Jesse Pollak

Terminal Use (YC W26): Vercel for background agents. Terminal Use is hosting infrastructure for background agents that makes harness engineering easy. https://lnkd.in/gv99wN2t

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EQUITYZEN & FORGE GLOBAL "A flurry of recent acquisitions may mark a structural shift in how traditional financial institutions approach private share trading. Morgan Stanley’s announcement that it will acquire EquityZen on 10/29 and Charles Schwab’s acquisition of Forge for $660mm (~5.3x 2026E sales) on 11/6 may signal that incumbents are no longer content to simply partner with independent marketplaces. Rather, they are moving to own them outright, integrating pre-IPO investing into their broader wealth offerings. The suggestion is that private share distribution is emerging as a valuable differentiator. Large financial institutions are betting that controlling the client relationship—particularly with high net worth investors—creates a channel to scale private share distribution. Secondly, scale and data appear to be emerging as competitive advantages. Marketplaces with deep order flow and transaction history can generate pricing and valuation intelligence (like NPM’s Tape D product) that smaller players cannot. To us, the deals also signal a broader verticalization of private market infrastructure. We expect a continued trend towards tighter integration across the stack—combining tender administration, cap table administration, secondary trading, data, and wealth distribution into unified platforms. The result, in our view, over time will be fewer, larger incumbents in private markets that dominate liquidity and pricing power. Will consolidation continue? Our crystal ball is cloudy, but interest in the asset class is clearly robust.  Beyond banks, other theoretical acquirers include large broker dealers and wealth managers, both of which could integrate private share trading to offer differentiated wealth products. In addition, traditional asset managers, many of which are already expanding into private credit and venture secondaries, could pursue acquisitions.  Finally, certain fintechs could look to integrate private market liquidity into their platforms." Nasdaq Private Market

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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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CRV Security: Request for Startups I never know if this actually works for our friends over at YC but figured we'd try. Here's what we want to fund in 2026! 1. Golden Artifacts: Think Chainguard but more broad. Artifact attestation exists for open source. Almost nothing exists for internal software — especially the vibe-coded tooling now running in production. We want the company building cryptographic proof of secure software delivered from secure artifacts: who built it, how, and whether it was reviewed. If more things are being yeeted into the world via Claude Code (myself included), this feels like an issue. 2. MCP & Agentic Security: Agents are getting real credentials and taking real actions. The security posture of most orgs around this is basically zero. That changes fast. You'd never give an employee hardcoded API keys or write access to your email without supervision/trust. Why give it to agents? 3. AI Governance: Boards are asking CISOs to account for AI risk. CISOs have no good answer other than "Palo has a module" 4. Next-Gen Endpoint: CrowdStrike was built for a world of static binaries and human operators. AI workloads, cloud-native infra, and AI-assisted attackers need a new architecture. The category is ready to be reinvented. 5. Networking in the AI Era: Zero trust was designed for humans. What does network security look like when the entity requesting access is an agent? Nobody's really solved this. 6. Email Security + Next-Gen Phishing: LLMs have made spear phishing infinitely scalable. I've never truly understood why Abnormal and KnowBe4 aren't one company. Maybe this time it's different. 7. Frontier Security Lab: We'd back a credible, well-staffed lab focused entirely on red-teaming models and setting the evidentiary standard the industry needs as LLM built apps become the norm. 8. Dependency Security: That Actually Remediates Malicious and vulnerable dependencies are a top attack vector. The tooling is mostly noise — scanners that don't close the loop. The winner here ships fixes, not just alerts. 9. Critical Infrastructure Cyber: Data centers, satellites, power grids, undersea cables. The physical backbone of the internet is increasingly exposed and wildly under-defended. We have data centers in space, for God's sake. Surely we need better cyber for critical infrastructure? 10. PAM for the Modern Era Legacy: PAM was built for static roles, human users, on-prem directories. Cyberark was founded in 1999.....Agents, ephemeral workloads, and cloud-native infra have broken all of those assumptions. Is anyone rebuilding this from scratch? If you're building in any of these areas — or something we haven't thought of — reach out. james@crv.com

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My two cents on the Claude Squeeze Application layer AI companies being built right now will not survive if they incorporate human in the loop as a core part of how work gets done. If your agent requires a human to approve the output, you’re building a better UI for Claude. If your agent helps an accountant do more accounting or a lawyer do more lawyer-ing, you might have a business, but companies won’t pay a lot for it. It’s not that Claude is going to steal your customers. It’s that the delta between what you’re offering and what someone gets from just using Claude directly is getting smaller every month. The complexity you’re solving for, better UX, smarter prompts, cleaner folder structures, is real, but it’s not worth a big check. And buyers are figuring that out. I’m already seeing it. A real estate brokerage looking at AI underwriting tools realized they can dump a rent roll straight into Claude and get 80% of the output for free. They’ll pay a little more for a better interface, but not a lot more. If you’re not doing the job end-to-end, your value is the productivity layer. And Claude is coming for the productivity layer. Hot take: I don’t think Harvey would get funded in 2026. They were funded when they were because the models weren’t advanced enough to reveal how thoroughly they’d eat the application layer. Harvey may survive, they’ve built real brand and enterprise relationships. But with that exact pitch today I think you’d struggle. Here’s what I think survives: Agents that own the outcome. They have to clear every one of these bars: 1. Fully autonomous. No human in the loop. The agent does the job, not assists with it. 2. Accountable for outcomes. Not activity. Results, and the agent is measured on that basis. 3. Mission-critical metrics. The outcomes it owns show up in the Monday morning operating review. The numbers the CEO reports. Going back to Harvey, if they said we’ll just do your legal work for you, end-to-end, accountable to outcomes, that’d be a defensible business in 2026. But notice what it is: outsourced labor with AI as the delivery mechanism. Not a productivity tool. A law firm that doesn’t charge law firm rates. Most AI companies won’t make that leap because it means owning outcomes. It’s hard. That’s what we’re building at Uniti. If you can autonomously run the entire leasing funnel for a property manager and own their rentals-per-month and conversion rate, you’re not a software vendor. Then do the same for all their workflows. You’re outsourced labor. Completely different moat. The mistake is selling the tool when they should be doing the job. If there’s a human in the loop, the customer is paying for the human’s time and your software. As models get better, the human becomes the cost center and your product becomes the overhead. The comparison isn’t your tool vs. Claude. It’s your agent vs. a full-time hire. That’s a different conversation, and a new category.

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Coinbase just turned wallets into agent-native infrastructure so software can hold identity, budget, and execution authority. That unlocks founders building autonomous operators that move money without human babysitting, and early movers will own the workflows when agents go commercial. https://lnkd.in/gAypr_23

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DeepSeek’s rise has been wild to watch. From hedge fund roots to topping app store charts, all while running models cheaper and faster than the big names? That’s no small feat. Their focus on reasoning models is especially interesting and definitely shaking things up in the AI space. #AI #DeepLearning #Innovation #TechTrends #MachineLearning #Startups https://lnkd.in/dDfmM99D

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