Sequoia Capital

How do you build an intentional career? This week the Talent team Sequoia Capital had the pleasure of gathering an exceptional group of rising leaders in tech to explore the idea of building intentional careers. We were lucky to be joined by panellists Laura Gonzalez Florez (Synthesia) Tara Massoudi (Revolut) Ellen (Moeller) McCormack (Watershed) who shared stories about their own career journeys and gave excellent advice on making purposeful career decisions. Hosted by our very own career expert, Franky Roberts. 4 key takeaways that stood out: 🎢 Actually, How Intentional Can You Really Be? Many tech careers, especially in startups, are non-linear. They often start accidentally without a clear North Star – and that’s okay.  Early on, following great people is perhaps the best North Star of all - for example, joining a visionary founder who can attract high-calibre talent could be the most intentional choice you make. 💬 The True Power of Mentors Mentorship doesn’t need to be formal. The best advice often comes from people who don’t even realise they’re mentoring you. Seek out diverse perspectives and direct feedback from people who won’t sugarcoat their advice – they’ll challenge you to grow in unexpected ways. 🧩 Network > Credentials An MBA is by no means a career prerequisite, but it can amplify your network. However, working in high-growth startups often creates even stronger networks. Be intentional about the company you pick to spend the next chapter of your career with. Companies like Stripe and Revolut have done a great job at building tightknit ecosystems of talented individuals that can supercharge careers. ⚡ Founders As Career Catalysts Purposefully selecting great founders to work for can accelerate your career. The best founders think deeply and broadly, challenging their teams to back up their instincts with data and rigorous thinking. This teaches you to dive deep into details, while also seeing the bigger picture. Founders are classically demanding, direct and have high expectations, which forces you to bring your A-game every day.

The terminal hasn't changed since 1969—until Warp Now powering OpenAI's DevDay demos and used by hundreds of thousands of developers, Zach Lloyd is bringing AI, collaboration and modern features to developers' most essential tool. 🔗 👇 https://seq.vc/zlc

Our latest LangChain Academy course, Introduction to LangSmith, is now available! Dive in and learn the essentials of LangSmith — our platform purpose-built for LLM application development, whether you're building with LangChain or not. In this course, you’ll learn how to: 🔄 Quickly iterate and refine prompts with LangSmith’s prompt engineering tools 📐 Evaluate and improve your app’s performance using best practices for testing LLM applications 📈 Monitor and debug real user issues in production with LangSmith’s tracing and observability Enroll for free ➡️ academy.langchain.com Request a LangChain Academy training for your team ➡️ https://lnkd.in/gmUC6D2V

“We absolutely must create this because if we don't do it, the bad guys will get there first.” Oege de Moor left his distinguished position as the creator of GitHub Copilot to build XBOW, an AI system that's revolutionizing cybersecurity. On the latest episode of Training Data, the brilliant former University of Oxford professor explains how AI is transforming both software development and security testing, and why protecting the free world's software has become his driving mission.

Can AI agents outperform the world's best hackers? XBOW founder Oege de Moor sure thinks so. Oege created GitHub CopIlot and is now building the world's first AI cyber warrior that matches human experts in finding security vulnerabilities. XBOW is one of the first great examples of "services-as-a-software" agent companies that will shift the penetration testing market from sporadic human-intensive services to continuous agentic action. Hear more from Oege, Konstantine Buhler, and me on the latest episode of Training Data. https://seq.vc/m1r

Last January, we compared ChatGPT to AI’s “Big Bang” and predicted that 2024 would be AI’s "primordial soup" year. “There is much potential in the air, and yet it is still amorphous," we wrote at the time. "Vision is required to convert it into something real, tangible, and ultimately, impactful.” Today, the AI ecosystem has hardened. There are now five “finalists” in the race for biggest model. Nvidia’s Blackwell chip is shipping this December. Data centers are entering full-on build mode. If 2024 was the primordial soup year for AI, the building blocks are now firmly in place. AI’s potential is congealing into something real and tangible – embodied by physical data centers that are rising up all across America. In a new post, we share three predictions for the year ahead: Prediction 1: LLM providers have evolved distinct superpowers—this should lead to incremental differentiation and a contested pecking order in 2025. ● OpenAI= Brand ● Anthropic = Talent ● xAI = Data Center Scaling ● Google = Vertical Integration ● Meta = Open-Source Prediction 2: AI Search is emerging as a killer app—in 2025, it will proliferate. ● Sematic search with AI is more powerful than navigational search ●  Perplexity has captured lightning in a bottle ● Specialized search engines for doctors, lawyers, are emerging     ● AI search maps onto the “theory of mind” of the target persona Prediction 3: ROI will remain problematic and CapEx will begin to stabilize in 2025. ● AI's $200B question and $600B question remain unanswered ● In 2024, Big Tech was nervous about falling behind their competitors ● Now, they have their arms locked firmly around the AI revolution ● In 2025, data center spending will start to stabilize at current levels https://lnkd.in/g4R5QCZk

When YouTube started in 2005, broadband was just coming online. It wasn’t clear the internet could even support playing video in a browser. One often-overlooked part of the early YouTube story is how the scrappy team hacked together novel innovations that scaled to occupy 30% of the internet’s traffic in a matter of months.

YouTube started as a dating site. Even after pivoting, at first no one noticed. Here are cofounders Steve Chen, Chad Hurley, and Jawed Karim, “depressed” that YouTube had only 40 videos and wasn’t catching on. Network effects are hard to get started—even for YouTube. Hear the story of how the founders got the flywheel started and rocketed into the zeitgeist, on the new episode of Crucible Moments. 🔗 👇

The future of human-facing AI isn't about replacing people—it's about enabling them. Take Rox, which provides AI augmentation for some of the best sellers in tech, including some at OpenAI, MongoDB, and Ramp. Rox helps them build even stronger relationships with their existing and prospective customers. The brilliant team at Rox (Ishan, Avanika, Shriram, Diogo, and company) built an auto-send capability that would allow sellers to automatically email potential buyers. But...they removed it. They found that the AI in conjunction with human judgment AI improved results by 3x. When an AI is human facing, Human + AI Agent is much better than AI Agent alone.

AWS re:Invent is amazing this year! The energy and excitement is contagious. We’re honored that Cobot - Collaborative Robotics, Inc was spotlighted in AWS CEO Matt Garman’s keynote at Amazon Web Services (AWS) re:Invent 2024. The keynote, packed with new innovations, featured Proxie, our cobot designed to handle material movement tasks in dynamic environments while working seamlessly alongside people. The video let me share more of our vision for robots that work alongside us in every sector, starting out with “Our preconceived notion of robots is they lack some empathy, they lack some interactivity; I don’t think it has to be that way.” We're excited to be working with AWS as well as industry leading customers like Maersk, Mayo Clinic, Moderna, Owens & Minor, and Tampa General Hospital to solve real-world automation challenges. Thank you to AWS for sharing more of our story. #reinvent #innovation #robotics