Stu Smith

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Stu Smith

Stu Smith

@stuartdsmith

Rarely on Twitter | Investor at @ScribbleVC | Co-Founder at @CoughdropCap (@Superhuman @BankMercury @LatticeHQ @VardaSpace + more) | Michigan 🏈 Go Blue! 〽️

Bend / SF 가입일 Aralık 2008
2.4K 팔로잉1.7K 팔로워
고정된 트윗
Stu Smith
Stu Smith@stuartdsmith·
Belated post: excited to share I joined @ScribbleVC last year. Since 2015, I’ve tried to be like the best VCs I worked with as an operator/founder — show up when needed and stay out of the way when not. That’s also the Scribble way. Proud to be on board!
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Tony Zhao
Tony Zhao@tonyzzhao·
We raised $165M at a $1.15B valuation to stop doing demos. 2026 is about 1) deployment and 2) research. We will start shipping Memo with our new frontier models in a few months. Our series-B is led by Coatue, with Thomas Laffont joining the board. ->🧵
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Bloomberg TV
Bloomberg TV@BloombergTV·
Sunday's dishwasher-loading, laundry-folding robot starts beta testing this year. CEO Tony Zhao explains how the robot learns — and why it wears a hat bloom.bg/3NAxIxQ
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Karina Nguyen
Karina Nguyen@karinanguyen·
Excited to release PostTrainBench v1.0! This benchmark evaluates the ability of frontier AI agents to post-train language models in a simplified setting. We believe this is a first step toward tracking progress in recursive self-improvement 🧵:
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Elizabeth Weil
Elizabeth Weil@elizabeth·
SO excited to welcome @stuartdsmith to @ScribbleVC! He's a triple threat (founder + operator + investor) with a stellar track record. But what makes him even more rare is that he's kind, humble, & a joy to talk to every single day. Big win for our team & our founders!
Stu Smith@stuartdsmith

Belated post: excited to share I joined @ScribbleVC last year. Since 2015, I’ve tried to be like the best VCs I worked with as an operator/founder — show up when needed and stay out of the way when not. That’s also the Scribble way. Proud to be on board!

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Scribble Ventures
Scribble Ventures@ScribbleVC·
We are pumped to welcome @stuartdsmith to @ScribbleVC! This is great news for both our team & our founders. Stu is kind and humble, yet has backed some of the best founding teams on the planet. He's a triple-threat - a founder + operator + investor, and he brings that to bear for our founders as they build their companies and their networks. Finally, he's a wonderful person and teammate, and we look forward to every conversation, every meeting, every decision, and every team offsite with him. We are thrilled you joined us, @stuartdsmith!
Stu Smith@stuartdsmith

Belated post: excited to share I joined @ScribbleVC last year. Since 2015, I’ve tried to be like the best VCs I worked with as an operator/founder — show up when needed and stay out of the way when not. That’s also the Scribble way. Proud to be on board!

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Scribble Ventures
Scribble Ventures@ScribbleVC·
"Have you really thought through your moat?" "Is speed really your only lead right now?" @elizabeth joins @glennsolomon @notablecap on hypergrowth lessons from the early days of Twitter & her early investments in Whatnot, Slack, Figma, + more.
Notable Capital@notablecap

On the latest Notable Perspectives podcast, @glennsolomon talks with @elizabeth Weil about scaling Twitter from 50 to 3,000, building @ScribbleVC, and why speed alone isn't a moat in AI. Her advice to founders: "Why you, why this, why now?"

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Stu Smith
Stu Smith@stuartdsmith·
Belated post: excited to share I joined @ScribbleVC last year. Since 2015, I’ve tried to be like the best VCs I worked with as an operator/founder — show up when needed and stay out of the way when not. That’s also the Scribble way. Proud to be on board!
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ben
ben@benhylak·
today, we're introducing self diagnostics: the first ever way for agents to proactively self-report issues they encounter. welcome to the future of agent observability.
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Proximal
Proximal@ProximalHQ·
Today, we are announcing Proximal. Proximal is a research lab for data. Our core belief is that data which is complex enough to teach today’s frontier models is not bottlenecked by domain experts, but by great ideas and excellent software. We are excited about a world in which coding agents can autonomously run for multiple weeks, solve the hardest technical problems and discover novel ideas that advance progress in various domains of science and engineering. We believe that we are not far from this future, but that the biggest bottleneck preventing us from achieving it is training data. Many companies work on data, but most of them are approaching it the wrong way. Historical capability breakthroughs are the result of creative engineers discovering scalable data collection methods, not thousands of contractors manually writing task demonstrations. Inevitably, the potential impact of human data will become smaller and smaller as model capabilities increase: agents are already outperforming most humans in many domains - the number of experts that are capable of judging model outputs shrinks with every new model release. Proximal is a new data company. We are not a recruiting firm or a talent marketplace, but a research and engineering organization that treats data as a problem which deserves the same level of rigor as work on training algorithms and model architectures. We think that this is the most impactful work towards agents that can autonomously solve complex technical problems, and intend to share our research and progress in the open.
Proximal tweet media
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Dave Nunez
Dave Nunez@capitaltruist·
Today a reset is taking place. The senior engineer making a million dollars a year in San Francisco uses the same frontier coding agent as the junior engineer in the Midwest. We talk to companies every day that are taking advantage of this reset, adopting expensive tools, putting in long hours, and still hitting a wall when AI struggles to understand their business context and intent. The real truth is somewhere between the teams’ heads and the codebase. Falconer gives everyone in the company, from engineering to sales to marketing to finance, a reliable source of truth. One that’s easy to contribute to and helps keep itself up to date. If you want to know what changed in your product last week, ask Falconer to write a changelog. If you want to understand how payment flows work for your new product, ask Falconer to create a diagram. If you want to capture the decisions in your long Slack thread, ask Falconer to turn it into a document. When the code changes, your PRDs, strategy docs, and runbooks get updated. Your employees are happy, your coding agents are happy. Falconer was built with lessons in mind from making engineers at Uber and Stripe the most productive in the industry. We built custom tools for top tier talent. The results were remarkable. But outside of these companies, no one has access to these custom tools. That’s what we had in mind when we built Falconer. The quality of information you feed yourselves and your AI tools is how you get the most out of them and separate yourselves from the competition. You can start centralizing and curating and compounding those gains over time, or you can let the bad information multiply, rot, and pollute your knowledge—severely limiting your AI leverage. Everyone wants more knowledge, and everyone has knowledge to contribute. Falconer is now available as your source of truth to achieve the productivity gains you’ve been searching for.
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Falconer
Falconer@falconer_ai·
Craft and beauty are finally coming to internal docs. Today we're previewing Falconer: the single source of truth for company knowledge. We're still working through our waitlist, but are now excited to take on more demo requests. Engineers spend way too much time answering repeated questions and searching for outdated information. We experienced these problems during hypergrowth at Uber and Stripe and thought, "What if we applied external docs treatment to our internal docs?" That simple approach achieved pretty remarkable results for productivity. And now Falconer is building the AI-native version of those platforms for everyone. With Falconer, your internal docs are: - In one place - Always up to date - Easy to find - Synced with your data Coding agents allow us to generate more code faster than ever...but that code is poorly understood and out of step with the company's crown jewels: business context and tribal knowledge. Falconer's mission is to connect teams and agents with a shared memory system—always available and always accurate. We're working on it, and will have much more to share soon.
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Kevin Weil 🇺🇸
Kevin Weil 🇺🇸@kevinweil·
💥 Today we say “hello world” from OpenAI for Science. We’re releasing a paper showing 13 examples of GPT-5 accelerating scientific research across math, physics, biology, and materials science. In 4 of these examples, GPT-5 helped find proofs of previously unsolved problems.
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Sunday
Sunday@sundayrobotics·
After 18 months in stealth, dozens of prototypes, millions of real-home demonstrations, and one final all-nighter, we’re thrilled for you to say hello to Memo
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Zack Chapple
Zack Chapple@Zackary_Chapple·
One of my favorite parts of being a founder is being able to work with amazing people. Now that everything is signed I'm super excited to announce that the @ZephyrCloudIO team is gaining a new team member. Welcome to the team @kdy1dev !!!
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maximus greenwald
maximus greenwald@MaxPGreenwald·
Introducing: Marketing Ops Agent by Warmly, // the #1 AI to create the most precise, real-time, auto updating list of target accounts ⭐️ Bluntly: this is the most powerful launch in Warmly’s history. This agent is the result of 250+ interviews with Marketing & Demand Gen leaders on what prevents them from hitting pipeline. ️ It's also the only marketing tool in the world where our promise is that you'll get LESS PIPELINE from using it. LESS? Yep. Haven't you heard less is the new more? Here’s why: I’ve been building Warmly now for 6 years now to give Marketers Superpowers & it’s been a hell of a journey. Along the way I've dealt with the same problem as my customers: building pipeline is incredibly hard. And whenever you do grow pipeline, what's your reward? the board moves your goal posts further. I spoke to a VP of Demand Gen at a Series C company last week and he admitted to juicing pipeline to hit his goals: he loosened his ICP definition & let just about any meeting with a pulse count as pipeline. All of a sudden, pipeline looked great. Until close rates plummet. We've all been there. Like most Demand Gen marketers or GTM Engineers out there, your inclination is that MORE Pipeline is better. But it's not. ANY Pipeline ≠ GOOD Pipeline. GOOD Pipeline = GOOD Pipeline. So we built something so crazy that it makes your pipeline go down. We make your pipeline leaner and you'll thank us for it. Warmly’s new MOPs Agent delivers targeted, precise, GOOD Pipeline. And it's already helping over a dozen of our customers solve their pipeline problems. How? Our MOPs Agent will prioritize & score your TAM to create powerful lead lists that your sales team can truly believe will close. The lists tell you the story on why these particular leads are good (or bad) - showing you the intent, fit & engagement behind the value of this lead or that lead. Leverage powerful features to build an amazing lead list like: 1/ AI Enrichment to ask any niche or complex questions about leads to help you filter for the good ones 2/ AI Buying Committee Finder to find the group of people cross-functionally who would be responsible for closing this deal 3/ AI Intent Signals to pull in 1st, 2nd, & 3rd party intent data to know who is in market, now. 4/ A Live-Updating capability that creates Dynamic Lead Lists that update hourly. Head over to our website today to request a demo Warmly, Max Ps. What other kick-ass AI Marketing Agents does Warmly offer? → Our Data Agent finds warm leads from 10+ intent signals like Person-Level Website De-Anonymization → Our Outbound Agent automates outreach + nurture to those leads on Email & LinkedIn. → Our Inbound Agent uses an AI Chatbot + Pop Ups to increase conversion rates on those leads → Our SDR Agents at Warmlegency (Humans) help our customers utilize our AI to book meetings daily.
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ben
ben@benhylak·
today, we're announcing our fundrai-- jk. we're shipping. meet raindrop experiments 🧪
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