Anand Arivukkarasu

On the latest episode of Embracing Erosion I sat down with Suyog Deshpande, Co-Founder & CEO of Webless (a Fluvio Ventures portfolio company). Before starting Webless, Suyog spent years at Amplitude, Salesforce, and Samsara - shaping products and GTM strategy at scale as a product marketing leader. That perspective is now fueling one of the boldest bets in tech: 🏗️ rebuilding the web for LLMs. Instead of optimizing for clicks and SEO, Webless imagines an agentic web -where sites are designed to interact directly with AI models and agents. We dug into: - What an LLM-native web could actually look like - How companies can prepare to be LLM-ready - What metrics will matter beyond pageviews and clicks - Why safety and trust are core to agent-driven experiences - Lessons Suyog brings from “big tech” into this transformation If you’re curious about how discovery, trust, and value exchange will evolve online, this one’s worth your time. Link to the full episode in the comments 👇

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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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Today marks a milestone for Salesforce Ventures, and a defining moment for enterprise security. Alphabet’s acquisition of Wiz has officially closed. Wiz has been a cornerstone of our portfolio since May 2021, when Nowi Kallen, Kartik Gupta, and team first invested in their Series B at a $1.5B valuation. We saw the potential early and invested deeply, backing the team through their Series C, D, and E rounds. From a $1.5B Series B to a $32B acquisition, one of the largest in enterprise tech history, the Wiz team’s execution has been nothing short of extraordinary. This outcome reflects our mission at Salesforce Ventures: identifying the companies that define the next era of technology and staying behind them for the long haul. But the real credit belongs to the entire Wiz team on the ground. Beyond the technology, it was the relentless grit and day one mentality of Assaf Rappaport and the team that turned a vision into a $32B reality. Huge congratulations to the entire Wiz team on this historic achievement.

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We at SIERRA Ventures are thrilled to lead the $8M Seed round in smallest.ai! We feel honored to partner with Sudarshan Kamath and Akshat Mandloi as they build an important company in the Voice AI space. We’ve now entered a new era. Voice AI agents are no longer research projects or demos - they’re deployed in production. Whether it’s buying or selling a house, scheduling a doctor’s appointment, or returning a purchase, there’s a growing chance you’ve already interacted with an AI voice agent without realizing it. Why Smallest AI: 💡 Team: Sudarshan and Akshat are customer-obsessed technical founders who understand what enterprises truly need.. agents that are fast, secure, and production-ready. 💡 Industry leading performance: The company has some of the fastest, highest-quality voice AI models in the world (Lightning Text to Speech) that outperform Elevenlabs, Cartesia across all parameters. Their SLM Electron outperforms GPT 4.1 Mini in both quality and latency for real-time conversational use cases. 💡 Integrated Voice stack:  Delivering a natural voice interaction requires a complex workflow under the hood integrating components like ASR, models, TTS. By optimizing every step in the loop, from low-latency TTS to contextually coherent responses, they are helping to deliver real-time, human-like conversational AI that sets a new benchmark for performance. 💡 Small models, big impact: Nvidia recently published a research paper - "Small models are the future of agentic AI". Smallest AI builds the high-accuracy models that customers can run at the edge consuming little power. 💡 Happy customers: customers consistently told us how much they enjoyed working with the team. For anyone building enterprise voice AI agents, please reach out and we'll be happy to connect you with the team! #voiceAI #ai #tts #asr #slm

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The hottest role in AI startups right now isn’t Forward Deployed Engineers. It isn't GTM Engineers. It’s Deployment Strategists. Decagon calls it an “Agent Product Manager.” Harvey calls it a “Solutions Architect.” Palantir Technologies has had versions of this role for years. And the salaries are climbing fast: - Decagon: $200k–$285k - Palantir Technologies: $120k–$200k - Figma: $150k–$260k - Ramp: $100k–$180k - Harvey: $190k–$260k So who are these people? They are usually pseudo-technical -- CS or engineering majors, or folks with technical work experience. Many come from 2 years in consulting, IB, or PE, then jump into startups to get their hands dirty. They are young, hungry, polished, and comfortable being in front of customers. What do they actually do? They make sure enterprise AI deployments succeed. A $100k+ deal does not survive on a nice pitch or a self-serve onboarding flow. It survives if the customer sees value in the pilot. That means: - Embedding directly with the customer - Designing prompt logic for specific workflows - Working with engineering to align integrations and data flow - Helping exec teams define their AI roadmap - Running feedback loops into product and GTM Why does this role matter so much? Because enterprise AI is messy. Integrations, data transfer, and adoption make or break a deal. Most buyers are using AI for the first time, and each has unique workflows. Deployment Strategists bridge that gap. They own the outcome. They are accountable for making pilots successful, which often means millions in revenue down the line. At Conversion, Sam Bochner has been leading this work for us. We are now thinking about scaling it into a full team. Because a few successful pilots can fund an entire department, and the cost of failed deployments is too high to ignore. Is this just a rebrand of customer success? Not really. Success is about answering tickets and renewals. Deployment Strategy is about going deep with a few enterprise accounts, extracting maximum value, and ensuring the pilot closes into a multi-year contract. Call it Agent PM, Solutions Architect, or Deployment Strategist. Whatever the title, this is becoming one of the most important roles in AI SaaS.

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