Alfred Lin

#TheTenYearFixedTerm. It drives the entire startup ecosystem. Here’s how. Week 4 of “Venture Capital” at the Santa Clara University School of Law. LPs don’t want to be trapped in an illiquid venture capital fund forever, paying annual management fees. How can they get out? There is a secondary market for those interests, but it’s primarily opportunistic, and targets desperate sellers. So without a structural endpoint, they could be trapped forever. And there is: the 10 year fixed term. On that anniversary, subject to possible but limited extensions, the fund must terminate and wind-up, distributing its final assets to its investors. Seems benign, but the impact is massive! 1️⃣ Our #VC and #startup culture is defined by SPEED. Startup-to-growth-to-liquidity, as quickly as possible. Market dynamics are most certainly relevant, and prevalent. But there’s a structural driver as well: yes, the 10 year fixed term. If you are going to fully harvest your fund in 10 years, you need to front-load your investment activity (to ensure that your portfolio companies have at least some time to grow and ripen). So VCs race to deploy their capital within the first 5 years. But that’s not all - they then apply pressure on founders to drive toward exit. Which in virtually all cases, is M&A (sale of the company). The need for LP liquidity within 10 years drives the need for startup speed. 2️⃣ #AgencyCosts refer to the inevitable conflicts-of-interest that arise when one party (the agent) is tasked with acting on behalf of another party (the principal). In the #VC context, the ultimate principal is the #LimitedPartner, and their agent is the #VentureCapitalist. Limited partners want big returns, and liquidity. But what’s to stop the VC from diverting focus (and capital) toward an unending lifestyle instead? In other words, people have their own agendas and motivations. Always. So how does this principal, here, ensure that incentives are aligned and agency costs minimized? Yep. The 10 year fixed term. By dramatically limiting the space for self-dealing by creating a brief window of active existence, the VC is forced to focus on getting to liquidity. They simply do not have the opportunity to selfishly create an endless, self-perpetuating empire underwritten by the limited partners. Bracketed with their carried interest, the VCs are incented to focus on big returns in a concentrated period of time. Exactly what the LPs want! I was on the road this week, and so I recorded the lecture for the students. I normally can’t provide access to my lecture recordings, because they live behind university firewalls, but this week I bootlegged it and uploaded them to my YouTube channel. If you are interested, this lecture (broken into 3 segments) is available there for free - no agency costs in sight! #DWProf

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The Headline family is experiencing incredible momentum, and today our portfolio company DeepIP is announcing a $25M Series B, bringing total funding to $40M.  This is the kind of company that doesn’t just add AI to a workflow, but it sets the standard for an entire category. The momentum speaks for itself: 1️⃣ 10x ARR growth in < 18 months 2️⃣ Trusted by 400+ law firms and leading corporate IP teams globally 3️⃣ 2M+ chats on the DeepIP platform We’ve had the chance to back FX (Francois-Xavier) L. and Edouard D., leading their Seed round with Headline. Watching them take on a problem as complex and high-stakes as patent work has been genuinely impressive. And working with them has been an absolute pleasure: these 2 are coupling very high ambition and humility. Tech built in Europe, but opening the US office very early and FX starting a life in NYC with his family with 0 hesitation in order to build a global category leader in the IP industry. What convinced me early is still what stands out today: patent teams don’t need another standalone AI tool. They need something that fits the way the work actually happens: documents, long-running matters, multiple stakeholders, and zero room for sloppy context handoffs. Big congrats to the whole DeepIP team + Korelya Capital, Balderton & Serena Proud that we’re doubling down at Headline and continuing the support for what’s next!

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🦄 Unicorns… Or reversed engineered and stated slightly differently: Which VCs have the most to lose in the event of a prolonged blocked exit window? More than 1200 unicorns… 🦄 - many of which haven’t raised funds since 2021. Don’t get me wrong - achieving unicorn status is a recognition of a significant milestone… you garnered a high valuation based on your future prospects. But it doesn’t mean much if you don’t deliver! Unicorns are fragile - if you don’t build a sustainable, durable infrastructure and a differentiated, competitive product, you’ll either run out of money or be merged into another portfolio company … In an increasingly narrowing group of professional investment leaders, you need to build camels 🐪 able to trek through the inevitable sandstorm. #Unicorns #BusinessStrategy #VC #VentureCapital #CapitalMarkets #IPO #Exit #Startups

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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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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 AI-Native Operator Takeaway #2: In AI-native PLG, the hard part isn’t conversion... it’s discovery. Many AI-native teams are still talking about PLG using a classic SaaS mental model, but based on operator conversations in SF, that model is starting to break down in fairly obvious ways. The biggest bottleneck right now isn’t conversion. It’s discovery. In traditional PLG, users generally understood the category before they ever signed up. The problem was obvious, the product’s value was legible from the homepage, and the “aha” moment tended to show up quickly in first use. In that world, PLG meant optimizing onboarding, reducing friction, and improving free-to-paid conversion because user intent already existed. AI changes that assumption. In AI-native products, users are often curious but unclear. They don’t yet know what’s possible, value depends heavily on workflow, context, data, and role, and the product can feel abstract until it’s applied directly to their job. As a result, many users stall not because the product isn’t valuable, but because they haven’t discovered how it fits into their world and how they can't live without it. This is the real distinction people kept coming back to. PLG conversion answers, “Is this worth paying for?” PLG discovery answers, “What problem does this solve for me, right now?” What’s working best in practice is less about funnel polish and more about clarity up front: role- or workflow-specific entry points, guided examples instead of blank states, and opinionated first actions that show users a concrete outcome before asking them to explore. This also explains a broader pattern across AI-native companies. Forward-deployed teams and services-heavy delivery aren’t just implementation tools; they’re discovery mechanisms. They translate abstract AI capability into concrete workflow value, observe real use cases users wouldn’t self-discover, and feed those learnings back into what eventually becomes productized. PLG isn’t going away, but in AI-native companies it’s being redefined. Self-serve no longer means self-explanatory. Education becomes part of the product, and discovery has to come before optimization. The teams making progress aren’t obsessing over conversion rates yet. They’re focused on whether users see themselves in the product, how quickly they reach a meaningful outcome, and whether the product helps users get to a meaningful outcome for themselves quickly, without too much guesswork. Bottom line: in AI, PLG is less about removing conversion friction early and much more about creating understanding first. Once they understand, they may be hooked. Tomorrow is my last SF AI operator takeaway focusing on everyone's favorite topic du jour: 996 work schedules.

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Nearly 40% of VC dollars go to just 10% of deals. That means most founders are already fighting uphill. And one legal mistake can kill your raise before it starts. The best founders win because they’re prepared, structured, and fast.

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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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There has been an explosion of startups building all manner of AI tools in Silicon Valley. I thought yesterday's Fortune Term Sheet with Allie Garfinkle captured a sentiment I've been having perfectly. “I’m a little bit worried,” he [Databricks CEO Ali Ghodsi] said. “There’s definitely too much of everybody doing the same thing in general…It’s kind of like watching kids play soccer—all of them run towards the same ball. Then, there’s a big collision in the middle, somebody kicks the ball somewhere else—and then all of them run that way.” The contrast could not be more stark. We are mostly looking outside Silicon Valley, where it is a different dynamic altogether.

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Honored and excited to partner with Drew Baglino and the incredible team at Heron Power as they re-imagine the electric grid for the modern world. Power in America is not zero sum. We deserve access to cheap and abundant electricity and we should win the AI race. And we must build the capacity to manufacture critical technology here at home. When faced with existential challenges, we deploy technology against them. And we win.

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What's an incredible side effect of AI-native semi-autonomous orgs is not just being able to cut labor cost and supercharge your ROI as a startup. But small teams = faster decision-making = product / GTM velocity. This is the real game-changer with building companies "with" AI.

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AI is reshaping every industry — and VC is no exception. great catching up with Nathaniel Barling, operating partner at Andreessen Horowitz, who leads a 10-person engineering team building internal AI tools to supercharge their VC workflows. 🚀 at Creandum, we’re right there on the same journey. Over the past year, we’ve rolled out multiple AI-enabled apps (some built with Lovable ofc 😎) that now power everything from sourcing + dealflow analysis to portfolio management. the productivity impact is real — and we’re only just getting started. in VC (like everywhere else): adapt and embrace…or get run over. ⚡️

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this clip is of former OpenAI Chief Research Office Bob McGrew talking on Sequoia Capital's AI podcast about the AI tools he uses. Spoiler alert: howie.com is on the list!

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It's been a pleasure partnering with Jeff Cripe and Kameron Rezzadeh on this journey. A board-certified surgeon turned founder brings a different lens to RCM. While many talk about AI "roll-ups", fewer spend a year quietly building the AI, acquiring the right asset, and proving out op + health IT integrations, translating into a 3,000 bps expansion in EBITDA. Excited to see Procode AI come out of stealth with dozens of customers already live! 🤞 🚀 📈

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Expectations about Seed => Series A have increased dramatically, and you'd better be ready for it. It's been a topic of conversation with many of our Seed co-investors as well as upstream funds. In 2021 (and even prior), conversations would start about an A around $1M in revenue. In 2025, some firms we work with might consider $1M, but really prefer $3M and actually would rather see the company be closer to $5M. What does this mean if you're in market for a Seed? Raise enough capital to get to at least the $3M ARR mark OR to cash flow neutral. Additionally, ensure that you have good investors that will hang around when things invariably take twice as long and cost twice as much. What if you already raised a Seed and haven't gotten serious Series A interest? Start prepping your Seed+, Pre-Series A, Top-Up, or whatever you want to call it round. There are plenty of Seed investors that will gladly take a look at these rounds if the economics work. Many of these investors are faced with choosing "AI" companies with no product and no customers or companies in that "messy middle" of $1-2M in revenue. Most I know are investing more in the latter. Fundraising in 2025 is predictably unpredictable, so plan accordingly.

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𝗪𝗵𝗮𝘁 𝗶𝗳 𝘁𝗵𝗲 𝗼𝗻𝗹𝘆 𝘁𝗵𝗶𝗻𝗴 𝘀𝘁𝗼𝗽𝗽𝗶𝗻𝗴 𝗶𝗻𝘃𝗲𝘀𝘁𝗼𝗿𝘀 𝗳𝗿𝗼𝗺 𝗳𝘂𝗻𝗱𝗶𝗻𝗴 𝘆𝗼𝘂… 𝗶𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂 𝗵𝗮𝘃𝗲𝗻’𝘁 𝗲𝘃𝗲𝗻 𝗿𝗲𝗮𝗹𝗶𝘇𝗲𝗱 𝘆𝗲𝘁? Most founders think fundraising comes down to a great pitch deck, a sharp story, and a bit of luck. 𝗠𝗮𝗿𝗰 𝗔𝗻𝗱𝗿𝗲𝗲𝘀𝘀𝗲𝗻 says it’s much deeper, and most founders are flying blind. In one of his most insightful Stanford University talks, the Andreessen Horowitz co-founder breaks down how great founders actually raise capital, and the subtle moves that separate fundable startups from forgettable ones. Here are 𝟱 𝗿𝘂𝗹𝗲𝘀 𝗠𝗮𝗿𝗰 𝗯𝗲𝗹𝗶𝗲𝘃𝗲𝘀 𝗲𝘃𝗲𝗿𝘆 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝘀𝗵𝗼𝘂𝗹𝗱 𝗺𝗮𝘀𝘁𝗲𝗿: 1️⃣ 𝗣𝗶𝘁𝗰𝗵 𝘁𝗼 𝗷𝘂𝗻𝗶𝗼𝗿 𝗩𝗖𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝗽𝗶𝘁𝗰𝗵 𝘁𝗵𝗲 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀 Junior investors are your private “rehearsal stage.” They’ll tell you what’s missing, what’s confusing, and what senior partners will push back on, before it costs you the meeting. 2️⃣ Start raising long before you need the money If you’re low on runway, investors can smell it instantly. Fundraise from a position of strength, not survival. Momentum is your leverage, desperation destroys deals. 3️⃣ “𝗕𝗲 𝘀𝗼 𝗴𝗼𝗼𝗱 𝘁𝗵𝗲𝘆 𝗰𝗮𝗻’𝘁 𝗶𝗴𝗻𝗼𝗿𝗲 𝘆𝗼𝘂.” Marc echoes Steve Martin here: excellence is the ultimate pitch. Show mastery of your market, real traction, clear insights, and a roadmap that feels inevitable. Hype fades. Substance converts. 4️⃣ 𝗕𝘂𝗶𝗹𝗱 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽𝘀 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗩𝗖 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗲𝗮𝗿𝗹𝘆 Founders who raise fast aren’t lucky, they’re known. Talk to junior VCs, senior partners, other founders, community members. When it’s time to raise, you want them thinking: “Oh yeah, I know this founder.” 5️⃣ 𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝗳𝗼𝗿 𝗱𝘂𝗲 𝗱𝗶𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗺𝗼𝗻𝘁𝗵𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝗳𝘂𝗻𝗱𝗿𝗮𝗶𝘀𝗲 If you’re scrambling to pull financials, metrics, and docs together once investors show interest… you’re already signaling chaos. Great companies look prepared before anyone asks. Founders: don’t guess how fundraising works. Learn it from someone who’s shaped the industry. Watch Marc Andreessen’s full Stanford talk here 👇 https://lnkd.in/gd9NU2se

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Thanks Ryan Lawler for covering our raise. “Investors are clamoring for new ways to acquire pre-IPO shares as high-growth startups stay private longer… Augment focuses on high-demand, late-stage names like OpenAI, SpaceX, xAI, Databricks and Canva, but has roughly 300 private companies on its platform… ‘You can go from seeing an offering to owning the shares in five minutes,’ Moldvai says.” Read the full Axios article here: https://lnkd.in/gn-K8-h7

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