Charles Wang @jetmanwang

I’m starting a new early-stage AI fund, doing what I love: partnering with founders from company formation on bold bets, long before consensus. The fund’s LPs will include Sequoia, Jeff Dean, Sachin Katti, Philip Wong (my Stanford professor and Chief Scientist adviser to TSMC), and others whose work has shaped our industry and how I think about AI’s future. I’ll remain a partner at Sequoia and keep serving on my boards on Sequoia’s behalf. Sequoia has been my home for the past 11 years. I joined as the youngest investor the firm had ever hired. I grew up here. Through years of intense debate and shared work, I found lifelong mentors and friends who took me under their wing and taught me this craft. They taught me to aim high and take big swings. I’ll carry that into what I build: outsized ambition, relentless truth-seeking and curiosity, and a refusal to become complacent. Working alongside founders has made me want to build something of my own: a firm shaped from day one around the convictions I’ve developed over the past decade. Life has taught me not to take time for granted. This is how I want to spend mine. Why now We’re seeing a new way of building companies in today’s AI era. Research and products often advance together. A breakthrough can open a market or accelerate a business far faster than expected. Some companies require extraordinary capital and compute early on. Others reach meaningful scale with remarkably small teams. The rules for how big these businesses can get, and how fast, are being rewritten. But early on, the technology is unproven, the resources required enormous, and the vision seemingly implausible. This is what I love most: seeing the potential right from the beginning, and helping founders realize their full scale of ambition. More than ever, it starts with an extreme willingness to believe early, with bold, independent conviction in a founder’s technical insight before any product or market validation. Then, it means helping founders take the biggest swings, giving the rare, long-term patience to see those bets through uncertainty, ambiguity, and turbulence, and serving as a level head when the stakes are highest. I learned this kind of partnership at Sequoia. It’s the foundation of the firm I’m building. Believing before consensus My fascination with AI’s potential took root at Stanford in the early-to-mid 2010s, studying computer science and working in Andrew Ng’s lab. The friendships I formed connected me to a community whose people and ideas would help shape modern AI and build some of our generation’s defining companies. What stayed with me was the gap between what those people saw was possible and what the wider world could imagine. I’m drawn to founders pursuing ambitions that sound impossible today. I start with a simple question: “What if everything goes right?” Then we work backward together to make it happen. In 2023, Deepak and Abhinav set out to build a general-purpose robot brain at @SkildAI, before physical AI was a consensus bet. Their sim-to-real breakthroughs gave me conviction where earlier robotics approaches had fallen short. But the data flywheel required deployment at scale. We made commercialization as urgent as research and brought in strategic partners like NVIDIA and SoftBank to support the ambition. Three years in, Skild is advancing the frontier of physical AI with nine figures in annualized revenue. In 2024, Ioannis and Misha founded @reflection_ai with an insight into scaling reinforcement learning. As that grew into the ambition to build a Western frontier lab for open models, the hard question was how a startup competes with labs spending tens of billions. An introduction to NVIDIA and many compute calls and recruiting events later, the team has built Beam, now one of the leading US open models. In 2025, Anna and Azalia, the co-creators of AlphaChip, founded @RicursiveAI to design models and hardware together. From day one, we made early customers and ecosystem partners a priority. Today, they are showing order-of-magnitude improvements on real workloads, working with some of the industry’s most consequential players, and reaching a defining inflection point. The ambition keeps growing as these companies scale. @linear has always had a kind of magic to it. Now it’s the system a new generation of AI companies builds on, for teams and agents alike. @tavus saw early that we’d one day talk to AI the way we talk to each other. Today, it’s building the human computing interface for a world of AI colleagues. @Mach_Industries began as hydrogen experiments in an MIT dorm room. It has since become one of the most exciting next-generation defense companies. Making the ambition possible Being a first believer is only the beginning. Compute falls through. A deep-pocketed incumbent makes your mission its top priority. A breakthrough changes the opportunity and the capital required overnight. These are stomach-churning moments, and early belief carries a responsibility to help make the bet work. This is the partnership I love: turning the full ambition into concrete steps. Raising capital, securing compute and strategic partners, recruiting exceptional people, and winning the first customers together. Thinking several moves ahead while solving what’s in front of us. And as breakthroughs open new possibilities, helping founders dream even bigger. Thank you To the founders I’ve worked with: thank you for trusting me and Sequoia to be your first partner and first believer. It’s been the joy of a lifetime, and I can’t wait to keep building together. Thank you to Alfred and Pat for your leadership of Sequoia and your support of my next chapter. To Roelof, for bringing me into Sequoia and believing in me from the beginning. Alfred and Roelof, you have been mentors in investing and in life. So much of what I know, and the investor I’ve become, comes from your guidance and generosity over the years. To Bill, for the close partnership and wealth of knowledge, always wrapped in humility. To Shaun, for showing me how to think deeply and imaginatively. To Michael Moritz, for inspiring 22-year-old me to dream big. To Doug, for teaching me to keep things simple. To Bogie and Jess, for bringing joy to the everyday and perspective on what matters. And to all my Sequoia teammates, for the friendship, camaraderie, and lessons I’ll carry with me. To my family, especially my husband and my brother, who have each started companies of their own: thank you for giving me the courage to take this leap. Let’s get to work!

花了 300 美金、折腾了 40 多个 Grok Bot，我把全网的玩法整理成了一个开源库：Grok Bot 中文配方库。 维护的不只我一个：Grok Bot 每天找料，Claude Code 逐条核实、写短评。 81 个核实过的项目，9 个能直接抄的配方。 感兴趣来个 ⭐ github.com/sit-in/awesome…

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芯片行业里从设计到量产两年一代已经算快了，但 Elon 想要 Terafab 一年十版，把逻辑芯片、存储、封装、光刻掩膜全部塞进同一栋楼，造出完整的计算机、测试、改掩膜、再造，让整个反馈回路在内部转起来。 这是他所有公司的共同方法论，而且屡次被验证过！把任何技术的进步拆成「单位时间迭代次数 × 每次迭代进步」。SpaceX 的星舰就是这么做的，靠硬件迭代的密度碾压对手。他现在想把这个方法搬进芯片行业，而芯片恰恰是全世界最不适合“炸了再来”的行业之一，所以他说这个行业风险厌恶太重😆 我觉得最值得关注的是这个逻辑和 AI 的交汇。如果 AI 能接管大量芯片设计和验证工作，设计端的迭代速度本来就会暴涨，那时候瓶颈会完全转移到“把设计变成实物并测出结果”这一步，谁拥有最短的物理闭环，谁就能把 AI 带来的设计红利真正兑现。 到时如果 AI 真能自己设计芯片，并通过工厂来自动化地生产芯片，那硅基循环就正式开始了⏩

we’re launching Open Intelligent UI :) built with OpenUI, it brings the @ChatGPT-style Intelligent UI experience to your own stack. use it with hosted models today, or wire it up to local models through tools like Ollama, LM Studio, etc. the goal: the same kind of rich, generative UI experience - but open, cheaper, faster AND inside your own apps. this is just the start. we’ll be adding a lot more examples, integrations, and capabilities to the repo over time. Check it out: github.com/thesysdev/open…

Visharad @KashyapVisharad

3 weeks ago

fun fact: openui.com isn’t owned by @OpenAI. It’s owned by us :) OpenUI is the open standard for Generative UI - and yes, it’s actually open source and MIT licensed, unlike someone else 👀 vibe-coded this demo after seeing the launch video for what ChatGPT is

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GPT-6 and Intelligent UI, now rolling out in ChatGPT for everyone. Intelligent UI in ChatGPT delivers fast, interactive answers that make everyday questions more visual, complex topics easier to grasp, and interactive tools for your task available on the spot.

The way Steve taught us to care about every detail, every experience, every person, still guides our work today. Forever grateful.

杨植麟昨天在中科大的演讲，台下看他就像看摇滚明星，亮点我总结一下： 1. 月之暗面的公司名，取自著名摇滚专辑，玩乐队的灵感 2. 大模型的本质是把能源转化成智能 3. Kimi不仅要训练大模型，还要提升Token效益，降本增效 4. 公司核心算法员工平均年龄20几岁 5. 中国可以培养出全世界最好的本科生

Crypto Doggy 叫我狗总 @CryptoDoggyCN

2 months ago

月之暗面Kimi也抢时间上市了，你懂的，9月Anthropic的ipo很容易把板块都带飞 公司目前300多人，平均年龄不到30岁 上市后三分之一可能成为千万富翁，杨植麟身价可能打到1600亿元

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I wrote about the state of AI, why I’m concerned about the next few years, and the choices we need to make to keep the future in humanity’s hands. An Alien Mind: openai.com/index/an-alien…

Today we're releasing data on models accelerating research at OpenAI. Recursive self-improvement could be the most important contributor to AI capabilities over the next few years, but by default it will only be seen inside a few frontier AI labs. Being transparent is more urgent than ever, so we can inform the public discussion on whether and how to pace model development. I ask other AI companies to do the same. openai.com/index/research…

感谢大家的留言！真的没想到大家对 Codex 的讨论这么热烈，已经有 1800+ 多条回复和提问了。如果没能一一回复，还请见谅！

Derrick Choi @derrickcchoi

2 months ago

最近搬到新加坡，想听听大家对 Codex 的意见：最希望我们改进什么？哪里用起来不太顺？ 中英文都可以，直接回我就好！

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@heisredminded @qwen_cloud it already has the "Set as default" button

デザインがダサかったQwen Studioのデザインが良くなってる！

We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With just 27B parameters, it outperforms Qwen3.7-Plus overall and shines in real-world coding & office workflows. - 262K native context, easily extendable to 1M tokens via YaRN. - Built for builders. Highly efficient, high-quality, and licensed under Apache 2.0. 🚀 The open weights for Qwen3.8-2.4T-A95B (Max-level) have also been released recently. Whether you're shipping lightweight applications with Qwen3.8-27B locally or building agents with Qwen3.8-2.4T-A95B, they're yours now! Download, deploy, and build something we haven't imagined yet. 👀👇 - Hugging Face： huggingface.co/collections/Qw… - ModelScope： modelscope.cn/collections/Qw…

Meet Qwen3.8-Max: A New Bar for Coding and Cowork.

📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub：github.com/qwen-code-dev-… - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀 📖 Blog: qwen.ai/blog?id=qwen3.8 ✅ Qwen Studio: chat.qwen.ai/?models=qwen3.… ⚡ API: qwencloud.com/models/qwen3.8…

@F2aldi @Alibaba_Qwen try chat.qwen.ai

new post on harness engineering for AI self-improvement: lilianweng.github.io/posts/2026-07-… It is hard to forecast how much the future of RSI will rely on harnesses. Likely harness engineering will evolve in the direction of self-improvement and enable auto-research, and, in turn, smarter models keeps harnesses simple. Even when many harness improvement get eventually internalized into core model, the need to specify goals and context will not disappear.

Stop overthinking what stocks to buy Elon Musk was asked What Stocks He Would Buy at the end of 2025 • Google $GOOGL • Nvidia $NVDA “AI and robotics and maybe space flight are going to be overwhelmingly almost all the value” Both stocks up 20% since the interview