Jeremy Levine

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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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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SF VC Takeaway #2: Pricing expectations, performance bars, and what’s actually getting funded. One theme that came up repeatedly in SF was how far pricing expectations and performance bars have shifted, even compared to just a few years ago. A few things investors kept anchoring to: 1️⃣ Median Series A valuations are higher than their 2021 peaks, but fewer of them are getting done. 2️⃣ Capital is being concentrated into fewer and fewer companies (and lots of capital!) 3️⃣ “Good” progress is no longer enough and the bar for standout performance has moved in an AI-native world So what does “top performance” mean right now? One investor told me that top quartile seed companies in their portfolio are going from $0 to $2M in ARR in <12 months. Outside of pure traction numbers, a few other themes that came up to describe "top performance": 📈 Explosive early revenue ramps (or a very credible path to them) 📊 Strong velocity and momentum for 2 quarters in a row, even if the baseline is small. 🚀 Clear signals of category leadership, not just product-market fit. Sometimes shown by either domain expertise, speed of product optimization, or by lack of competition in the category. This creates a counterintuitive dynamic where it can be easier to fund a company with strong pedigrees in a hot space and no traction yet than a company that went from 0 to $1M ARR at what used to be considered a rapid pace. Pricing today is driven by trajectories, not moments in time. We used to say investors invest in lines not points; I think that's more true than ever now because crossing certain milestones doesn't carry as much influence as it once did. Finally, investors still say that valuation matters, but many of them are acting differently. Pace and belief in category-defining companies really sets the price; while slower growth gets scrutinized rather than discounted. One silver lining in the camp of durable growth: Series A rounds are happening so fast that many companies don’t yet have meaningful history of retention data. Large bets are being made on velocity before the durability is proven. Several investors told me the same thing: we may soon swing back to a market where retention, not growth, becomes the defining metric. Let's hope so. I'll share my third SF VC takeaway tomorrow!

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VC schedules, and thoughts on being a VC noob. -- VC schedules to know -- Most venture capital firms hold partner meetings on Mondays. This is typically when the investment committee votes on new investments and other key decisions. Savvy founders learn the exact timing and may need to provide additional data over the weekend to stay in motion. It is also well known that many venture capitalists observe a “European summer,” with August often being light or fully off. Similarly, the winter holidays reduce activity across much of December. That said, data from Carta shows a meaningful year-end push to close deals in December, followed by a flurry of activity in January. Founders should be cautious about kicking off fundraising during these slower periods. You do not want a raise to go stale and fall apart. VCs talk to each other, the industry is highly interconnected. -- I’m a mid career Noob! -- I am an “emerging manager,” effectively a new VC, less than three years in. In venture capital, the timeline is long. On my Linkedin you'll see I have two roles at Blitzscaling: Limited Partner means I put money into a fund, but have no decision making ability, and General Partner means I'm actively finding startups, bringing them to the partnership, and funding. As a General Partner, you are often considered an emerging manager for close to a decade, as it takes years for a fund to fully mature and establish a VC track record. Investing is a long game, but the upside can be extraordinary. Fortunately, I entered this role with a positive angel track record from my own bank account, which is often a good idea to have as a VC. When I learn a new VC concept or term, I’m an AI first, I’ll link to my post a few days ago in the comments, I totally live for constant growth and learning, if you’re not growing you’re dying. Fun fact: Many/most start their VC career in their 40s, as they need to have enough tech and biz cycles, a broad enough network, resources, and a platform to stand upon. As we end the year, I'm sharing more career thoughts, and productivity thoughts, rather than industry trends and market maps and frameworks and forecasts. I wrote all of this by hand myself, but used AI to edit some of it.

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Here's a problem we see all the time in early studios: they copy-paste a VC fund's operating cadence and wonder why nothing feels right. Weekly deal flow reviews. Portfolio monitoring calls. Valuation-focused LP reports. All borrowed wholesale from a fund playbook. But a VC fund's primary activity is deal selection -- source, evaluate, check, board, wait. A studio's primary activity is venture creation -- generate, validate, recruit, build, launch. Those are fundamentally different jobs. When you run a studio like a fund, things break in specific ways: Your meetings are wrong. You're reviewing deal flow instead of venture build progress -- milestones, blockers, resource allocation. The work is building, not sourcing. Your team is wrong. Studios need builders at every level -- operators, designers, engineers. Not just investment professionals. You can't build companies with a team designed to pick them. 📉 Your metrics are wrong. Entry valuations and markups don't tell you anything useful. Cost-to-build-a-venture, time-to-market, and venture survival at 18 months -- those are the numbers that actually measure whether the studio is working. Your LP reporting is wrong. Report operational progress -- what's building, what's launching, what's been killed and why. Not just portfolio movements. Here's the lesson -- the studios that struggle most are the ones that adopted VC templates without modifying them for fundamentally different work. The portfolio companies don't exist until the studio creates them. Not a fund that happens to build things. A builder that happens to have a fund. The operating rhythm should reflect which one is primary. 🎯

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I had a great time chatting with Patrick O'Shaughnessy on Invest Like The Best. I've known Patrick since college, and this is the first time we've talked markets and investing at this much depth. The fundamentals of company building haven’t changed: people, products, and markets matter. But obviously, private markets have evolved substantially over my career: there are now ~6x more private unicorns than public companies with a $1b+ market cap. And at the end of 2010, just 2 public technology companies were among the top 10 in market cap; today it’s 8 of 10. AI (alongside software eating everything more generally) is clearly driving a lot of this. But it’s instructive to look at everything from the steam engine, to the early days of Facebook and Google user monetization, to real-time success stories like Databricks, Anduril, OpenAI and Waymo, to get a clear picture of where the opportunities lie. It was a pleasure to go deep on all this and more!

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🚀 Big milestone for Attio: today announcing a $52M Series B led by GV (Google Ventures), with Michael McBride joining the Board. This follows incredible momentum in customers, revenue, and team growth. But what excites us most remains the same as the very first day I met Nicolas Sharp four years ago, and the reason we have continued to back Attio from Seed through to Series A to now: game-changing product philosophy, world-class technological leadership and delivery, and resulting customer delight. From day one, Nicolas Sharp and Alexander Christie set out to build a new kind of CRM: ✨ Lightning fast and a delight to use ✨ Built on a flexible, modern data model ✨ All designed to give users full control to build a CRM that works for their GTM motion and seamlessly plug into the rest of their stack That foundation has proven to be exactly the right one. A new generation of GTM builders is emerging with Attio as their central pillar - including companies like Lovable, Granola, Modal and more. And the data model is perfect for building native AI functionality and allowing agents to work with the CRM - some of this is live, some is coming soon 👀  Nick and Alex have assembled a stellar team and have impressively scaled the organisation. Congratulations to them all on this funding milestone. Thank you for having us along for the ride over the past few years, and here’s to an epic next chapter ahead.  More from Nick here: https://lnkd.in/easA6jYV

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𝗩𝗘𝗡𝗧𝗨𝗥𝗘 𝗖𝗔𝗥𝗘𝗘𝗥𝗦 𝗗𝗘𝗠𝗬𝗦𝗧𝗜𝗙𝗜𝗘𝗗 𝟱: 𝗧𝗛𝗘 𝗦𝗘𝗖𝗢𝗡𝗗 𝗖𝗔𝗥𝗘𝗘𝗥 𝗩𝗖 Continuing my series on routes into VC Investment Teams (see previous posts in the comments), it’s time for a final group: Second Career VCs (SCVCs). 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮 𝗦𝗲𝗰𝗼𝗻𝗱 𝗖𝗮𝗿𝗲𝗲𝗿 𝗩𝗖? SCVCs are people who have had a substantial career in another field before turning to Venture. This doesn't include a product manager with five years experience or even a founder of a company that made it to Series B (great backgrounds, but more relevant to my previous post on Operator VCs). Instead, SCVCs typically spent 15-20+ years in another field, even reaching retirement stage, before starting afresh in VC. I’ve seen a variety of SCVCs – some are founders (myself included), others financiers (such as my previous partners Mark Evans and Tim Bunting) and others have had careers in medicine, law or even sports (e.g. Serena Williams’ primary focus is now Serena Ventures). Historically, this was almost the *only* way into venture. Key founders of Kleiner Perkins and Sequoia, for example, were successful, effectively retired operators before they got into venture, first investing their own capital and then adding other people’s money – much like successful Angel-turned-VCs do today. 𝗣𝗿𝗼𝘀 & 𝗖𝗼𝗻𝘀 𝗼𝗳 𝗕𝗲𝗶𝗻𝗴 𝗮 𝗦𝗖𝗩𝗖 ✅Credibility: A successful first career brings instant credibility with founders.  ✅Financial: Some firms require partners to buy into the firm/funds. A previously successful career likely provides the capital to do this. ❌Starting Again: You go directly from respected expert to total noob! It’s a humbling transition. ❌Structure: Many folks in this boat could just choose to invest directly themselves. Being a VC brings more capital and support, but it also brings more structure and bureaucracy. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗳𝗼𝗿 𝗦𝗲𝗰𝗼𝗻𝗱 𝗖𝗮𝗿𝗲𝗲𝗿 𝗩𝗖𝘀 1️⃣ Unless their previous career was in finance, there will be gaps in a SCVC’s toolkit. SCVCs are unlikely to go back to business school so they need to find a firm where others can balance out their skills. 2️⃣ As with Operator VCs, working in an investment firm is different to most careers and a transition in mentality and work-style is required - more on this in my previous post. 𝗧𝗵𝗼𝘂𝗴𝗵𝘁𝘀 𝗼𝗻 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗩𝗖 𝘃𝗶𝗮 𝘁𝗵𝗶𝘀 𝗿𝗼𝘂𝘁𝗲 1️⃣ The world is competitive and it is rare to be sufficiently successful (in a relevant enough field) to be able to get into VC this way. 2️⃣ And, of the few who can do it, many have other attractive options in life: retirement, a portfolio career, becoming an elder statesperson in their existing career, philanthropy, etc. 3️⃣ Once upon a time, VC could be pursued as an ‘active retirement’, alongside long vacations and other pursuits. Today the market is simply too professional, competitive and demanding for this – you’re either in or not, making it a less attractive path for those with the privilege of this option. 

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Yesterday's seed market was built on three constraints: Products were hard to build. Traction took time. VCs were hesitant to underwrite day zero risk. Those constraints created a unique market. Today, all three are dissolving.

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Every hire, product feature, and GTM experiment is a capital allocation decision, most teams just don’t call it that. I’m kicking off a 3-part series on capital allocation for founders, operators, and finance leaders with a simple question: ➡️ Will the next $1 you deploy become worth more than $1? Series overview Part 1: defines the core concept + the math Part 2: where capital goes + how to measure whether it’s working Part 3: AIMS framework for communicating allocation decisions to management teams and your board Part 1 (attached here) lays the practical foundation: 🔹 The $1 invested test and ROIIC vs. hurdle rates (scoreboard vs. decision lens) 🔹 A lightweight “investment brief” to evaluate bets (GROW / BUILD / BUY) 🔹 The small metric toolkit that translates finance into operating decisions (NPV / payback / ROIIC / incremental margin) 🔹 Early-stage proxies when DCF inputs are unknowable (burn multiple + revenue quality) 🔹 Operator “vital signs” to spot drift early (profit engine, leverage, cash conversion, optics) Series Roadmap ✔️ This series (Parts 1–3): breadth-first. shared, lightweight framework to define value creation, choose decision-grade metrics, and communicate tradeoffs clearly ✔️ Next series: depth-first. momentum drivers + operational decisions that need near real-time measurement to spot drift early and course-correct fast Read Part 1 here and Part 2 and 3 on substack. Next Series will be out next week. 💰 What’s one bet you’re funding right now, and how will you prove it’s working?

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