Osama Bedier

It's been a pleasure partnering with Jeff Cripe and Kameron Rezzadeh on this journey. A board-certified surgeon turned founder brings a different lens to RCM. While many talk about AI "roll-ups", fewer spend a year quietly building the AI, acquiring the right asset, and proving out op + health IT integrations, translating into a 3,000 bps expansion in EBITDA. Excited to see Procode AI come out of stealth with dozens of customers already live! 🤞 🚀 📈

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One of the best in #venture with a strong take on hype vs reality. Give it watch. Chasing problems will win the majority of the time. The how becomes where the art lives. If you are a seed, pre-seed or just getting started founder building in anything #fintech, JC Bahr-de Stefano and Better Tomorrow Ventures should be your first call.

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Jobs and AI are no longer abstract debates. When the government publicly entertains the prospect of constraints on AI-driven workforce replacement, it’s a sign the conversation has moved from theory to policy and boardrooms. Last year, at the advice of the tech team at Venrock, I spent my time learning new industries from the ground up. The goal was simple: reduce bias before forming conviction. Through conversations, research, and deep dives, patterns began to emerge. This is the first of a few lessons that emerged from that process. Insights that meaningfully shifted how I think. First, about the future of work. I’ve written up some of my thoughts in the link below. Strong opinions, weakly held. And a thank you to Bharat Chandar and Ruyu Chen, two awesome economists at the Stanford Digital Economy Lab, for spending time with me as they continue their research into AI and labor impacts. (Fun fact: their research was highlighted in the The Economist Podcast!) If you’re building in any of the spaces I write about, disagree with a take, or see something here that resonates, I’d genuinely love to hear from you. https://lnkd.in/gg9wjDFn

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Three lessons from a second-time founder Husayn Kassai built and led Onfido for 10 years. These are the three lessons he's applying to ollo. 1. Product-market fit is about solving burning problems, not building perfect products. If you're working on something customers desperately need, they'll be patient while you figure out execution. Your first product doesn't need polish, it needs to solve a problem urgent enough that customers tolerate rough edges while you improve. Be scientific about validating this. 2. Hiring determines everything Your ability to bring in people who complement each other and fit your mission is the biggest determinant of success. 3. Trust your gut, especially when you think you've outgrown it. You have three signals as a founder: your head (rational), your heart (emotional), and your gut (instinct). Tech founders have a habit of preferring rationality and ignoring the other two. How your team feels matters. How customers feel about your product matters. And your gut matters most five or ten years in when you’re hiring experienced execs from big companies and think you can finally stop paying attention. Trust the pattern recognition you've built.

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We've been using Macroscope for the last six months and consider it an essential part of our engineering stack. It gives engineers practical feedback they can use, while giving product leaders a far better understanding of what is actually going on.

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The best founders don’t just build products; they reframe the problem. Ryan Alshak has done exactly that with Laurel - turning time from a background task into a source of insight, alignment, and leverage. IVP is leading Laurel's Series C to help build the system of record for how work actually happens. Read more from Allie Garfinkle: https://lnkd.in/gweNiwsc

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A few weeks ago, we brought the Origin Ventures community of LPs and 80+ portfolio company executives together in Park City for our Annual Meeting and CXO Summits. In our annual meeting, we covered the Origin Ventures VI investment themes: ⚡🖥️🔒AI Infrastructure (e.g. compute, power, quantum, language models, security) 📦💿🔗AI-Native Software (e.g. logistics, supply chain, sales, operations, consumer) 🤖🛰️🚀AI Frontier Tech (e.g. robotics & autonomy, defense, electrification, space, materials & manufacturing) We featured Origin Ventures VI CEOs from: Torus fresh off its $200M financing led by Magnetar Voze integrating AI into its sales enablement roadmap for field sales AudioShake scaling 5x YoY with enterprise partners across AI and media & entertainment The next day, portfolio company leaders exchanged ideas in three forums in three iconic locations:  - CEO summit  - Builders Summit (engineering and product) - GTM Summit (sales and marketing) The highlight is an unforgettable dinner at Blue Sky Ranch—an evening of conversation, connection, and community with our LPs and execs together. We are grateful to our LPs and our execs who make it a great week of learning. 👨‍🏫  

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Founders: every rule (about fundraising and everything else) is artificial and meant to be broken. For example, consider the “rule” that the lead investor should invest at least X% of the entire round. It’s BS. For example, the amazing Kirsten Green led Bonobos’ $30m Series C round with $1m (and helped the founder raise the remaining $29m). Ignore the so-called rules. Do the right thing for your company. Be the exception.

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Big news from the Vermilion Cliffs Ventures portfolio today. Keycard acquired Anchor.dev 🎉 🎉 🎉 🎉 As the talent wars in AI heat up, we’re seeing more early-stage teams join forces in thoughtful, founder-first ways. Not just traditional acquisitions, but combinations of people, product, and vision. When funds stay close to their founders, these outcomes can be incredibly powerful. This acquisition brings two Vermilion portfolio companies together to accelerate autonomous coding agents in production. Anchor brings deep infrastructure experience from places like Cloudflare, GitHub, and Heroku, with a focus on making identity primitives automatic, reliable, and invisible to developers. That expertise now lives directly inside Keycard’s agent-native platform. Together, they’re enabling: Application-layer policy enforcement at runtime: Policy is evaluated per task and per tool call, where agents actually execute actions, rather than at login, the network boundary, or through protocol-specific proxies. Protocol-agnostic support for the full agent toolchain: Agent behavior is governed consistently across MCP workflows, CLI commands, APIs, and agent-generated tools, enabling the long tail of applications and patterns used in modern software development. Explicit tool governance with full visibility: Teams define which tools an agent is allowed to use, and every tool invocation, successful or failed, is evaluated, logged, and attributed to a specific agent and task with support for additional metadata. Identity-bound, task-scoped credentials: Static secrets are replaced with short-lived credentials issued per task and cryptographically bound to the agent and the application being accessed. Portable agent configuration across environments: Agents are configured once and can be used across laptops, sandboxes, and production systems without reconfiguration, using cryptographically attested runtime context. Autonomous workflows with built-in guardrails: Routine actions proceed without human involvement, while sensitive operations can still require explicit approval, enabling autonomy without sacrificing security or control. From my perspective as an investor in both companies, this combination makes perfect sense. Agents are becoming first-class actors in modern software systems, and autonomy without identity, governance, and visibility is a non-starter. Keycard is building the foundation that lets agents move safely from local development into production. Huge congrats to Ian Livingstone, Matthew Creager, Jared Hanson, and the Keycard team, and to Wesley Beary, Ben Burkert and the Anchor crew. Proud of both teams and excited to see what they build together. And thank you to Kyt Dotson at SiliconANGLE & theCUBE for the great coverage! https://lnkd.in/gH-i8vRu Onward. 👯‍♀️

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Our WillowTree Ventures dinner brought together an incredible group of fintech and AI operators. What struck me most was the consistency across perspectives: AI is finally unlocking tangible value in workflows, personalization is becoming real, and some of the biggest opportunities sit in the corners most people overlook. Founders building for financial services and enterprise AI deserve more conversations like these. Grateful to everyone who made time, and if you’re tackling one of these “non-sexy but massive” markets, let’s talk. Here are some key takeaways - AI is still about efficiency. The most serious near-term initiatives focus on automation, workflow augmentation, and operational leverage across teams. - Tech orgs continue to control the AI agenda. Budgets and decision-making largely sit with product and engineering, who are driving both exploration and implementation. - Personalization at scale is becoming real. There was broad agreement that AI can finally enable true 1:1 experiences in products and services, not just improved segmentation. - The most interesting opportunities are in “boring” corners. Non-traditional and overlooked segments are wide open for AI. “Non-sexy is sexy” may define the next wave of category creators. - Crypto is still early in the enterprise. Despite broader excitement, real day-to-day adoption remains nascent and uneven.

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Yesterday we gave an in-person NYC workshop on automating your financial document ingestion pipelines with AI. If you're an investment bank, accounting team, finance AI startup, fintech company, and you're processing a massive amount of consumer/regulatory/public financial paperwork at scale - you might find these resources useful! Logan Markewich built a full set of tutorials showing how you can stitch together VLM-enabled document parsing with schemas and business logic into an e2e workflow. This is both much more accurate than existing OCR solutions in extracting out data with much less human review, and can be easily stitched together with your downstream agent applications. Check it out: https://lnkd.in/gTH5Wsz7 If you're interested in VLM-powered doc processing, come check out LlamaParse: https://lnkd.in/g9Wpqn7w

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Friday Fun - As a VC I was investing for Angels, Family Offices, UHNW, (you name it), and one thing everyone has in common is a genuine urge for comprehension. They want to understand the action. So I decided to put something I've done in meetings for years locally on my machine (and give it to you too). Good Founders are the deepest expert in any room they walk into. They've lived inside the problem long enough that the causality and implied vector of motion is just obvious to them. A happens, then B and C kind of collapse, and D emerges or B1 becomes viable — and they've watched that cycle enough times that it feels self-evident. But when they say it out loud to a room of people with different reference points... the explanation needs to become materially more like Tetris. Just like languages with nuance and context, the problem becomes translation. Landing metaphors and analogies so context is gained even while learning the fundamental concepts. The mental models Founders have are genuinely irreducible. You can't compress years of domain experience (or literally created knowledge) into a brief pitch. Before I'd bring a founder to our LPs, I'd spend time explaining who'd actually be in that room — what they'd built, what sector their intuition lived in, who was going to ask sharp questions and who was going to call me or find me in the hall afterward with their questions. And then I'd work with the founder on how to get their logic to land for that audience, not a generic one. Not reducing it or simplifying it — but taking the version of the idea that already exists in someone else's mental model and drawing a line between the two — just a bridge built from their side. Anyway — I made a little HTML thing a few days ago that basically does that prep work. Single file, lives in your browser (although I did make it a skill file too if you prefer). You (add your api key) put in a concept you're pitching (the hard part, not the whole pitch), tell it something about who's in the room, and it helps you find the analogy that'll actually land for them. It's not polished, but it's the kind of thing I spent hours doing with founders when they met with our LPs. It's a small thing that isn't small at all. Suddenly the context is served on a platter, and they get the base for free — they can stack their own ideas from there. They're present. Here you go. https://lnkd.in/gdjXVhWF

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Excited to share that CapitalG is leading Duna's Series A. Duna has an audacious vision to build the internet’s missing "business graph." Onboarding is a massive hidden tax on the B2B economy. Most new business relationships start with a painful manual exchange of documents. This friction costs billions in labor and lost revenue - 30% of new partners churn mid-onboarding. The status quo rhymes with the consumer economy before Visa. Data was trapped in “one-to-one” silos, forcing merchants to perform the same underwriting work on the same customers over and over again. The shift to a portable network created 10x value for payers and merchants by eliminating that wasteful redundancy. 30 years into the internet, business identity is still trapped in a “single player” paradigm. Billions are spent collecting redundant information in silos. Duna’s end-to-end approach (intake, policy engine, and analyst workflow) is already delivering massive value to customers, with 35%+ conversion rate increases and 90%+ reductions in time to onboard. Duco and David are the perfect duo to build this business. They met as fellow stars at Stripe - Duco leading Benelux/DACH and David leading the core card platform product - and saw first hand as business onboarding emerged as one of the company’s key technical rate limiters. Read more on Kelly's, Miriam's, and my thesis here: https://lnkd.in/guF8sgKg

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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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I'll post more about this later, but for startups looking for an ai boost to get your team aligned and moving, check out Travis Kahn's Growth Blueprint: https://lnkd.in/e4bcd_dG. Founders and teams pair with an agent to get real foundational work done - Business Model Canvas, Customer Profiles, Messaging Frameworks, and Go-to-Market in a centralized environment that shows how everyone's effort connects (and hopefully amplifies). This is very similar to the strategy work that I did in previous lives at BrandNewMatter and Algoworks, and it really shows me how fast ai is moving. The important thing to understand is that frameworks and platforms like this and r4 Technologies are powerful because the technology works with the PEOPLE you have in the loop. True force multipliers only occur when tech, data, and staff are aligned and empowered.

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Usually good consumer UX removes friction. Alinea Invest made a bold choice to *add* friction -- and its spot on. Alinea launched Crypto investing as part of their wealth platform for beginner investors last week. Before users can invest in Crypto, they receive an AI-powered lesson and *must* complete a quiz, proving their new knowledge. Only 30% of Crypto investors are women. Not fully understanding crypto is a huge reason why women don't invest. Very excited for more investors to have access to this knowledge and feel empowered to try a new asset class. Congrats to Eve Halimi Anam Lakhani & team! Read More in Forbes by Nicole Casperson: https://lnkd.in/ggx545Hz

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🎙️ From Square to Mercury: How Rohini Pandhi became one of fintech’s top product leaders—and how velocity of learning at high slope companies shaped everything. Rohini dropped so many gems in our first episode of First Builders: 💎 Generalist → Specialist: In her early career, she was a generalist and tried everything. This led her to critical discoveries. She specialized in product and fintech when the “time was right” 💎 Follow the Engineers and Designers: Square was a high slope environment for Rohini, packed with talent density and learnings. She finds high slope environments by studying where smart engineers and designers are going. 💎 Fake News about PMs: PMs don’t just “move fast and break things.” Her team runs 30-50 customer interviews per quarter, providing rigor behind every decision. 💎 It’s Usually Too Early to Hire a PM: A top question she gets from founders is whether they should hire a PM. She usually says: “it’s too early.” 💎 Hiring a World Class Team is Like Tennis: When finding a tennis partner, you want someone a little better than you who can challenge you to improve your game. Give us a listen and leave a review on your favorite podcast location (see comments for links)! #FirstBuilders #StartupPodcast #ProductLeadership #TechCareers #Leadership

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