Mohak Sharma

I’ve spoken to over 2 dozen MDs at PE firms I can confidently say that the arb of figuring out how to implement Vertical AI at portfolio companies is very real right now It will fundamentally change underwriting for those who can do it predictably and unlock generational returns. Most are aware they need to act. Very few have.

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San Francisco-based DVC has launched DVC AI Fund I, a $75 million fund focused on Series A and B rounds. DVC is rewriting the venture playbook by replacing its analyst team with proprietary AI agents that handle deal sourcing and due diligence, analyzing 120 signals to build investment memos in minutes. The firm invests in core AI infrastructure, vertical model stacks, and application-layer solutions, leveraging a network of over 170 founders-turned-investors from companies like OpenAI, Google, and Tesla as LPs to mentor portfolio companies. The new fund is backed by notable LPs including Mike Arrington (Arrington Capital), Denis Yarats (Perplexity AI), and Andrew Filev (Wrike). The fund will be used to make early, low-friction investments in breakout AI startups, often providing capital months before a formal raise. Congratulations to founders Marina Davidova, Nick Davidov, and the DVC team. Tech Funding News: https://lnkd.in/dQKxCCrr Deals like this are reshaping the AI landscape. For weekly analysis on the funding, valuations, and strategic moves that matter, subscribe to the Charted Growth newsletter: chartedgrowth.beehiiv.com #AI #VentureCapital #VC #Funding #Startups #Investment #Tech #Innovation #SeriesA #SeriesB

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87% of YC companies are enterprise. Now it makes complete sense that AI is starting in enterprise. The models are expensive to run, and enterprise lets you automate workflows and vertically integrate. But to reach billions of people in their daily lives. The real prize is still consumer. A lot of founders are scared of consumer right now. At any point, OpenAI or Google can vertically integrate and kill your company. But you can make a similar argument for enterprise applications. The other part is that consumer is genuinely hard. Distribution is more mature, the App Store feels saturated, and there aren’t obvious new channels. At the same time, we are in the midst of a revolution. Interfacing with the world will be more than just a handful of chatbots. If you pay attention to daily life, to your parents, your kids, anyone close to you, you’ll notice how many small, annoying things still exist. Yes, the App Store is mature. But the top apps right now are AI apps. If something is truly great, innovative, or fun, people will go out of their way to find it. Menlo Ventures analyzed routine tasks of US adults. The Takeaway: Fewer than one in five people actually use AI for their day-to-day tasks. Most people stick with whatever system they already have, even if it’s annoying. At Hands, we're building with these 3 rules in mind: 1. Meet people where they already are 2. Make it easy to try. 3. Prove the product's value almost immediately

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Big milestone for Firmable. We’ve raised $14m Series A led by Airtree. Sales has moved through a few big waves: intuition-led, CRM-led, data-led. We’re now entering the next one – intelligence-led sales. The opportunity isn’t just better data. It’s turning that data into clear direction and action, without adding more work for sales teams. That’s what we’re building at Firmable: a foundation of trusted external data, layered with intelligence that helps sellers know who to focus on and when. Led by Airtree, this round supports our expansion across Asia and into the US – and accelerates the build-out of AI agents that take the admin work off sales teams so they can focus on what they do best. Proud of the team, grateful to our customers and investors. We’re just getting started. Read the exclusive in the AFR. https://lnkd.in/gr66uknb Leigh Jasper | Tara Salmon | Karthik Venkatasubramanian| Chester Thompson| Chath Widanapathirana

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Why was the Fivetran-dbt merger all but inevitable? Fivetran & dbt Labs announced their merger yesterday. The all-stock deal combines two companies into an entity approaching $600 million in ARR. The beauty of the modern data stack was the explosion in choice. As the cloud exploded onto the scene, the legacy data warehouse was replaced by a collection of fast-moving platforms. In that era, specialization won. The pendulum is now swinging back towards consolidation. Why? The answer lies in compute economics & revenue scale asymmetry. The table below shows why. There are three different categories of software within this subset of the ecosystem: 1. Ingestion takes data from software & moves it into a cloud data warehouse. Snowflake acquired Datavolo, which commercializes the open source product Apache NiFi, calling it Openflow. Databricks acquired Arcion for ingestion through change data capture, calling it LakeFlow Connect. Fivetran focuses exclusively on this layer. 2. Transformation means reformatting the data within the cloud data warehouse. Snowflake launched native dbt Projects on Snowflake. Databricks offers Delta Live Tables, native SQL, & Python, plus supports hosted dbt through Databricks Workflows. dbt Core/Cloud is the leading independent transformation tool. 3. Compute revenue is generated when we ask questions of our data. Snowflake remains one of the leaders in structured data analysis with their cloud data warehouse. Databricks’ compute is their own as well. Here’s the asymmetry in one number. Compute represents 72% of the overall market ($7.6B of $10.6B). As a result of their massive operations, Snowflake & Databricks exert significant gravity within the ecosystem. They have expanded beyond the compute market to impose their presence & capture marginal revenue within customers, pressuring the competitive ecosystem. That’s not to say these components are independent. George Fraser analyzed Snowflake workloads in September 2024, finding transformation represents 40-45% of total Snowflake compute, which means even at smaller scales, startups can have significant impact on these behemoth businesses. The Fivetran-dbt merger is an inevitable evolution of a maturing market. Two unicorns must partner to compete against two decacorns. They solve two of the three customer problems. But not yet compute. One could surmise this consolidation signals the end of the modern data stack. I view it differently. The MDS has succeeded beyond our expectations. The stakes are higher now. Broad platforms, fast growth, & AI-native architectures define the next phase. Expect more consolidation. Category revenue estimates based on public disclosures & company filings. Ingestion: Informatica ($1.64B FY2024), Fivetran ($300M est.), Talend ($350M), others ($200M est.). Transformation: dbt Labs ($300M est.), others ($200M est.). Compute: Snowflake ($3.6B FY2025), Databricks ($4.0B ARR Aug 2025).

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Supabase's Ant Wilson and Paul Copplestone raise $200m seven months after last raise. TC talks about the growth of vibe coding. https://lnkd.in/gaNYvyRC

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We rebuilt Alpaca VC with AI. From the ground up. In production. Not talking about it. Not planning it. Actually running our entire firm on infrastructure we built ourselves. Private MCP server. RAG deployed. Knowledge base living in Supabase. Custom agents covering more surface area than our team ever could alone. Ryan Freedman internally talks about it as "riding on the back of the wave" - implementing tools as they ship, breaking things, rebuilding better. We're former builders. We know how to move fast without waiting for permission. Most VCs use AI to write memos faster. We use it to find founders others miss. Our agents don't just summarize pitch decks - they identify patterns across thousands of data points, surface non-obvious connections, track founder momentum in real-time. They're doing the work that used to take analysts weeks in minutes. But more importantly, they're freeing us to do what only humans can: build trust, make judgment calls, spot that spark in a founder's eye during a tough conversation. The real goal? Not just efficiency... Alpha generation through better sourcing, winning, and supporting. And in our humble opinion, this isn't about being cutting-edge. It's about accepting that the firms still doing venture the old way are already obsolete. They just don't know it yet. Alex Konrad did a deep dive into who is doing this best, and identified the folks alongside us at Union Square Ventures (Rebecca Kaden), Thrive Capital, Topology Ventures (Casey Caruso), DVC (Nick Davidov) + more. Which other VC firms are building with AI? 🙋‍♀️ https://lnkd.in/gDRBvaBz

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The search fund model is built on alignment. But "usually" isn’t "always." While search funds are collaborative by design, collaboration doesn’t eliminate tension. Based on experiences from both sides of the table, our latest note explores the moments when incentives between ETA CEOs and investors naturally drift apart. Why this matters: It’s Structural: These aren't "bad actor" stories; they are inherent constraints of the model. It’s Predictable: Tensions surface when timelines, personal realities, or stakes shift. It’s Navigable: Understanding these frictions upfront builds empathy, clearer expectations, and better discussions. Grateful to collaborate with Alex Hodgkin, CFA, and A.J. Wasserstein on a topic that rewards honesty and dialogue over optimism alone. Read the full paper at: https://lnkd.in/e_eskQ9V #ETA, #SearchFunds, #Searchfund, #EntrepreneurshipThroughAcquisition, #Entrepreneurship, #CorporateGovernance, #InvestorRelations, #PrivateEquity, #YaleSoM, #Kellogg, #Booth

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The big labs are expansive in their product ambition, especially since foundation models have largely improved in lockstep - in order to compete with them you have to do things they won’t which are: - building a very rich software ecosystem around a primitive - orchestration across multiple models - going insanely deep on product and growth for a narrow vertical domain

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Fundraising for Emerging Managers The fundraising environment is tough for new VC firms, but Moxxie Ventures just raised $95M for their third fund, exceeding targets. This shows potential shifts in investor confidence and highlights the importance of strong networks. Katie Jacobs Stanton, Moxxie’s founder, leveraged her extensive connections and track record to attract leading LPs despite the broader landscape. Her investments in pre-seed and seed startups, particularly those led by underrepresented founders, position Moxxie uniquely in the market. This success underlines a few key implications: 1. Investor Selection: Founders might prioritize VCs with aligned values and proven support systems in today's climate. 2. Diversity in Funding: Moxxie's commitment to BIPOC and female founders reflects a strategic focus that can resonate with socially conscious investors. 3. Focus on Emerging Tech: Investment in health tech, SaaS, and AI indicates a shift towards sectors forecasted for growth, potentially influencing other firms' strategies. Overall, Moxxie's success amidst challenges may inspire emerging managers and reshape the investment landscape. Let’s discuss how these dynamics could affect our industry. #venturecapital #emergingmanagers #fundraising #diversityintech #startups https://lnkd.in/d5NHg8s3

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While there has never been a more exciting time to be a founder building dev tooling or next-gen infra, it has also never been less investable at seed/pre-seed. I'm either really missing something or a lot of my peers are lost. As someone who has not just written, but also SHIPPED, about 75k lines of code in the past 6 months I can tell you that the evolution of how to build products has changed as much in the past year as it did in the entirety of 2007-2017. The complete rise and fail of frameworks, platforms, methodologies, etc... paved over and forgotten... that is of course except for the 1 company that gets a 1000x return from a wildly overvalued hyper-scaler or drunken growth stage investor obsessed with compounding at scale. Imagine a world where any seed investor in trends like Openstack, Hadoop, PaaS, etc all took a full loss on their investment. That's what we're looking at right now. I personally know of over a dozen well-funded seed-stage companies building in these spaces, with years of runway, scrambling to get acquired for a return of capital + several million personally while they're still relevant. If you're not seeing this unfold in front of you, you either aren't paying attention or you're satisfied playing the lottery instead of investing.

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🚨NEW EPISODE: Recorded live at FUTURE TITANS 2026 - Jeff Perry of Carta sat down with the iconic Seth Levine, co-founder of Foundry. Seth has been in venture for 25 years, built Foundry from scratch as an emerging manager himself, and has backed about 50 emerging manager funds through his fund of funds. He has genuinely seen every side of this table. They went deep on building Foundry, why VCs are in the influence business, not the decision business, and why the concentration problem in venture is not only bad for LPs, but also for the innovation ecosystem overall. And why Seth's new book, Capital Evolution, is so important for the future of America. 🎧 Links to listen... Apple: https://lnkd.in/ehQUQ2EM Spotify: https://lnkd.in/eU4FExpg

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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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Two weeks ago on Swimming with Allocators, we sat down with David Clark, CIO at VenCap, to talk about what decades of venture data can teach allocators. One takeaway that stood out: discounts don’t matter as much as people think in venture secondaries. Because venture is such a power-law asset class, outcomes are driven by exposure to a few massive winners. Whether a stake is bought at a small discount, or even a premium, often matters far less than the quality of the underlying company and its upside. Great conversation on venture returns, manager selection, and the nuances of how allocators should think about secondary investments. 👇 Link in the comments.

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Amazing opportunity! Selected teams will receive $250K in catalytic funding, six months of technical support from OpenAI engineers and experts, API credits, access to a leading AI network, and the opportunity for additional capital to scale their projects. Chike Aguh, Nitzan Pelman, Tina J. Walha, Ariana Soto, Jennifer Anastasoff, Angie Cooper, Kelly Fitzsimmons, Sara Holoubek, Cassandra Madison, Alex Swartsel, Lynn Overmann,

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It's great that NY wants to remove the QSBS tax exclusion! Clearly, we need to raise the taxes on risk takers because we don't need more startups and VCs in NY. 💡 We've solved every important problem out there! (-- other than the problem of our inflated government budget.) What's also cool about the current proposal is that it's retroactive to 2025 so even if someone got demotivated and decided to uproot their family and work and move to a different state, it still wouldn't be enough and they would also need to delay any liquidity event and do all sorts of financial engineering to optimize their tax liability. But hey, at least we'll get a free grocery store in NY and maybe some free bus tickets... Great work Kathy Hochul, Andrea Stewart-Cousins,Carl Heastie, Zohran Mamdani... 👏 Disclaimer: this is my personal view and doesn't represent Constrafor or its shareholders. #QSBS #startups #NYQSBS #NYtax #tax

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Reading Holden Spaht commentary about LPs curiosity regarding AI and it highlights some very interesting points. I completely agree with the sentiment expressed here. When advising private equity portfolio companies executives I've always been mindful of letting them know the tension between emerging tech and legacy systems, and the opportunity to leverage #AI within the SaaS ecosystem is absolutely something to watch. The future isn't about #disruption for disruption's sake, it's about thoughtfully evolving and amplifying value, particularly in the areas of productivity and innovation. There’s a clear, compelling case for why #SaaS companies with deep #data rights, first-party data, and network effects are uniquely positioned to thrive in the age of AI, as Holden eludes to. What’s often missed however, in the headlines most exercise and the general public see, is that SaaS, with its system of record capabilities, is enabling the #AIrevolution, not being replaced by it. The data, scale, and domain expertise embedded in these businesses make them the perfect platform for integrating AI in a way that adds exponential value, both in terms of efficiency and #innovation. I agree that we’re in the early stages of the AI-SaaS convergence, and it's not about an all-or-nothing proposition. Rather, we’re in the midst of a journey: from experimentation (Wave 1) to ROI-driven applications (Wave 2), culminating in seamless, enterprise-grade AI that doesn't disrupt core business operations (Wave 3). The key is not just having AI, but having the right AI that integrates within existing and improving #frameworks and amplifies what’s already working and reimagines what may not be or may not be working at its best. The proof is in the numbers. SaaS continues to show impressive growth, and the biggest players are already laying the groundwork for the #AI-enabled future. But it’s also clear that the path forward requires more than just bold promises from early-stage AI startups. It’s about trust, #scalability, and building with a long-term vision. I remain bullish on the symbiotic relationship between SaaS and AI. AI will enhance the SaaS value proposition, not erode it. #AIandSaaS #EnterpriseAI #SaaSInnovation #DigitalTransformation #TechGrowth #AIenabled #StrategicGrowth

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Fullstack startups are the latest craze: Marc Andreessen talked about this phenomenon on Jack Altman's latest podcast Today Browserbase launched Director.ai for consumers to automate the web This follows Vercel launching @v0 for consumers to build sites and apps Both of these companies are infrastructure (picks and shovels) providers that have now moved "up the stack" to launch consumer applications on top of their infra This is the latest in vogue playbook following: Compound startups (multi-product - i.e. Rippling) Layer cake vertical startups (SaaS+Payments+Lending - i.e. ServiceTitan) Links in comments: Jack altman Marc podcast Director.ai launch video Paul Klein IV, Guillermo Rauch, CRV

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