Jason Calacanis

I’m sharing a cap table guide + modeling framework founders should internalize early Here’s the second lens this guide is built around: 1️⃣ Your cap table behaves like a living model 2️⃣ Every SAFE today reshapes leverage tomorrow 3️⃣ Long-term dilution drives outcomes more than current ownership 4️⃣ Option pools expand as momentum builds 5️⃣ Structure quality directly affects deal speed 6️⃣ Equity grants ripple through every future round 7️⃣ Clear math builds trust faster than storytelling 8️⃣ Ownership outcomes are intentionally designed This guide and model help founders stay ahead of dilution instead of reacting to it later: https://lnkd.in/e5NKErS5 enjoy!

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The first check is always the hardest one to land! Early-stage fundraising isn’t really about metrics, it’s about risk management. Here’s why that first “yes” is so elusive: 1️⃣ It’s a pure team bet - investors are backing YOU, not your data. 2️⃣ There’s a data vacuum - no LTV/CAC or churn to justify valuation. 3️⃣ It’s an access hurdle - networks and warm intros matter more than most founders realize. I’ll be diving into this topic at TiE Silicon Valley’s Early-Stage Fundraising Webinar this week with Preetha Ram and Phillip D. of Venrock to share what really moves investors to write those first checks. 👉 Register at https://luma.com/egh4g50e #FundraisingTips #PreSeed #VCFunding #StartupLife #AngelInvesting #EarlyStageFunding #VentureCapital #StartupGrowth

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Harpoon Ventures + Black Flag is teaming up with Microsoft for Startups to provide founders with access to up to $250,000 in Azure credits, empowering builders to scale faster, train models more efficiently, and access world-class AI infrastructure. What’s included: ⚡ Up to $250K in Azure credits (usable across Azure OpenAI, Grok 3, Llama 4, and more) 💻 On-demand GPU VMs for model training and fine-tuning 🧠 Access to GitHub Enterprise + Microsoft 365 Business Premium 🤝 Dedicated Microsoft technical + GTM support This partnership is designed to give deep-tech and dual-use founders the tools and resources they need to win. Because when they win, we all win. 🏴‍☠️

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𝐓𝐡𝐞 𝐏𝐞𝐫𝐟𝐞𝐜𝐭 𝐏𝐢𝐭𝐜𝐡 𝐃𝐞𝐜𝐤 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐞 This deck shows the exact story flow VCs expect—based on hundreds of funded pitch decks. It’s not about design. It’s about sequencing. Key Takeaways: 1️⃣ Hook first – Capture attention fast with a clear problem and why now. 2️⃣ Prove it early – Traction, usage, and momentum beat feature lists. 3️⃣ Reduce risk logically – Team, advantage, economics, and competition should build confidence step by step. Bottom line? Winning decks don’t impress—they create conviction. PS. check out 🔔 for a winning pitch deck the template created by Silicon Valley legend, Peter Thiel https://lnkd.in/eQFrsUnE

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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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Do you dare to disagree with YC? I just watched Y Combinator 's recent video (see link below) claiming AI will transform service businesses into software companies. For ad agencies and mass litigation or due diligence? I agree 100%. Production costs will plummet. But when they use the example of a law firm "using AI to write legal docs in minutes rather than weeks"... they miss the mark entirely. They seem to have no idea what actual legal work entails in negotiations. [The "Text Generation" Myth] Anyone working in legal advisory knows that a contract doesn't take weeks to be "prepared." A first draft, based on pre-existing templates, takes minutes or a few hours to get ready. This represents, at most, 2% to 5% of a legal team's total invested hours. [Where the real value (and time) lies] The real bottleneck isn't generating text; it's managing people and risks: 🗣️ 80% to 90%: The Negotiation Trenches. This is where the real work happens: (a) explaining to the client's team what is being proposed and what makes sense to accept; (b) managing the back-and-forth with the other party—which almost always means overcoming the ignorance, foolishness, and vanities of both sides of the table; (c) reaching a final deal that actually stands up and makes sense for everyone. 🔍 5% to 10%: The Fine-Tuning. The final adjustments to the documents. Let's be honest: anyone who actually prompts knows that, right now, prompting for the perfect fine-tuning takes way more work than just doing it directly yourself. 🧠 The Human Factor (The Irreplaceable). What actually requires the qualitative, high-value hours of a partner is strategically contextualizing the demand and drafting the action plan. That strategic guidance is worth infinitely more than the raw hours spent on it. YC might know everything about scaling software, but high-level legal work isn't about typing clauses faster. It's about aligning expectations, mitigating risks, and navigating the human ego and educating clients in what they still haven’t experienced. And they haven't invented an LLM for that yet. What do you guys think? To what extent can AI negotiate the human vanity on the other side of the table? 👇 #Law #LegalTech #ArtificialIntelligence #YCombinator #Innovation #M&A #LegalAdvisory https://lnkd.in/g2TJ32_k

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You can turn $100,000 into a $50 million business through acquisitions. This is closer to capital allocation than traditional entrepreneurship. Here's the deal structure. First, the capital stack. You buy a business the same way you buy a house. Equity in, bank covers the rest. With SBA loans: 90% loan, 10% equity. A million dollar business might require $100K to $200K down. Target companies with $1 to $3 million in earnings. Go to sellers that are NOT at market. Brokered deals are competitive and sellers want cash at close. This only works off-market. Here's what you propose: Seller keeps 20% equity in a new entity. Asset sale, their company moves into newco, they keep running it at fair market salary. You write them a check for 60% via bank loan. Remaining 20% is a seller's note: 10% straight note, 10% performance earnout. From the bank's perspective, you created 40% equity. The truth? It's really only 20%, and it's the seller's. Your money in? Approaching zero. But you own 80% of Enterprise Value. Why would a seller agree? Tell them: my goal is to make your 20% as valuable as the 80% we're giving you today. What are the odds you double the value on your own in 3 to 5 years? Now stack earnings. $2 million average per company. Buy 10 just like this. $20 million combined earnings under one entity. Centralize marketing, accounting, HR, governance at HQ. You bought each at 4 to 4.5x. A $20 million earnings business sells for 7 to 7.5x or more. That's multiple expansion, just by combining them. Close the first one. Negotiate the next $100K for the next business. Then newco sells to PE for 7, 8, 9x your $20 million in earnings. That's the path from $100K to $50 million. If you're considering buying a business in the next 12 to 24 months, we built Acquisition Lab for exactly this. walkerdeibel.com

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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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I spent years learning to think in portfolios. Diversify. Spread bets. Manage risk through volume. That's how bankers manage uncertainty, and it's how most VCs deploy capital. It's also the wrong mental model for a venture studio. Studios don't make bets. They make companies. The difference sounds semantic, but it changes everything — how you allocate time, how you staff, where you spend money, and what "success" means in year one. A VC fund with 30 portfolio companies can afford 25 zeros. The math works because the winners are so large they cover the losses. That's portfolio theory. It's elegant. It's also completely inapplicable to a studio that's building three ventures with the same 8 people. When you run a studio like a fund, you start optimizing for deal flow instead of venture quality. You spread your operators thin across too many bets. You start measuring portfolio size instead of venture depth. And you end up with 12 half-built companies instead of 3 that actually work. The studios that break through do the opposite. They concentrate. They go deep on fewer ventures with more support. They treat each company like it's the one that matters — because at studio scale, it is. Diversification doesn't do your work for you. Rigor does.

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