that will carry you through school, your first job, and beyond.
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Shishir Mehrotra shared thisWhy does using AI feel like a detour even when it's good? It's because you have to go to it. You have to pause what you're in the middle of doing, open a separate chat window, explain the whole situation, wait, then paste the answer back where you were actually working. That's the challenge we've been chipping away at with Superhuman Go, and today we shipped our biggest update yet. Go shows up where you already work. It sits alongside you in whatever doc, inbox, or tab you're in, reads what you're doing, and pulls in the agent that can help. And my personal favorite update is, now, you can build those agents yourself. Describe what you want and Go will make it for you. Here are a couple agents we shipped to get you started: - The Knowledge Checker agent catches you before you send a number that's out of date or a stat that doesn't match what's in your company's data. - The Email Assistant agent sorts out your inbox and writes drafts that sound like you, getting you that much closer to Inbox Zero. Go can do a lot more now, too. It works in the background, searches the web, spins up docs you can share, and picks up on how you work over time. It's time to let AI come to you. Really proud of what the team pulled off here, and there's a lot more coming.
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Shishir Mehrotra liked thisShishir Mehrotra liked thisI speak to higher ed leaders every day, and many of them are asking themselves this question: “How do we get our students and faculty to actually use the AI tools we’ve thoughtfully vetted and onboarded?” Determining your AI strategy is one hurdle. Turning it into coordinated adoption is another. Many institutions invest in AI and put the right infrastructure in place, only to find their faculty, staff, and students defaulting to other tools. That’s the challenge at the center of our upcoming EDUCAUSE session, Built With Institutions: How Three Campuses Built AI on Their Own Terms. One solution? Embedding custom AI tools directly into the workflows your students and staff are already using. Leaders from Indian River State College, New Mexico State University, and Saint Joseph's University will talk candidly about what they built, the problems they encountered, and what campus leaders can learn. If you’ll be at EDUCAUSE in Denver, I hope you’ll join us on Wednesday, Sept. 30 at 2:15 pm! https://lnkd.in/gPPusYNV
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Shishir Mehrotra liked thisShishir Mehrotra liked thisToday marks my first day as CEO of lululemon. I began the day with yoga, breakfast, and candid conversation with an incredible group of Educators from across our Vancouver stores. As I step into this role, it is so important for me to hear directly from our team about their experiences, our guests, what is working, and where we can be better. lululemon is an extraordinary brand that I’ve long admired, an industry pioneer built by passionate teams and a deeply connected community. There is also important work ahead. While my initial priority during this onboarding period will be listening and learning to better understand lululemon’s product, brand, and culture, my focus from day one is to build on what makes lululemon special while raising the bar for what comes next. I sent a note to our teams this morning about how I'm approaching this next chapter. We’ve also published it on our website so others who care about lululemon can see the priorities and perspective I shared: https://lnkd.in/dgUaSYbP It’s a privilege to lead this company and work alongside the talented teams and leaders across the business. Thank you for the warm welcome. I couldn’t feel more optimistic about the journey ahead.
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Shishir Mehrotra liked thisShishir Mehrotra liked thisWow...it is a day of recognitions. We just got chosen as TIME's World's Top Healthcare Companies. With due humility, I feel this an obvious recognition. We *are* a top healthcare AI company in the world :) But I will take it. Thank you TIME! I would love to be a top company from the perspective of customer impact. I wish there was a people's voice or customer oriented top company list. That is where Suki should aspire to be. In the meantime, I will take the accolade. It is that kind of day anyways. Happy weekend!
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Shishir Mehrotra reacted on thisShishir Mehrotra reacted on thisWe’re thrilled to announce that Fathom.ai is now part of Superhuman! Fathom has built an incredible AI notetaker that helps teams capture, search, and act on what happens in meetings. Bringing Fathom into Superhuman adds an important source of context to our suite—connecting what people discuss and decide with email, documents, data, and the apps and websites where they work. We’re incredibly excited about what we can build together. Welcome to Superhuman, Fathom.ai team!
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Shishir Mehrotra liked thisShishir Mehrotra liked thisBig news: Fathom is now part of Superhuman! We’ve always believed the real value of meetings isn’t the notes — it’s what happens after. The follow-up that gets written. The decisions that get carried forward. The work that gets done. We’ve spent years building Fathom to capture the knowledge inside meetings and make it useful beyond the call. Joining Superhuman gives us the opportunity to take that much further. Superhuman is building an AI productivity platform that spans email, calendar, collaborative documents, and more, with AI assistance that works across the apps and websites people use every day. Together, we can make what gets discussed and decided in meetings more useful wherever the work goes next. It’s a big step toward what we’ve been building toward from the start: helping people show up at their best and move work forward.
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Brittany Walker
Voice is a super interesting modality right now - maybe the first modality we're seeing move to open source models across a number of scale ups / enterprises. Reliability concerns, high costs, and open source model performance are pushing engineers to do their own fine tuning vs. relying on third-party vendors of proprietary models. Many of these orgs have already been collecting their own first-party data and now with third-party vendors like Extrian, David AI, etc they can train really high quality models. RL has been insanely hyped, but it's been unclear how long it will take scale ups and enterprises to actually lean in. Voice AI might be hitting that inflection point faster than expected.
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Jesse Landry
When most people hear "solid-state," they think storage. But in Santa Clara, xMEMS Labs just gave that term new resonance, literally. The company just raised $21M in Series D funding led by Boardman Bay Capital Management, with Cloudview Capital, CDIB-TEN Capital, Harbinger Ventures, Susquehanna Asia Venture Capital, and other strategic investors tuning in. This isn't another round of capital, it's an #amplifier for a company turning silicon into a new language of #sound and #cooling for the AI era. Founded in 2018 by Joseph Jiang and Jemm Liang, xMEMS spun out of piezoelectric R&D at TSMC and turned what was once wafer-level theory into commercial hardware. Joseph Jiang, a veteran of Knowles, Fortemedia, and InvenSense, leads with precision and swagger, while Jemm Liang, who built Ultrachip from the ground up, drives the engineering with surgical focus. Co-Founder & CLO Wei-Fu Hsu, the former MediaTek exec and IP expert, ensures xMEMS' innovation is as protected as it is disruptive. Their play? A monolithic MEMS platform that transforms voltage into vibration, silicon into sound. Unlike legacy coil speakers and fans, xMEMS tech doesn't move parts, it moves markets. Over 500K MEMS speakers shipped in 1H'24, backed by >250 global patents. The Cypress & Sycamore lines redefine what "small" can do: 1mm-thin, full-range, and capable of sub-bass response once thought impossible in earbuds. Their XMC-2400 µCooling chip, 1mm-thin, fan-on-a-chip, inaudible, moves 39cc/sec of air at just 30mW. That's not cooling, that's choreography at a molecular level. Dr. Chester Hwang, named CTO on Oct 15, 2025, joins to push that curve further. Alongside veterans Mike Housholder (VP Marketing & Biz Dev), Jim Wargnier (VP N.A. & EU Sales), James Lee (VP & Korea GM), Steven P. Bentley (VP Sales), and Martin Lim (VP MEMS Tech), xMEMS is scaling at semiconductor speed. They're already in BleeqUp's AI sports glasses and teamed with Dongguan Rayking Electronics for TWS modules. When OEMs talk "next-gen," they're talking xMEMS-level integration. For investors like Boardman Bay's Will Graves, this isn't just sound engineering, it's signal intelligence. With AI pushing devices thinner, faster, and hotter, xMEMS' piezoMEMS platform sits at the intersection of #acoustics and #thermals, where every millimeter matters. Backing them is a bet that the next wave of #sensorytech won't just compute, it'll feel alive. So what's next? Scaling production, expanding capacity, and embedding xMEMS' silicon pulse into everything from earbuds to AI #datacenters. In a world chasing speed, silence, and fidelity, xMEMS isn't following the beat, they're building the frequency the future will hum to. #Startups #StartupFunding #VentureCapital #SeriesD #AI #Sound #SoundEngineering #Semiconductors #Data #DataDriven #Technology #Innovation #TechEcosystem #StartupEcosystem #Hiring #TechHiring If software engineering peace of mind is what you crave, Vention is your zen.
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James Green
CRV Security: Request for Startups I never know if this actually works for our friends over at YC but figured we'd try. Here's what we want to fund in 2026! 1. Golden Artifacts: Think Chainguard but more broad. Artifact attestation exists for open source. Almost nothing exists for internal software — especially the vibe-coded tooling now running in production. We want the company building cryptographic proof of secure software delivered from secure artifacts: who built it, how, and whether it was reviewed. If more things are being yeeted into the world via Claude Code (myself included), this feels like an issue. 2. MCP & Agentic Security: Agents are getting real credentials and taking real actions. The security posture of most orgs around this is basically zero. That changes fast. You'd never give an employee hardcoded API keys or write access to your email without supervision/trust. Why give it to agents? 3. AI Governance: Boards are asking CISOs to account for AI risk. CISOs have no good answer other than "Palo has a module" 4. Next-Gen Endpoint: CrowdStrike was built for a world of static binaries and human operators. AI workloads, cloud-native infra, and AI-assisted attackers need a new architecture. The category is ready to be reinvented. 5. Networking in the AI Era: Zero trust was designed for humans. What does network security look like when the entity requesting access is an agent? Nobody's really solved this. 6. Email Security + Next-Gen Phishing: LLMs have made spear phishing infinitely scalable. I've never truly understood why Abnormal and KnowBe4 aren't one company. Maybe this time it's different. 7. Frontier Security Lab: We'd back a credible, well-staffed lab focused entirely on red-teaming models and setting the evidentiary standard the industry needs as LLM built apps become the norm. 8. Dependency Security: That Actually Remediates Malicious and vulnerable dependencies are a top attack vector. The tooling is mostly noise — scanners that don't close the loop. The winner here ships fixes, not just alerts. 9. Critical Infrastructure Cyber: Data centers, satellites, power grids, undersea cables. The physical backbone of the internet is increasingly exposed and wildly under-defended. We have data centers in space, for God's sake. Surely we need better cyber for critical infrastructure? 10. PAM for the Modern Era Legacy: PAM was built for static roles, human users, on-prem directories. Cyberark was founded in 1999.....Agents, ephemeral workloads, and cloud-native infra have broken all of those assumptions. Is anyone rebuilding this from scratch? If you're building in any of these areas — or something we haven't thought of — reach out. james@crv.com
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Mike Duboe
Greylock is leading the seed in SuperMe, the AI-native professional network. Most expertise is not yet legible to LLMs. Professionals demonstrate expertise in private contexts: product docs, meeting notes, and most often - in their own heads. SuperMe is building a way to extract and structure these insights into AI profiles, grounded in an expert's real words and personality. And it is network-first; the more conversations one's AI profile has, the more opportunities for experts to reinforce or create new insights -- expertise compounds. This is one of the strongest examples of founder-market fit we've seen at Greylock. Casey Winters is the most in-demand product & growth advisor that marketplace operators (self included) wish they could hire. And Ludo Antonov built & led engineering teams at some of the most iconic network businesses over the past decade: Whatnot, Lyft, and Pinterest (where he worked closely with Casey). The two started this company out of our offices, and have until now been quietly building a highly curated network with profiles like Elena, Lenny, Brian, etc. We see a unique opportunity to create the professional network graph in a world where likes & follower counts have lost meaning. More on our investment below:
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