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Building Cursor At 23, Taking On GitHub Copilot & Advice To Engineering StudentsMichael shares the lessons that came from years of failed projects with his co-founders, why he believes programming is still essential even as AI changes how we code, and how Cursor is taking on GitHub Copilot with the conviction that all of software development will flow through models
Scaling Figma and the Future of DesignDylan shares the early challenges of building in the browser, the early risks and pivotal choices that shaped Figma’s growth, the principles that guided its product and community, and how he thinks about building tools that empower creativity at scale
Scaling and the Road to Human-Level AIJared walks through how that discovery reshaped the path to human-level AI, what it means for future models like Claude, and why even the dumbest questions can lead to the biggest breakthroughs. He reflects on memory, oversight, and what's left to solve as models grow smarter — and longer-horizon tasks come within reach.
Building Robots That Can Do AnythingChelsea traces the evolution of her team's work — from early experiments on robotic grasping and vision to today's ambitious efforts at folding laundry, tidying kitchens, and generalizing across tasks — all without hand-crafted code. Instead, they used scalable foundation models and massive datasets, teaching robots physical common sense as they learn by doing.
AI is Revolutionizing Scientific DiscoveryJohn shares how a deep learning breakthrough at CASP14 turned into AlphaFold 1 and then AlphaFold 2, delivering atomic accuracy predictions and revolutionizing biology. He explains the scientific puzzle behind protein folding, the key algorithmic breakthroughs, and the impact of making millions of protein structures accessible to researchers worldwide.
Perplexity's Race to Build Agentic SearchAravind talks about the big bet on the AI-powered browser, why agents — not just chatbots — are the next step, and how speed, accuracy, and focus help a startup compete against giants. Along the way, he reflects on co-founder dynamics, early technical challenges, and what it takes to keep building when the biggest players in the world are racing alongside you.
Building Faster with AIAndrew shares what he's learning now: why execution speed matters more than ever, how agentic workflows are changing what startups can build, and why concreteness beats vagueness when turning ideas into products. He reflects on the rise of AI coding assistants, the shifting bottlenecks in product development, and why, despite faster software, it's still human judgment and responsibility that will shape what comes next.
How We Get To AGIFrançois walks through the limits of pretraining and memorized skills, and lays out a path toward true general intelligence — AI that can adapt on the fly, reason in new situations, and invent novel solutions. He explains why abstraction and compositionality matter, how ARC became the benchmark for progress, and what his team at a new research lab called Ndea is building next.
Microsoft's AI Bets, Hyperscaling, Quantum Computing BreakthroughsSatya shares how Microsoft is thinking about this moment — from the infrastructure needed to train frontier models, to the social permission required to use that compute. He draws parallels to the early PC and internet eras, breaks down what makes a great team, and reflects on what he'd build if he were starting his career today.
The Future of OpenAI, ChatGPT's Origins, and Building AI HardwareSam traces the path from early startup struggles to building OpenAI — sharing what he's learned about ambition, the weight of responsibility, and how to keep building when the whole world is watching. He opens up about the hardest moments of his career, the limits of personal productivity, and why, in the end, it's all still about finding people you like working with and doing something that matters.
Software Is Changing (Again)Drawing on his work at Stanford, OpenAI, and Tesla, Andrej sees a shift underway. Software is changing, again. We've entered the era of "Software 3.0", where natural language becomes the new programming interface and models do the rest. He explores what this shift means for developers, users, and the design of software itself — that we're not just using new tools, but building a new kind of computer