Roger Ehrenberg

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Roger Ehrenberg

Roger Ehrenberg

@infoarbitrage

partner @ebergcapital @AlpineF1Team @marlins @realsaltlake. founding partner @iaventures. @thetradedeskinc @Wise. @UMich @Columbia_Biz. family man. @umich 〽️

ÜT: 40.76136,-73.980129 Katılım Şubat 2008
244 Takip Edilen35.5K Takipçiler
Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
I haven’t really viewed reserves as a specific number - it’s the concept of optimizing the risk/reward profile of the portfolio. This means being comfortable with extreme concentration when you feel those follow on checks reflect attractive risk/reward trade offs. The issue with very early stage fund is, of course, recycling. My tendency is to deal with that as it comes rather than to view it as a hard constraint. Take the great opportunities that present themselves to you now and figure out how to take advantage of other great opportunities later.
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Harry Stebbings
Harry Stebbings@HarryStebbings·
My Biggest Lesson on Reserves Four Funds In: "My first three funds. I did do reserves and I did some great reserve investments. I put 15% of my third fund into @owner @adamguild their series A. So that was a good investment, but I realised the opportunity cost of that investment given where I come in, it could be 20 to 30 pre-seed investments and the value creation at the pre-seed is so high that I decided for my fourth fund, no reserves, just everything up front." @Joshuabrowder What do you know now about reserves that you wish you had known when you started @chadbyers @NWischoff @honam @infoarbitrage @jasonlk?
Harry Stebbings@HarryStebbings

I am going to piss off so many friends by saying this but if I could invest in one emerging manager sub $50M fund, it would be @Joshuabrowder. A few things you need to know about Josh: - He makes the founders he invests in live in his spare room at the Four Seasons until they raise their seed - He turned his $100K Thiel Fellowship grant into a $10M angel portfolio - He was one of the first cheques into Micro1, Yuzu and many more - When he found out his father had been taken by the Russians, he was playing poker… (legend!) I have never had founder references like the ones I got on Josh. I spoke to 12 founders. He averaged 9.2/10 across all 12. This is one of the best episodes we have done in a long time and my notes below: 1. Why I Believe Young Founders Make the Best Founders Young founders have no safety net and no option but to win. Corporate engineers often default to hiring big teams, while young founders stay focused on building the product. Their grit is much higher. Without that level of dedication, most people quit at the first real obstacle. 2. How I Test Founder Commitment Before Investing To filter out tourist founders, schedule a pitch meeting at 11:00 PM. Elite founders accept immediately. Mediocre ones push it out by weeks. During the interview, ask rapid-fire questions. If they claim a specific revenue number, have them pull up their live Stripe account on the spot. Look for tactical customer acquisition goals, not vague partnership promises. 3. Why I Make Founders Live With Me After Investing The best early investments come from deep day-one relationships. Living together creates a focused, one-person accelerator where founders get a three-week crash course and avoid years of mistakes. The rule is simple: co-founders share one room near the Four Seasons and cannot check out until they raise an institutional seed round. 4. Why Pre-Seed Companies Fail Startups usually fail for three reasons: they run out of money, they run out of hope, or the co-founders break up. Money problems usually come from weak pitching, which is why founders should drop the deck and show the product live. To maintain hope, ignore Silicon Valley vanity signals and focus on customer progress. To avoid team blowups, handle mechanics like vesting early. 5. What Founders Need to Know About Signing With a VC VCs will say almost anything to get you to sign on the spot. They reverse-engineer your desires and claim they know every customer you want to meet. Impressionable founders fall for it, but the promised intros often never happen. Never sign in the room. Take the night to think clearly. 6. My Biggest Lesson on Reserve Investing Holding back reserves for later rounds has a huge opportunity cost. The biggest value creation happens at pre-seed, so saving capital for a Series A follow-on can limit your upside. Deploying upfront into 20 to 30 pre-seed companies can produce far better long-term returns. Go all-in early. (links below)

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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
If you’re really early, the bias should generally be towards slightly insane and irrational founders who have a non-consensus take on a large market. If you’re really early, a small venture check can get you large ownership if you can make the case that your money isn’t a commodity. If you’re really early, you can generally create a 25-30 constituent venture portfolio where you can concentrate into most promising companies. If you’re really early and if you’re a talented assessor of people and markets, 2 great companies can produce a generational fund. These fundamental principles haven’t changed in my 20 years in venture. Amidst the chaos, it’s really the same f&cking game at the pre seed and seed stages IMO. Maybe I’m wrong but I don’t think so.
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Packy McCormick
Packy McCormick@packyM·
Some spicy takes on venture capital: - Saying that "seed has gotten expensive" or something and then pointing to a valuation - like "they used to be $10 million and now they're $20 million" - is bascially the same thing as people who say Stock A is more expensive than Stock B because Stock A has a share price of $100 and Stock B has a share price of $5. - The market has gotten better at differentiating among startups earlier and pricing accordingly. - Some very big funds will generate great returns and some will generate poor returns. - Some small funds will generate great returns and some will generate poor returns. - Some concentrated funds will generate great returns and some diverse funds will generate great returns. - The concentrated funds probably have a higher ceiling, and the diverse ones probably have a higher floor. - Some generalist funds will do really well, as will some sector-specific ones. - Some of each will do really poorly, too. - Ownership % is overrated - easy to measure so gets measured but practically meaningless except in hindsight. No shit it would be better to own 20% of your biggest winner than 10% or 1%. - Manager-strategy fit matters much more than any prescribed portfolio construction. - Portfolio construction is overrated, too, because it's something you can measure. - The best portfolio is one that puts all of its money in the best returning investment of the vintage. - LPs who invest in emerging managers basically all want high ownership at pre-seed and seed to have the potential for outlier returns, but like, if enough emerging managers fit that box to attract capital, those returns get competed away. - Plus, the megafunds can usually win whatever they want at pre-seed and seed. They just have the luxury of waiting. - Even if AI is what everyone thinks it is, there are too many funds and dollars chasing it for it to be a good strategy for all but a pretty small number of funds. - This will take a while to see, because the companies grow fast and markups will look good on paper for a while. Exits will probably be harder. - Pretty much every AI application company is long AGI and short ASI. - But there is a scary amount of consensus around AI. What if AI isn't what everyone thinks it is? - Tech is going to get much bigger and there will be fewer, bigger winners, which means a lot of this is probably about getting into the companies you think have a shot at being one of those at prices that don't make you throw up too much. - [always has been meme] - Greatest job in the world - All of the above notwithstanding, I'm pretty sure that my strategy is the optimal one.
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
@HarryStebbings Once you develop your thesis, execute the strategy and don’t panic. Succumbing to FOMO and PR hype cycles is bad for your mental health and your returns.
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
The future is bright, and Simon Sokol, Ethan Ehrenberg and I are here to make Equipe ubiquitous across the sports and, eventually, the enterprise customer landscape. hashtag#data hashtag#infrastructure hashtag#fandom /fin
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
The Equipe business sits at the intersection of pretty much everything Game Changers Ventures cares about, and bringing our full capabilities to bear in helping Nick and Sajan to build the best business possible is truly a gift /3
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
We @gamechangersvc have been working with Nick Benson and Sajan Gutta from earliest days. We explored how our shared love of data, infrastructure, fandom, disruption and sport might help in a landscape short on modern technology but long on opportunity. The result was @EquipeHQ /1
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
Six months ago, we formally launched @gamechangersvc. It feels good — really good — to be back building a firm from scratch around ideas and domains where I have deep conviction. Even better is doing it with @ssokol94 and @ethanehrenberg, and with the founders we’ve had the privilege to back so far. Early-stage venture, when done right, is not a transactional business. It’s a deeply personal one. Our job is to help founders become the best versions of themselves — as leaders, as decision-makers, and as humans — while they attempt something very hard. I believe we’re doing that the right way. I also believe what we’re building into is not cyclical, but secular. AI will reshape almost everything about how we work and create. Paradoxically, that will only increase the value of being human together — gathering, belonging, cheering, participating, identifying with something larger than ourselves. Sports, entertainment, live experiences, and the technologies that power them sit squarely in that shift. To us, it looks like a generational opportunity. When I first announced the firm, I mentioned that we would eventually add one more partner-level person. That remains true. There is no job description. There is no timeline. There is no “process.” What there is: openness. We are looking for someone who is AI-native in their thinking, intellectually curious, comfortable with ambiguity, and genuinely passionate about sport, entertainment, community, and culture. Someone who wants to build a firm — not just join one. Someone who extends how we think rather than simply amplifying what we already do. This person may not currently be in venture. They may not even be in this sector. In fact, that could be a feature, not a bug. The goal isn’t incremental horsepower. It’s new perspective, judgment, creativity, and values alignment. There is also no rush. The right partnership is discovered, not hired. We’ll get to know this person over time, and they’ll get to know us. In all likelihood, this will be the last person we ever add. The aspiration is a very small, very high-trust, very long-term partnership — similar to what we built at @iaventures. That model worked pretty well, and it was a lot of fun. If this resonates with you — or with someone you think we should know — my inbox is open. roger@gamechangers.vc #LFG #vc #builders
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Lenny Rachitsky
Lenny Rachitsky@lennysan·
My biggest takeaways from @sherwinwu: 1. AI is writing virtually all code at OpenAI. 95% of the engineers use Codex, and engineers who embrace these tools open 70% more pull requests than their peers, and that gap is widening over time. 2. The role of a software engineer is shifting from writing code to managing fleets of AI agents. Many engineers now run 10 to 20 parallel Codex threads, steering and reviewing rather than writing code themselves. 3. The average PR code review time has dropped from 10-15 minutes per PR to 2-3 minutes. Every pull request at OpenAI is now reviewed by Codex before human eyes see it, and Codex surfaces suggestions and catches issues up front. This allows engineers to focus on more creative and strategic work while dramatically increasing productivity. 4. The models will eat your scaffolding for breakfast. When building AI products, don’t optimize for today’s model capabilities. The field is evolving so rapidly that the scaffolding (vector stores, agent frameworks, etc.) that seems essential today may be obsolete tomorrow as models improve. 5. Build for where the models are going, not where they are today. The most successful AI startups build products that work at 80% capability now, knowing the next model release will push them over the line. 6. Top performers become disproportionately more productive with AI tools. AI tools amplify the productivity of high-agency individuals, so the gap between top performers and everyone else is widening. The ROI on unblocking and empowering your best people compounds faster than ever in an AI-augmented environment. 7. Most enterprise AI deployments have negative ROI because they’re top-down mandates without bottom-up adoption. Success requires both executive buy-in and grassroots enthusiasm. Sherwin recommends creating a “tiger team” of technically-minded enthusiasts (often not engineers) who can explore capabilities, apply AI to specific workflows, and create excitement throughout the organization. 8. The one-person billion-dollar startup is coming, but with unexpected second-order effects. As AI makes individuals more productive, we’ll see not just billion-dollar solo founders but an explosion of small businesses: hundreds of $100M startups and tens of thousands of $10M startups. This will transform the startup ecosystem and venture capital landscape. 9. Business process automation is an underrated AI opportunity. While Silicon Valley focuses on knowledge work, most of the economy runs on repeatable business processes with standard operating procedures. There’s massive potential to apply AI to these workflows, which are often overlooked by the tech community. 10. The next two to three years will be the most exciting in tech history. After a relatively quiet period from 2015 to 2020, we’re now in an unprecedented era of innovation. Sherwin encourages everyone to engage with AI tools and not take this moment for granted, as the pace of change will eventually slow. 11. AI models will soon handle multi-hour tasks coherently. Today’s models are optimized for tasks that take minutes, but within 12 to 18 months we’ll see models that can work on complex tasks for upward of six hours. This will enable entirely new categories of products and workflows. 12. Audio is the next frontier for multimodal AI. While coding and text get most of the attention, audio is hugely underrated in business settings. Improvements in speech-to-speech models over the next 6 to 12 months will unlock significant new capabilities for business communication and operations.
Lenny Rachitsky@lennysan

"Engineers are becoming sorcerers" @SherwinWu leads engineering for @OpenAI’s API platform, which gives him a unique view into what’s going, where things are heading, and what the future of software engineering looks like. Over 95% of engineers at OpenAI use Codex daily, each works with a fleet of 10-20 parallel AI agents, and he's seeing the productivity gap between AI power users and everyone else widening. In our conversation, discuss: 🔸 Why the next 12-24 months are a rare window of opportunity 🔸 Why “models will eat your scaffolding for breakfast” 🔸 What OpenAI did to cut code review times from 10mins to 2mins 🔸 How AI is starting to change the role of managers 🔸 Why most enterprise AI deployments have negative ROI Watch below and find it on YouTube here 👇 youtu.be/B26CwKm5C1k

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Simon Sokol
Simon Sokol@ssokol94·
Goodbye Toronto 🇨🇦 So excited to have officially moved to New York 🇺🇸 to partner with @infoarbitrage and @ethanehrenberg to build @gamechangersvc! To all sports, media & entertainment tech founders, don't hesitate to reach out. PS GO JAYS
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
I know Detroit well and am building several business there, and I can say Dan's perspective is spot-on. It's nowhere near time to declare victory - you don't fix 50 years of troubled history in a single generation - but the progress is real and has to be seen. #LongDetroit
Dan Reese@DanReese21

What US city has the largest gap between national perception and reality? My answer: Detroit Everyone seems to think it’s a run down hell hole w nothing but boarded up buildings. In reality: > Completely rejuvenated downtown w businesses, residential, restaurants, & nice sports venues – Ford Field (Lions), Comerica Park (Tigers), Little Caesars Arena (Pistons & Red Wings) > One of the best airports in the country – Delta hub w direct flights all over the world > Tons of history, culture, and classic architecture > Diversifying economy beyond auto into tech, medical, etc. > People are genuinely nice but also super tough & resilient Of course it’s not all unicorns and rainbows. While some parts of the city are making a comeback, others are being left behind. There’s crime, traffic and all the other things most big cities battle. But if Detroit has a national reputation of 1/10, in actuality I think it’s more like 7/10.

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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
If I recall, @joshk , didn’t the same thing happen to @square when they had a pre-IPO ratchet deal that seemingly cost a lot of money but ultimately paid off in spades for the founders? It’s insanely hard to do but wow, if you get it right…
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
This post is genius. It’s so hard to accept because of ego. But by ignoring ego and playing the long game, controlling emotions can unlock intrinsic value. Short-termism is a tax on our futures, especially for those with great ideas that take a longer time to unfold.
Josh Kopelman@joshk

Private company CEOs go to extreme lengths to avoid down rounds. But from Jan 2022 to Jan 2023, almost every public company took the equivalent of ~40% Down Round. Of the 63 public companies in the Bessemer Cloud Index: • ~97% were down (61 out of 63) • Median drawdown ≈ 40% docs.google.com/spreadsheets/d…

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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
@HarryStebbings So yes, one of the best traits in deal making and in life is to listen. Actively. I want to listen, and to learn. Conquer this, and you’ll be in a better position to evaluate and to make better decisions. Always.
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
@HarryStebbings Humans want to talk. Humans are generally uncomfortable with silence. The ability to let others fill the empty spaces takes discipline and is a sign of pushing down ego to learn. Most people are really bad at this.
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Harry Stebbings
Harry Stebbings@HarryStebbings·
"Listen more than you speak, because movement is not action in deal-making. Talking the most doesn’t mean you’re in control, and silence doesn’t mean the other side isn’t listening. All deal-making is people reading people, one-on-one, in groups, and at scale." What are your single best pieces of advice to founders on deal-making @honam @infoarbitrage @ilyaf
Harry Stebbings@HarryStebbings

The story of Harvey is absolutely fricking wild. Two friends, a lawyer and an engineer realise the power of OpenAI and legal and cold email Sam Altman and co. They have calls which lead to OpenAI leading their Seed Round as the sole investor. (baller) Sequoia (@gradypb), @eladgil @saranormous go on to lead their Series A. The company today does: - $190M in ARR - 500+ employees - 1,000+ mega customers The best shows are art (storytelling) and science (frameworks). This has both off the charts. Spotify 👉 open.spotify.com/episode/2PiFsM… Youtube 👉 youtu.be/PhbVnUBmygA Apple Podcasts 👉 podcasts.apple.com/us/podcast/20v… My 7 takeaways with @winstonweinberg and special thanks to @mamoonha for making this show happen 👇 Timestamps: 00:00 Intro 04:16 #1 Thing Every Founder Needs to Do Everyday 13:35 Why VCs Suck at Helping Companies Hire? 15:26 How to Get Sequoia and a16z Term Sheets 25:49 What No One Understands About Enterprise AI Adoption 38:21 AI's Impact on Professional Services 39:14 Future of Law Firms: Do They D*e? 43:17 What Everyone Should Know That No One Tells You About Hiring in Europe 48:54 I Have Massive Trust Issues… 55:55 Biggest Lessons on Effective Deal-Making 01:01:30 Cold Emailing OpenAI and It Leading to a Term Sheet 01:05:10 Quick Fire Round

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Harry Stebbings
Harry Stebbings@HarryStebbings·
We have a big problem. The venture model doesn’t work with the current public market revenue multiples. Datadog ⬇️ 21% Figma ⬇️ 20% Wix ⬇️ 38% Braze is 2.5x ARR Atlassian is 4.8x ARR Klaviyo is 4.5x ARR Venture doesn’t work unless this changes. Agree @infoarbitrage @bgurley @jasonlk @rodriscoll?
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Roger Ehrenberg
Roger Ehrenberg@infoarbitrage·
No. It’s not just about multiples - it’s about competitive positioning, growth rate and margin dynamics. Multiples are what they are for different reasons - interest rates, sector preferences, growth rates, margins, etc. You can’t lock into a single metric and look at it in a vacuum. And you certainly can’t extrapolate from a handful of companies - too many conflating variables at work
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Chon Tang
Chon Tang@chontang·
@infoarbitrage @HarryStebbings If that was true, just buy the proven revenue from Wix / Datadog and wait for multiples to come up. No reason to invest in startups at a tiny fraction of the size.
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Keşfet

@owner @adamguild @Joshuabrowder @chadbyers @NWischoff @honam @jasonlk @HarryStebbings