Karthik Rau

Per-seat pricing is a short position on the future. Seats were never the product. They were a proxy for work. Agents break the proxy. Ben Thompson nails it: "Owning and organizing a company by identity is progressively less valuable if the number of human identities starts to dwindle." You're optimizing a shrinking denominator. Old world: sell logins. New world: sell work completed. That's not a pricing tweak. That's a full rewire. The winners will sell throughput—and the instrumentation to prove it. https://lnkd.in/g3VpGCMZ

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The leading AI application platform Anyscale is partnering with Common Room to reimagine what data-driven go-to-market looks like (and love seeing the results—2x pipeline QoQ!). Innovators like Bill O'Connor and the Anyscale team are using signals, AI, and automation to map out their buyer universe, refresh leads based on what’s happening in real time, and take action fast. Better yet, they’re showing what it looks like when Ops, sales, and marketing work in lock step to drive pipe. Learn about their playbook here 👇 https://lnkd.in/gW6qjXqs

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As always, GitGuardian was first to catch the devastating CISA leak and alert them. I use them on my own repos to prevent leaks by me via Claude Code as well as to be notified (honeytokens) if I get pwned by a supply chain or prompt injection attack. It is _deeply_ unsafe to use full-auto coding agents without some protection against the lethal trifecta applied to local secrets. Note: consider micro-VMs / Sprites for defense in depth.

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Here’s how I built a Signal360 GTM engine to turn market noise into strategic motion. Signal360: Listening Before Launching In a previous GTM role at a technical infrastructure company, I walked into a familiar challenge. The product was strong. The category was growing. But the go-to-market motion was disconnected from what users actually cared about. Conversations centered on how to tell a better story, how to launch louder, how to scale faster. All fair questions. But they missed a critical step. Before building velocity, you need direction. Before crafting messaging, you need to understand where you already have pull. That is where the Signal360 framework comes in. What is Signal360 Signal360 is a framework I created to operationalize strategic listening. It captures directional market, user, and product signals and turns them into actionable GTM priorities. It layers five primary sources: • External sentiment across LinkedIn, GitHub, forums, and analyst chatter • What your ICP is searching for or discussing across channels • Patterns from sales conversations, onboarding drop-offs, and exit surveys • Product usage behavior and activation paths • Lifecycle engagement data to uncover drop-off points and message mismatches This is not about collecting noise. It is about synthesizing the clearest signals across the funnel and aligning your motion around them. What it changed in practice At that company, this approach shifted the GTM in a few meaningful ways: • We moved away from abstract positioning and reframed our product around concrete developer use cases like agentic orchestration and workload simplification. This made our messaging land more clearly with buyers already exploring that space. • We rebuilt onboarding around the actual product journeys users were taking, rather than the internal ideal state. Activation improved significantly. • We developed content campaigns and SEO initiatives tied directly to product exploration patterns, creating a bridge from early intent to meaningful usage. • Product marketing prioritized roadmap storytelling around friction we saw across activation and expansion conversations, not just what was next in the sprint cycle. Why it matters: GTM is often built on assumptions. Assumptions about what users value. About what buyers need to hear. About what story will resonate. Signal360 gave us a system to challenge those assumptions with real evidence. It helped us build GTM strategy with clarity and weight. It is not about making the loudest noise. It is about tuning into the frequency that already has attention and building from there. This is post 25 in my series on growth, GTM, and building meaningful systems during the in-between. If your GTM motion is stalling or misaligned, it may not be a product problem. It might be a signal problem. I would love to help fix that. #gtmstrategy #growthmarketing #productmarketing #plg #ai #signal360 #gtm

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Today, we launched House Mates, the ClickHouse partner community and program, live from Open House 2026. 🚀 60+ partners. Six continents. ISVs like dbt Labs, Fivetran, Grafana Labs, Confluent, Sigma, Hex, and many more. SI and channel partners like Tigerdata Llc, Ciklum, MegazoneCloud, ShellKode, Quest1 and more. ClickHouse crossed $250M ARR (3x+ YoY) and 4,000 customers. That kind of growth demands an ecosystem around it. Bespoke partnerships were never going to scale. We needed a programmatic foundation to build on, measure impact, and reward the partners who go deepest. House Mates is that foundation. For customers: build faster, build with confidence. For partners: a strong revenue engine to grow alongside ClickHouse. Validated integrations. Certified experts. Joint GTM. Real incentives. A clear path to grow together. A lot more to come. Read my blog to learn more: https://lnkd.in/ewuymC-g

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As a Stage 2 LP, I get to watch some exciting companies scale up close. One of our portfolio companies Letter AI, just announced their $40M Series B. Letter AI modernizes the First-Meeting-to-Closed-Won journey by creating custom buyer agents for pre-meeting practice, in-meeting agents for real-time coaching, and post-meeting automation of CRM updates, forecasts, and next-step actions. It's an intelligence layer that’s tuned to every call prep, embedded in every live interaction, and actively shaping next steps for each deal. Worth the read: https://lnkd.in/gXFbZd74

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Every PMM team needs to do this now! Get access to the source code repo. Here is why: 1. Ask questions in Claude or Cursor 2. Uncover how the product works 3. Answer technical and high level questions quick 4. Format outputs by audience 5. Even draw flow diagrams Now there is never a new question you can’t answer in minutes. No need to ask a PM. No need to wait.

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Want to hear more from the Spotlight team on the news regarding the sale by Gartner of Capterra, Software Advice, andGetApp to   G2 - this post by John Rockhold is a great summary - and tells you why user reviews continue to grow in importance for LLM’s and by extension, for Influence Orchestration! 

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This session we did two weeks ago was a Masterclass in bringing highly informed CISOs to discuss pressing topics in security and resilience. Well run by Gaven Smith CB and Chris Martin. Particularly interesting to me was the discussion on enforcement and incentives for securing organizations--it was a shame regulators weren't in the room taking notes!

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SaaS lock-in has historically been built on two main kinds of friction: the cost and risk of migrating data at scale, and the muscle memory that comes from teams building workflows around a specific interface. Agents weaken the second kind. When users interact with an agent rather than the underlying system directly, the interface becomes less sticky. This affects SaaS broadly: any tool whose value lived primarily in its interface is now vulnerable. For systems of record, the threat runs deeper. As agents increasingly do the work, fewer people log into the CRM directly. The system of record shifts from being an application to being infrastructure. You don't need to rip out Salesforce to make it worth a fraction of what it is today. You just need agents sitting above it, capturing the value of the work being done. So what replaces friction as the moat? We believe it’s context: the organizational decision histories and reasoning patterns that accumulate as an AI system learns how a specific company thinks and operates. That's what we've been calling a context graph, and it's different from existing systems of record. Incumbent systems of record were optimized for a human workforce. They record outcomes, not the reasoning behind them. For a human workforce that carried that context in their heads, that was fine. Agents need to understand not just what a company has done, but how it thinks. Retrofitting a context graph onto a legacy architecture is a fundamentally different engineering challenge than building one from scratch. Incumbents will have to do it while protecting existing revenue, supporting existing customers, and reporting earnings every quarter. Startups carry none of that weight. We laid out our context graphs' thesis in December. February’s “SaaSpocalypse” is the market catching up to the same realization: https://lnkd.in/gP25Qvzt

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🦞 Thanks to all who attended our OpenClaw Silicon Valley meetup last night. While the coffee was strong, the insights on Enterprise Security were stronger. 🦞 The biggest takeaway wasn't about prompt engineering or Python scripts. It was about the massive shift we're seeing right now: OpenClaw isn't just a tool anymore. It’s a Digital Co-worker. And just like human employees, these digital co-workers need "HR" (Governance) and "Controlled Access" (Security). The Reality of Shadow AI Employees are spinning up local agents to get more work done. It's the new "Shadow IT," but faster and more autonomous. ✅Companies that try to ban it will lose productivity. ✅Companies that ignore it will leak data. ✅The winners will be the ones who govern it. Look at projects like NanoClaw (https://lnkd.in/gQCsRnVs). The community is actively building more secure runtimes with better containerization and permission boundaries. The tools are maturing from "cool hacks" to "enterprise-grade infrastructure." My Prediction for 2026: The most in-demand role won't just be the "AI Engineer" who builds the bot. It will be the AI Governance Lead who defines the policy. 👍 Who authorizes the agent? 👍 What files can it touch? 👍 How do we audit its actions? If you work in Compliance, Security, or IT Governance, your skills aren't obsolete. They are the missing link to making Agentic AI viable in the enterprise. Thanks to everyone who contributed to the spirited conversation. We also have a WhatsApp community where we discuss all things OpenClaw. DM me for access.👇 #OpenClaw #ShadowAI #AIGovernance #EnterpriseSecurity #SiliconValley

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Love it or hate it, being in the SF Bay Area is still one of the biggest hacks for First Builders to discover huge opportunities before anyone else. But what can you do if you’re not here? Cecilia for example moved here in 2001 and instantly joined Yahoo after feeling the palpable energy around early internet. And it’s been nonstop ever since as she later joined Amazon, Cruise, Replit, and her own breakout company GC AI. She credits a lot to the emerging tech density and optimism in the Bay Area. But she also mentions additional ways people can identify these opportunities early on: - Follow intuition around big waves - Follow your envy - Never lose curiosity - Watch the teen hackers - Talk to peers early and often (builds long term networks/insights)

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𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝘆 𝗪𝗲𝗲𝗸𝗲𝗻𝗱 𝗙𝘂𝗻𝗱 𝗶𝗻𝘃𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗗𝗲𝗮𝗹𝗼𝗽𝘀 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗶𝘀 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗺𝗲𝘀𝘀𝘆. Flat-rate and seat-based models are giving way to usage-based, hybrid, and outcome-driven models...and companies are iterating weekly. And yet…most deals are still priced in spreadsheets, Slack threads, and CPQs built for a world where pricing changed once a year. That’s why we invested in DealOps. Their platform cuts quoting time from ~30 minutes to 2–3 minutes while increasing ACVs and margins. It can: - Map use cases to SKUs (critical as platform companies explode in SKU count) - Automate forecasting (needed with usage-based pricing) - Generate polished proposals in one click 𝗙𝗼𝘂𝗻𝗱𝗲𝗿 𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗽𝗼𝗶𝗻𝘁 Spyri priced thousands of deals at Stripe as part of the finance team, saw the limits of current tools firsthand, and has lived this problem end-to-end. 𝗦𝘁𝗿𝗼𝗻𝗴 𝗺𝗮𝗿𝗸𝗲𝘁 𝗽𝘂𝗹𝗹 They're off to a strong start. Teams like Plaid, Harvey, and Airwallex use DealOps to scale new pricing models, guide reps in real time, and drive pricing discipline without slowing deals. The results: 10× faster quoting, 30% lifts in average contract size, millions in incremental revenue. They’ve already processed over $1 billion in revenue, and are just getting started. 𝗧𝗵𝗲𝗶𝗿 𝘁𝗶𝗺𝗶𝗻𝗴 𝗶𝘀 𝗿𝗶𝗴𝗵𝘁 The entire AI supply chain, from GPUs to infrastructure, is variable COGS. Pricing agility is no longer a “nice to have”; it’s a must-have. We’re thrilled to back Spyri and the team alongside Pear VC, General Catalyst, and others as they build the pricing system of record for modern sales teams.

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I've had the pleasure of working with Eric in the past and continue to see B2B selling organizations struggle with this. Make no mistake, this is the ultimate leading indicator that explains a lot of the negative lagging ones. I'm sure that Eric would also have an opinion on the diversity of talent needed on a value engineering team. At the end of the day, this is all about leading change and you need people in your org with the experience and track record of actually having done it. https://lnkd.in/euNTNNx7

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Huge congrats to the Haast team on announcing their $12M Series A 🚀 I met Kunal 18 months ago at a conference of all places. I knew instantly that we had to back him. The insight was simple but incredibly powerful: in a world where AI is accelerating every part of the enterprise, compliance was becoming the bottleneck. That gap is only getting wider and Kunal Vankadara, Liam King and team are the right people to bridge it. What’s impressed us most is how the team has executed against that vision. They’re not just building another AI tool. They’re creating the infrastructure layer that allows companies to move fast and stay compliant. Embedding policy, judgment, and risk directly into workflows is a fundamentally different approach. The leading indicators of a special company speak for themselves - rapid growth, zero churn, and adoption by some of the world’s largest enterprises. They are strong signals of what we’ve believed from day one: compliance is becoming mission-critical infrastructure in the age of AI. defy.vc is proud to be early partners to the entire Haast team. The journey is just getting started. If you'd like to learn more reach out to Kunal below. 👊 💥 Peak XV Partners, DST Global, Airtree, Aura Ventures, Black Sheep Capital. Rohit Agarwal Jackie Vullinghs Daniel Gavel Eric Chan Yoseph Taslim Jessica H. Tan

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https://lnkd.in/geSxUcPk Interesting read..AI-native SaaS startups under $25M ARR are scaling with ~38% leaner GTM teams by leaning heavily on AI for onboarding, support, and RevOps—delivering growth without the usual headcount. But as these companies cross $50M ARR, the efficiency gains start to flatten, and in M&A scenarios, the traditional playbook of achieving operating leverage post-acquisition may not apply—AI-native orgs don’t scale in the same formulaic way as their non-AI peers, and integrating them into legacy structures can actually erode the very efficiency buyers are hoping to acquire.

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Using real world examples from Optimizely , Hinge Health, Aptean , Diligent , Copado , Brinqa , CentralReach and Fin, this shows how companies have pivoted AI product strategy and operations to embrace #AI transformation. Companies need to adapt or risk their future.

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The best AI apps today are being built like infrastructure companies. Great breakdown from the awesome 💡 Yazan "Yaz" El-Baba on why technical depth, rapid iteration, and margin-aware architectures are becoming table stakes for AI startups. Definitely worth a read: https://lnkd.in/gMVFFXgH 

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vSAN Tip of the Day: Dump the Dedicated Storage Array Still clinging to your SAN? It’s time to rethink the economics. By moving to a hyperconverged model like vSAN—or better yet, a fully integrated, ultraconverged architecture—you can eliminate the complexity and cost of: • Dedicated storage arrays • Proprietary controller hardware • Specialized storage networks • Separate support contracts • Costly refresh cycles The ROI is clear: Instead of paying a premium for all-flash arrays with SSDs marked as "SAN-optimized," you can use server-grade SSDs in standard servers and avoid the 10X markup added by AFA vendors. This method also reduces the number of components to manage and maintain, resulting in considerable cost savings. Organizations making the switch are saving tens of thousands of dollars, all while improving performance and simplifying operations. https://lnkd.in/gvehn6T7 If you’re facing a storage refresh or VMware exit, this is your opportunity to consolidate and cut costs at the same time.

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