Euwyn Poon

Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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Very Insightful Itamar Friedman Systems thinking and design isnt old school or outdated . In AI systems where outputs are probalistic than deterministic.. Systems thinking is all the more needed.

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Every #VentureStudio GP knows some portfolio bets won’t hit. That's expected - and it's one of the reasons studios are such a powerful vehicle for innovation. And while a venture's failure might be what's visible to the outsider, what keeps them up at night isn’t failure at the venture level — it’s failure at the systemic level within the studio. One bad entity design. One IP misstep. One governance gap. That’s how studio operations fall apart. We break down how to spot (and fix) these cracks before they turn into fault lines in our latest paper, "The GP Dilemma" - DM me and I'll send you a copy!

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NYC is losing young technical founders to SF — and it’s not about vibes. It’s about cost of entry. SF has far more entry infrastructure than NYC: i.e. the housing, community, and early support (financial and otherwise) that lets founders start building before they raise capital. This is widening the gap between the two cities' tech sectors. We are specifically calling for ideas (and hopefully action) to address NYC’s dearth of hacker houses: physical spaces that combine housing, workspace, community, and early peer support. I’m convinced that seeding hacker houses, if done right, is a low-cost, high-impact way to attract more young technical founders to NYC — and critically, something this community can actually do. And we should. The data is stark. Venture investment in NYC is ~19% of SF’s total — the lowest since 2017 — and the biggest, most innovative companies (especially in AI) are overwhelmingly being built in San Francisco. People who want to be entrepreneurs tend to work where those companies are. Unsurprisingly, many students and young builders assume they must go west. But do they actually want to — or is it just easier to get started there? I spent significant time in the Bay last year, and one difference stood out immediately: SF is dense with hacker houses and founder residences that help people get from 0→1. These resources are especially critical for recent grads and first-time founders who might lack capital or built-in networks. NYC may have long-term pull, but at the earliest stage, higher upfront costs and friction (recent Economist data suggests ~50% higher rents than SF) push many founders away. Hacker houses may sound anachronistic, but they’re real centers of gravity. We estimate SF has at least ~10x more active hacker houses than NYC, and that these houses have helped foster hundreds of billions of dollars in market value. I’m an NYC tech evangelist. I’ve worked on tech ecosystem development at New York City Economic Development Corporation, helped design national innovation programs for the Obama White House, and now invest in early-stage companies as a GP at Max Ventures. From a dollars-to-impact perspective, seeding hacker houses in NYC is one of the most efficient levers the city can pull. We wrote an overview doc (linked below) that explores this concept — and we'd welcome feedback from the NYC tech community. We are also hosting a small series of conversations — starting with a dinner in February co-hosted with Tech:NYC, Keel (Brent J. Smith), Company Ventures and Inspired Capital — to bring together leaders across tech, real estate, and policy. 👉 If you’re a founder, operator, VC, student, or have built / lived in a hacker house: • Does this resonate? • What would make this work in NYC? • Who’s already doing something adjacent we should talk to? Would love to connect if you’re interested in contributing or joining the conversation.

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DealWire.TECH Deal of the Week - Feb. 20, 2026. Waymo raises $16B to scale robotaxi infrastructure Deal: $16B late-stage round, Valuation: ~$126B Lead investors: Dragoneer, DST Global, Sequoia, Alphabet Waymo, the autonomous driving unit of Alphabet, has raised a massive $16 billion late-stage round, valuing the company at approximately $126 billion. The financing brings together leading global venture and crossover investors, with Alphabet continuing as the strategic anchor. The raise comes as Waymo transitions from years of R&D and pilots into full-scale commercial deployment. The company already operates fully driverless ride-hailing services in multiple U.S. cities and is targeting rapid geographic expansion, with ambitions to reach 1 million weekly rides by the end of 2026. The new capital will accelerate fleet deployment, expand into new urban markets, and build the infrastructure required to support large-scale autonomous mobility networks. Why this matters: • Autonomous driving becomes infrastructure Waymo’s $16B round reframes robotaxi networks as long-term infrastructure assets rather than experimental tech. • Part of the trillion-dollar AI infrastructure cycle Unlike foundation model raises, this capital is flowing into AI deployed in the physical world—vehicles, sensors, and city-scale operations. • Winner-take-most dynamics emerging Only a few companies globally can fund autonomy at scale, making capital access a key determinant of long-term leadership. • Capital intensity becomes the moat Success will depend not just on algorithms but on financing and operating large fleets and urban logistics networks. • Structural advantage for Waymo More than a decade of development, billions of miles of data, and deep integration with Alphabet’s AI and compute stack give Waymo a meaningful edge as competitors like Tesla and Cruise continue to push forward. • Start of the AI transport wave Robotaxis are likely just the first step toward broader AI-driven autonomy across trucking, logistics, maritime, air cargo, and drone fleets. DealWire Takeaway: Waymo’s $16B financing marks a turning point: autonomous driving is shifting from frontier technology to city-scale AI infrastructure. As AI moves into the physical economy, the winners will be those who combine advanced algorithms with capital, data, and operational scale. Waymo’s latest round positions it among the frontrunners in the emerging autonomous transportation stack. #DealWire #Waymo #AutonomousVehicles #AIInfrastructure #Robotaxi #VentureCapital #FutureOfMobility #ArtificialIntelligence

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🚨 Founders: If you're not exploring cross-industry alliances, you're playing the wrong game. Some of the biggest breakout companies didn’t scale by outspending the competition they scaled by out-partnering them. 🚀 Think Figma embedding into dev workflows. 🚀 Calendly riding the rails of Zoom and Salesforce. 🚀 Zapier integrating with Trello and Slack before raising big money. 💡 The playbook? Fuse your solution with another industry's infrastructure and unlock distribution, data, or demand without burning capital. Cross-industry alliances do 3 things: 1. Collapse time by borrowing someone else’s audience. 2. Unlock non-obvious use cases that give you strategic moats. 3. Increase your valuation before the first funding conversation. If you're a startup founder and you’re stuck thinking, “We need capital to grow,” you’re asking the wrong question. Ask instead: 👉 “Who’s already serving my customer in a different way and how do we win together?” That’s how exponential growth actually happens. 💬 Founders: Which alliance would double your reach in 90 days? #Startups #GrowthStrategy #VC #EarlyStage #FounderTips #Platform #AI

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This valuation tells founders who capital is for. Waymo raising at a roughly 110 billion valuation is not about revenue today. It is about category ownership tomorrow. Investors are paying for inevitability. The belief that autonomous mobility becomes baseline infrastructure. For founders this clarifies a harsh truth. Capital is still abundant, but it is highly selective. Markets are rewarding companies that look unavoidable. Not just impressive. That means clear leadership in one narrow problem. Clear proof that losing to you would be expensive. If you are building in a capital heavy space this changes the pitch. You are not selling traction. You are selling why no one else should win. The danger is copying the valuation logic without the substance. Big numbers only work when paired with dominant position. If an investor asked why your category should consolidate around you what would you say?

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Super exciting to see reports this morning that Waymo is in advanced discussions to raise $10–15B at a valuation near or above $100B, with Alphabet expected to anchor the round. That would be a major step up from Waymo’s prior ~$45B valuation in 2024 and a clear step change in investor confidence. Notably, Waymo has not raised this year, despite the broader AI funding frenzy. The size and structure of the round also make this feel like a step toward an eventual spinout or IPO. This matters because capital supercharges growth. Waymo is past the “does this work?” phase and firmly in “how fast can we scale?” mode. The company has already logged ~14M rides this year and expects to reach ~1M rides per week by late 2026 as it expands into markets like Miami, Dallas, and Philadelphia, including expanding onto freeways. At the same time, competition and consumer expectations are accelerating. In markets where Waymo operates, fully driverless rides are becoming normal rather than novel. Once people can reliably hail a car with no one in the driver’s seat, tolerance for “pilot programs” and distant timelines drops quickly. The race is no longer about whether robotaxis work. It is about who can scale them first, safely, and everywhere — a win for consumers who get cheaper, safer, and more reliable rides.

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"Build the event you wish existed" That's what we at Monadical did last week at #NYTW. We wanted an AI Engineers discussion for Engineers. There's always a lot of events out there for VCs to network, or for startups to learn about G2M, but very little on lessons learned from actual engineers in the field. So that's the event we hosted. Big thank yous to our awesome panel, Roy Pereira, Ben Cohen and Corey J. Gallon. Here's the key takeaways and the AI tools we're using. 🚀 All three panelists independently called AI Agents the most transformative LLM application they’ve used. They specifically called out Claude 3.5 Sonnet for its accuracy and reliability. 🪨 We dug into how LLMs are “jagged”, not general. They can be shockingly good at some tasks and completely fail at others. Everyone agreed: good evaluations are critical (and hard.) 🧪 Corey noted how public benchmarks and reality are two different things. Most public evals are saturated or gamed. ♊ Ben emphasized that AI projects are actually two projects: building the tool and building the evaluation process. 🧱 We explored how falling dev costs may impact startup defensibility and labor demand. Roy shared that founders are already shifting strategies in response. ⚒️ In a world of daily AI launches, the panel discussed how they decide what’s worth attention, and what’s just noise. They called out tools like Goose, Aider, Claude Code, and Monadical’s own Cubbi, which helps run agentic workflows safely in dev environments. (links in the comments). CTA: What would you want to hear in an AI Applied Engineering talk you attended?

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