Divanny Lamas

As I'm leaving AWS re:Invent in Vegas, I’m reminded of a counterintuitive truth: competing with the public clouds is often really good business VCs love to ask, “Why wouldn’t the incumbent do this?” But in markets this large (and evolving this quickly) that’s rarely the right question. The real questions are: Who can assemble the best team, get to market fastest and with the most focus? And where are there opportunities to partner with the biggest players rather than compete? We’ve seen this pattern repeat across the ecosystem: -People assumed Vercel and AWS were destined to compete. Today, they’re strategic partners with CEO Guillermo Rauch in the keynote -Snowflake vs. Amazon Redshift. Now, AWS is one of Snowflake’s strongest distribution channels -In Datadog’s early pitches, the concern was, “If it’s just monitoring AWS, why not use CloudWatch?” Fast forward to now, and Datadog is now $50B+ public company We’re going to see the same dynamics play out with OpenAI and Anthropic. These are becoming foundational platforms. But that doesn’t preclude incredible companies from being built on, next to, and even around them. Some will look competitive. Many will end up as partners. And the biggest outcomes often start in those gray zones

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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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A few weeks back, I watched Maggie Hott, GTM leader at OpenAI, confidently navigate her first board meeting at Unify. Having worked with her through Emergence Capital's Operator in Residence (OIR) program, seeing her immediately contribute valuable insights made me think about how most board members receive virtually no training for this critical role. At Emergence, we've built our firm around developing board excellence. We grow all our partners from within and have established a culture of mentorship focused on board service. Junior investors aren't thrown into the deep end—we pair them with senior GPs to observe effective board dynamics firsthand. My initial experience was at DroneDeploy alongside my partner Kevin Spain, where I got great mentorship before taking on independent board responsibilities. We extend this methodology to our OIR program, where operators learn how to be effective board members. Based on my experience mentoring directors, here are the fundamental principles I share with first-timers for how board members can best support founders: 1. Reframe the purpose: Problem-solving, not reporting If your board meeting is primarily reporting, you're wasting your management team's time. Information sharing should happen asynchronously, with board members engaging with materials before the meeting. This enables the live session to leverage collective intelligence on critical challenges. This rarely happens because many directors overextend themselves across too many boards—another reason we maintain a disciplined investment pace. 2. Master the Socratic approach The most valuable contribution often comes through thoughtful questions rather than declarative statements. Your objective is to enhance the decision-making capability of management. I enter each meeting with 1-3 specific areas where I know I can add value, focusing questions on these topics. 3. Follow-through separates professionals from amateurs Diligently document your commitments, establish clear action items, and execute them. It's crazy how just doing this proactively makes a board member stand out. 4. Understand your unique contribution to the board ecosystem A high-functioning board resembles a great basketball team—you need complementary skills, not redundant ones. In every meeting, I stay conscious of my distinct value relative to others in the room, whether that's SaaS expertise, AI knowledge, or a particular relationship dynamic with the CEO. I calibrate my role based on needs—sometimes assertively addressing areas where others have less experience, other times asking probing questions where fellow members have deeper expertise. -- To my knowledge, Emergence is the only VC firm with a formalized program dedicated to board excellence. It's an investment that yields returns where they matter most—in bending the odds of success for our founders. Founders, I'm curious: What board member behaviors have you found most valuable?

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🚀 Excited to share that today Vantage is launching a native integration with Vercel! This gives customers the ability to see their Vercel usage and costs in Vantage alongside all other providers they use to run their infrastructure. All the same great Vantage features now work for Vercel costs: cost allocation, anomaly detection, budgeting and more. I've known Guillermo Rauch for over a decade at this point and have followed the Vercel story closely - it's been amazing to see all the work the company has done over the years. Vercel has also won the hearts and minds of millions of developers. Vercel has done things TheRight™ way by shipping a FinOps Foundation FOCUS-compatible endpoint to allow their customers to easily export cost and usage data. If you're a Vercel customer, this integration is now included in the Vantage integration library by default. Login to the Vantage console to integrate Vercel or read the full blog post with all the details in the link below.

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The old SaaS pricing playbook doesn’t work for AI. Madhavan Ramanujam and I partnered with Emergence Capital and Jake Saper to write a new one—built for where AI is going, not just where it is today. We lay out what state-of-the-art AI pricing looks like now—and what it will look like: ✅ Hybrid pricing (seats + usage) is the current best practice 🎯 Outcome-based models are the future—pricing tied directly to impact 💰 The best AI companies already capture 25–50% of the value they create As autonomy and attribution improve, outcome pricing will go from rare to expected. Founders who move early will win. Full read here 👉 https://lnkd.in/gwp6tDtp

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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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Excited to share a new blog post I co-wrote with Patrick McClanahan on the evolving landscape of #VerticalSaaS! As Vertical SaaS companies navigate limited market sizes, sustainable growth comes down to two key levers: expanding the customer base and deepening monetization. From embedded payments to AI-powered workflow automation, industry leaders like Shopify, Toast, and Clio - Cloud-Based Legal Technology are using AI to enhance user experiences and unlock new revenue streams. The future of Vertical SaaS is intelligent, adaptive, and built on deep domain expertise—and AI is accelerating that shift. A few of our takeaways: 📈Vertical SaaS Growth: SAM/SOM growth comes from serving new customers and deepening monetization 🤝Proven Strategies: In the past, leading companies grew their addressable market with strategies like integrated payments and ecosystem integrations 💡AI Opportunity: AI enables Vertical SaaS to reach previously unreachable workflows and solve new pain points, growing SAM and share of wallet 🏆Moving Beyond Service Providers: In the future, the most successful Vertical SaaS companies will leverage intelligence and automation to move from service providers to AI-enabled advisors and co-pilots Check out the full post and let us know what you think!  https://lnkd.in/g3vipcKq #VerticalSaaS #AI #GrowthStrategies #SaaS Fika Ventures

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Yesterday Clay hit $100M ARR and I shared a post on the GTM bets that got us here. Today, I'm sitting down with our Head of Finance to dive deep on the business - metrics, our view on the AI market, and the path to $1B. Karan often gets this question from candidates: "Look, I have to dedicate my livelihood to Clay. All the upside of my equity is baked into one asset. How should I frame the real risk/reward?" It's a great question! So I wanted to use this video to go beyond the tactics and share how we think about the business holistically. The fundamentals, market dynamics and where we're really going. Some of what we cover: - The AI market and why GTM is actually the least crowded - Cohort data that shocked even us (enterprises never churn!) - How we've built an entire economy around Clay - The three things that create our customer flywheel - Why we're not burning cash while growing at an insane rate - The vectors to $1B: new geos, personas, use cases, channels, and verticals At the end, we get candid about the real risks and why World of Warcraft helps explain them. Watch here 👇

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I often see marketing leaders respond with insufficient urgency to creative performance degradation. I view any meaningful drop in creative performance as an all-hands-on-deck emergency that needs to be addressed aggressively. A few years ago, in one of the most popular posts on Mobile Dev Memo, I proposed the idea of a "creative performance half-life": the point after which creative performance degrades precipitously because of saturation. That half-life is essentially a replacement timeline. If the creative production process requires two weeks from concept to deliverable into testing, then any significant decline in creative performance means that the creative production process either malfunctioned or became misaligned with market conditions *two weeks ago*. That's a catastrophe. The team should respond accordingly by dramatically increasing production output. This is why I advocate for working with a large number of agencies and freelancers, since their output can be flexibly scaled at a moment's notice. But the broader point is that a considerable drop in creative performance reveals a process problem in the past that will have accumulated over the half-life of the advertiser's creatives. Fixing it now requires a deliberate expansion of creative output and diversity.

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My thanks to Marty Kagan, co-founder and CEO of Hydrolix, for joining me [🎙️ https://rayburn.link/marty] for a detailed conversation on 𝘁𝗵𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝗰𝗲 𝗼𝗳 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗶𝗻𝗴 𝗯𝗲𝘁𝘁𝗲𝗿 𝗲𝗻𝗱-𝘂𝘀𝗲𝗿 𝗤𝗼𝗘 𝘄𝗶𝘁𝗵 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝘁𝗲𝗹𝗲𝗺𝗲𝘁𝗿𝘆 and the challenges that come with CDN observability. Marty highlights why more hot data is crucial for AIOps and challenges that M&E customers face today, including the need to discard data due to storage costs. Marty presents a compelling argument against the notion that most data is irrelevant and that content owners only need to retain a small percentage as a sample. We also discuss why Hydrolix isn’t an AI company and Marty's plans to continue growing its streaming data lake platform in verticals outside of video. Listen here: 🎙️ https://rayburn.link/marty #streamingmedia #infrastructure #hydrolix #contentdelivery

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AI is changing the structure of most companies we see. Lots more coming from us on how startups can build faster, leaner teams -- and where we see all of this going. Great piece from Pete Flint to kick it off: https://lnkd.in/dcUebcJj

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