Vineet Edupuganti

This isn’t our preferred choice ofcourse as you’ve all loved trying Fabel. Good news is that in our internal evals, good context makes Opus and Fabel score within 2% of each other.

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I had a great time chatting with Patrick O'Shaughnessy on Invest Like The Best. I've known Patrick since college, and this is the first time we've talked markets and investing at this much depth. The fundamentals of company building haven’t changed: people, products, and markets matter. But obviously, private markets have evolved substantially over my career: there are now ~6x more private unicorns than public companies with a $1b+ market cap. And at the end of 2010, just 2 public technology companies were among the top 10 in market cap; today it’s 8 of 10. AI (alongside software eating everything more generally) is clearly driving a lot of this. But it’s instructive to look at everything from the steam engine, to the early days of Facebook and Google user monetization, to real-time success stories like Databricks, Anduril, OpenAI and Waymo, to get a clear picture of where the opportunities lie. It was a pleasure to go deep on all this and more!

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🚀 Anthropic Just Transformed Enterprise AI Collaboration Claude Cowork now lets admins build private plugin marketplaces for their entire organization. Here's what just dropped: **For Admins:** Private plugin marketplaces with full control over distribution Build plugins from templates or scratch - Claude guides you through setup New unified'Customize' menu for managing plugins, skills, and connectors OpenTelemetry support to track usage and costs across teams Per-user provisioning and auto-install options **For Teams:** Slash commands now launch with structured forms Company branding throughout the interface Claude works across Excel AND PowerPoint - handles multi-step tasks end-to-end **New Connectors:** Google Workspace (Calendar, Drive, Gmail), Docusign, Apollo, Clay, Outreach, Similarweb, MSCI, LegalZoom, FactSet, WordPress, and Harvey. Plus partnerships with Slack, LSEG, S&P Global, and more. **Fresh Plugin Templates:** HR operations, Design workflows, Engineering tasks, Brand voice analysis, Financial modeling, Investment banking, Equity research, Private equity, Wealth management. Each template built with actual practitioners. Real workflows, not theory. The cross-app functionality is wild. Claude can run analysis in Excel, then automatically create a presentation in PowerPoint. Context flows between apps just like your work does. "Three waves have reshaped professional work: productivity tools, cloud and search, and now agentic AI." - Sanjay Subramanian, PwC Available now for Team and Enterprise plans. The Excel and PowerPoint integration is in research preview for all paid plans. This is how AI becomes actually useful at work. Not replacing your tools - connecting them. Thoughts on private plugin marketplaces for enterprise?👇

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Today is launch day. ClawSecure is live on Product Hunt 🚀 I've been heads down building this for months. A dedicated AI agent security platform for the OpenClaw ecosystem covering everything from skill-level audits to real-time monitoring to agent marketplace and identity protocol security. 1 in 5 OpenClaw skills are sending your data to attackers. We know because we audited 3,000+ of the most popular ones. What's under the hood: ⚡ 3-layer audit engine with 55+ OpenClaw-specific detection patterns ⚡ Watchtower monitoring that tracks code changes in real-time post-install ⚡ Full 10/10 OWASP ASI coverage across all agentic security categories ⚡ Security for agent marketplaces and agent identity protocols The opensource agent ecosystem is powerful, but the skill supply chain is wide open and bad actors are already exploiting it. We're building the verification layer to keep the community protected. Free. No signup. 30 seconds. Check it out on Product Hunt and leave us some feedback 👇 🔗 Link in comments #ClawSecure #OpenClaw #ProductHunt #AISecurity #FounderJourney

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Key takeaways: - The core shift is economic, not hype. LLMs turn “AI” into a recurring operating cost, so pilots quickly become capacity planning, governance, and ownership. - Power and timelines show up because production inference needs sustained compute capacity. When usage increases across the org, you run into procurement, security review, integration work, and infrastructure readiness challenges. - The winners are not the teams with the flashiest demos. The winners are the teams that convert compute into measurable outcomes inside a workflow with traceability and controls. - In 2026, “AI strategy” that is not tied to a specific workflow, KPI, and operating model is mostly theater. If you are building the application layer on top of the datacenter buildout, execution systems, workflow automation, data-layer tooling, compliance automation, I want to see what you are shipping. Founder intro: www.axion.ventures

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🚨 🔒 California recently launched the most powerful FREE privacy tool in the country — and most people have no idea it exists. It's called DROP (Delete Request and Opt-out Platform), and it lets you send ONE request to 500+ data brokers telling them to delete your personal information. One click. 500+ companies. Your data gone. Here's why this matters more than you think: Right now, data brokers are collecting and selling your name, address, phone number, email, SSN, browsing history, and location data — without your knowledge or consent. That data is fueling: → Phishing & scams. 54% of consumers report increased phishing after their data is exposed. When scammers know your employer and bank, their emails look real. → Identity theft. One data broker breach exposed 2.9 billion records — including SSNs for ~80% of Americans. → Stalking & domestic violence. People-search sites sell decades of addresses and family connections. For DV survivors, this is life-threatening. A federal judge's son was murdered by an attacker who bought the family's home address from a data broker. → Foreign espionage. Adversaries buy profiles on military personnel and government officials for blackmail and intelligence gathering. → AI-powered impersonation. Criminals combine brokered data with AI to build convincing deepfakes and scams at scale. → Discrimination. Brokers sort people by race, religion, and health status. One broker sold location data from 600 Planned Parenthood clinics to target individuals with ads. The old system was broken — 43% of CA data brokers weren't even responding to individual deletion requests. DROP changes that. Starting August 1, 2026, data brokers must check DROP every 45 days and delete your data within 90 days — or face $200/day fines. You can enroll right now: https://lnkd.in/gFrJi7MF It takes minutes. You verify CA residency, provide basic info, and DROP handles the rest. You can also submit on behalf of your kids or elderly parents. This is the highest-ROI thing you can do for your personal cybersecurity in 2026. Free. Takes minutes. Cuts off the supply chain feeding scammers, stalkers, and spies. Share this with every Californian you know. 🔒 #Privacy #CyberSecurity #DataPrivacy #California #DROP #DataBrokers #IdentityTheft #InfoSec

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Where is the post-training infra market still “unsolved”? The best pockets are areas where the stack is still missing a reliable primitive. Here are 4 areas where it might work: 1. Outcome-based evaluation (beyond LLM-as-judge) Enterprises care about “did the agent complete the workflow correctly?” as opposed to “did it look fluent?”. But the big challenge is instrumenting ground truth from business systems (CRM, ticketing, payments) and then turning it into automated evals. Startups that own this interface can become system-of-record for AI quality. 2. Continuous learning for agents (safe retraining loops) A lot of teams want self-improving agents, but they don’t trust the loop. The winning wedge is: gated data collection + audit trails + rollbacks + sandboxed deployments. This could be the next evolution after basic orchestration. 3. Governance + compliance automation as product There are rules in place to push companies to document risk controls, testing, and monitoring. The infra opportunity is software that continuously produces compliance evidence (test coverage, incident trails, red-team results) as a byproduct of normal operation. 4. Data flywheels for post-training (high-quality feedback at scale) Post-training quality is gated by data. Partnerships like Anthropic’s use of Surge AI’s RLHF platform illustrate the demand for scalable human feedback + QC systems. Startups that productize “feedback ops” (tools, QC, workforce routing, privacy) can be critical picks-and-shovels.

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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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