I have spoken to 3 founders in the last 48 hours; all of them with 500-1,000 employees. Each of them is planning a minimum 20% headcount reduction. Said with great concern; this is about to get very real for labour markets.

This is for everyone who has a dream that simply seems out of reach. 11 years ago I started 20VC as an 18 year old in a bedroom in London. I didn’t know a single VC and had no money. I wrote down the names of three legends of the venture world. I have had two on the show previously and today I complete the list that 18 year old boy made. This was 11 years, 3,000 shows, 3,750 hours, in the making. Never give up, never doubt yourself, stay focused, row your own race. It will come through. Welcoming Marc Andreesen to 20VC today. (Links in comments)

I have invested $200M into the UK in the last five years. If @RachelReevesMP implements “Exit Tax” all that funding will go overnight. That is countless jobs, companies and people who will lose out. Rachel, you have managed to steal our hopes, our dreams even our growth, don’t take our freedom also. @Dom_Hallas 🙏 for his work here 👇 t.co/Z7pfrcdWjC

Every single dev and product team I speak to in the last 30 days has moved from Cursor to Claude Code. 1. Is this permanent? 2. If so, what happens to Cursor?

Everyday I am in the gym at the same time as an old man on the treadmill. Today I stopped him after the workout and introduced myself. Turns out he started his business in 1982. He has scaled it over the last 43 years, slowly but steadily every year. Today the business does $4.5BN in revenue. He owns 100% of it. Never raised a dollar. At 75, he remains CEO. That’s a magical story of entrepreneurship.

Adam Foroughi is by far one of the best CEOs I have ever interviewed. Candidly he is insanely stern and cold but also obsessive, focused and utterly brilliant. With Adam there is zero fluff, like none. He says what he means and means what he says. Applovin does $10M EBITDA per head. They have 80%+ margins. They do $5.48BN in revenue. No business on the planet has numbers like Applovin. Following the discussion, I wrote up my biggest lessons from sitting down with him and summarised them below: 1. Are People Ready for the AI Future That Is Within Every Company? True AI integration requires a massive "leveling up" of talent. Companies must be honest about the path forward: keeping employees who fail to adopt AI creates a "blockade" to reaching a truly AI-native state. Consequently, we should expect continued tech layoffs as organizations prioritize efficiency over legacy headcount. 2. Biggest Advice on Token Budgeting and Token Maxing? Treating tokens as a simple budget or leaderboard is "flawed logic". If you incentivize raw usage, teams will simply create high-volume "crap" that burns capital without driving revenue. Instead, optimize for specific KPIs where token consumption aligns directly with business growth; when revenue is on the other side, the "budget" mindset disappears. 3. Can You Have a Team Full of Only A Players? An organization cannot thrive if A players are surrounded by B, C, or D players. AppLovin slimmed its HR department from 80 people to 15 by retaining only "doers" who don't get bogged down in the process. The goal is a lean culture of individual contributors who want to make a difference without needing heavy management layers. 4. Do the Majority of Company Teams Need to Be Rebuilt for the Technology We Have Today? If a role is likely to be automated, or if a department is too slow to adopt AI, it is time to rebuild that organization from the ground up. Foroughi cut staff by 40-50% in most departments during a year of triple-digit growth to force the organization into an automated, efficient state. 5. Why Investors Need to Give Ceos Better Comp Packages Founders take massive risks to build something out of nothing, and they need continued upside to stay mentally motivated. If a CEO is expected to work without performance-based incentives, they may drift toward new ventures rather than staying committed to the "lonely, stressful" task of scaling a public company. 6. Why This $160 Billion Company Does Not Have Any Learning and Development Structured L&D is often disconnected from the reality of high-performance work. The best employees are curious enough to figure things out on their own. By documenting all communication in transcripts and chats, new hires can use AI models to summarize tribal knowledge and develop themselves more effectively than any formal training program. (links below)

Venture investors are going through an existential crisis. If you are not in the OpenAI, Anthropic, Cursor, Mercor etc etc you do not fricking matter.

I have never met a top-performing CEO who likes the role of HR. They are here to slow us down and instill meaningless process.

Getting a job in venture capital is incredibly simple. 1. Choose three VC partners that you like and would want to work for. 2. Study the type and stage of company they like. 3. Send them one company every other day that fits their stage and thesis. Provide one line on why it is interesting. 4. Do this for 60 days and 100% guarantee you will have a job offer. Show the freemium version of yourself.

Most podcasts are BS because they are fluffy and lack substance. This is the densest, most insightful episode you will listen to this year. @gokulr breaks down the 8 defensible moats you need for your company to be successful in a world of AI. 1. Data (Proprietary and inaccessible) 2. Workflow (Deeply embedded operations) 3. Regulatory (Licenses and contracts) 4. Distribution (Exclusive proprietary channels) 5. Ecosystem (Third-party platform reliance) 6. Network (Marketplace liquidity density) 7. Physical (Infrastructure and atoms) 8. Scale (Low cost through volume) (Links below)

I have interviewed 1,000s of the world's best founders over the past decade. Few have impressed me like @ShivdevRao at @AbridgeHQ. He navigated a brutal 5-year wilderness before exploding into one of the most dominant forces in vertical AI. Today, Abridge is a $5.3BN powerhouse. I sat down with Shiv to unpack exactly how he did it and condensed my notes below: 🚀 6 Lessons on Building a $5.3B Vertical AI Juggernaut 1. Survive Long Enough for Market Timing to Catch Up: Abridge spent 5 years in the "wilderness" before hitting a tidal wave of adoption. When you have an absolute true north thesis, your primary job in the early days is simple: stay standing and don’t die. You must be alive when the sky finally opens up. 2. Pivot the Product, Never the Core Thesis: Shiv was willing to pivot on features, go-to-market strategies, and business models. But he refused to budge on his core thesis that healthcare is ultimately powered by the spoken human signal. Die on the hill of your thesis; adapt everything else. 3. Target the Concentration of Scale Early: A massive trap for healthcare and enterprise founders is staying down-market too long for "fast feedback loops". In the US, the vast majority of clinicians are concentrated within large, integrated delivery networks. Time your "YOLO shot" to go up-market the moment the market inflects. Single biggest advice to founders on when to go up market @bhalligan @dharmesh? 4. Own Your Stack to Protect Your P&L and UX: While many AI startups rely entirely on frontier systems, 40% of Abridge's model outputs are generated by in-house models. Milliseconds matter in high-stakes enterprise workflows. Building your own models gives you insane performance gains, lower latency, and ultimate control over your P&L. When should you vs should you not build your own model @matanSF @MaxJunestrand @antonosika? 5. Don't Fight Foundation Models—Counter-Position Instead If you try to fight the frontier model giants directly, you've already lost. You win by going millions of miles deep into regulated industries with proprietary datasets and workflows they can't easily replicate. Find ways to coexist and leverage their tailwinds. Reminds me of what @bradlightcap said on his 20VC. 6. Move Toward the "Flat Company" Era: With the explosion of AI agents and advanced tooling, the traditional management layer is compressing. Shiv’s latest idealistic shift is building a hyper-flat organization: fewer managers, and highly leverageable "Super ICs" who can move in lockstep and cover massive surface area. (link in comments)