My conversation with Gabe Stengel (@GabeStengel), founder and CEO of Rogo. For years, Gabe and I have talked about how much of an investor's job AI will eventually do and how he is building Rogo toward that future. Today, Rogo helps some of the world's largest financial institutions research companies, run diligence and execute M&A. But Gabe's ambition is much bigger. He is building toward investing superintelligence, where Rogo does much of the work inside investment banks and firms and becomes the venue where they do their deals. It's a fascinating business and has been so fun watching Gabe build it. We discuss: - 10,000 agents searching for one great investment idea - Which investing skills will still matter - Why Anthropic/OpenAI won't win finance - "Chewing glass" - Why the harness around the models matters so much - Getting rejected by 40+ investors - Building an AI native Bloomberg - Becoming a black hole for talent Enjoy! TIMESTAMPS: 0:00 Intro 2:38 Building Rogo 6:12 10,000 AI Agents 12:02 Skills That Still Matter 17:31 Beating OpenAI and Anthropic 28:35 Bloomberg of the AI Era 37:37 Rogo’s Company Brain 44:19 Chewing Glass 53:34 AI-Native Finance 59:21 What Humans Still Do Better

Gokul (@gokulr) explains why utility-based software companies like Zendesk are more exposed to AI than systems of record like NetSuite, and why public markets aren't distinguishing between the two: "The software companies that should be the most worried right now is where they are pricing the product based on utility. Zendesk is a good example. Instead of paying for 50 Zendesk seats, you can pay for 20 and I can have 30 AI agents sitting next to Zendesk. For these companies you need to change your pricing model to be based on outcome. It's going to be hard for them to stay public. The companies that are less exposed are ones based on data that has been collected and captured over a period of time. ERP is a great example. There is no compelling reason for someone to put their career at stake by ripping out NetSuite. NetSuite has more time to build AI agents on top of it because they have the data, they can train the AI agent on top of it and bundle it. I think the public markets do not distinguish between these two types of companies." (Jan 2026)

the new investing meta might be to just full port into anyone @colossusmag or @colossusjeremy interviews

Gabe Stengel on why every software company will eventually charge based on outcomes: "I look at how hard it was for Anthropic to sell to us. Very easy. And the amount that we pay them has risen exponentially without a human in the loop because it's a token consumption model. Every business needs to go through two different pricing revolutions. You need to move to some sort of usage-based, and then you need to move to some sort of outcome-based. For me, if I can figure out a way to skip the usage-based, and just wait until I can say, 'Hey Patrick, what if I just charge you for every good investment idea I give you? Or what if I charge you for the quarterly report you send to LPs that I can do perfectly?' I would much rather get there than have to figure out some random way of trying to assign dollars per token. You're going to spend $100,000 on tokens and say, well, did I get $100,000 of value? And I don't really know. But you know what the value is to you of a good investment idea because you can actually see how much money did I earn."

Ingredients coming together for nyc launch: One of the best founders alive (@eldsjal) One of the most talented new founders (@HNilsonne) The magic man (@shak) An amazing team 8 years developing their own technology 8 years iterating on the experience Finally, nyc gets Neko

Launch day! 🗽🇺🇸

How to build a defensible vertical AI company: "The industry actually does have to have enough complexity and depth in the types of data, systems of record, deployment models, that you can spend a lot of effort solving those problems in order to have a wedge to solve everything else. The second thing I would look for is domain expertise from the team and the founders. I have over 100 people that have spent time within investment banks or within investment firms across the world's best institutions. Our job is really to catch the change in the models and figure out how to apply it into these institutions. The final big thing I would look for is a business that's willing to constantly reinvent the core product and constantly willing to slash it to nothing."

This talk is so, so good Favorite idea—This photo shows what tech did to number of pictures taken. Now same progression happening to code. Then it’ll happen to…

Listen to the Zuckerberg profile as an audiobook, free of charge. Read by Scott Brick, the voice of Dune, Moneyball, Jurassic Park, Atlas Shrugged, Chernow’s Washington and Hamilton, and the Foundation and Jack Ryan series. Link in the article below.

“You can't take this away from him. He wouldn't be him if he stopped.”

Self recommending

Yesterday’s launch a great excuse to read this on Zuck

Gabe's answer to the kindest thing anyone has done for him was about both his parents, and how differently their kindness showed up: "My mother's version of kindness was no matter what I did, I was amazing and smart and could do no wrong...you need some of that irrational confidence that comes from undying love. My dad was very different...his version of kindness was figuring out how does he understand who I am and why I am failing at this thing and then help me...while staying true to his standards of excellence."

Every internal conversation at Rogo is recorded and fed into a company brain called Shrek. "When anyone starts, we say, "Hey, just FYI, you're always being recorded." There's a dashboard where you can see the swamp of everything that people are working on at any given time, but it's connected to all of our different systems. It can shape every answer and deliverable that way, and it's both proactive and reactive. Someone can go in and say, I'm trying to get up to speed on how I should talk about model routing and how I should think about the value prop there for a very large institution and what the savings will be, and it can pull out all that information for you."

IB chat is one of Bloomberg's strongest moats. People pay $25k+ a year for a terminal in large part because everyone they need to talk to is already on IB. @GabeStengel on building the same thing for agents: "Bloomberg's strategy was, offer a little bit of data to get in the door, build all the analytics and workflows on top that someone would need, and then provide the exchange and the communication platform where you can actually transact in a bunch of asset classes that before was pretty opaque. Bloomberg Messenger. For us, it's use a little bit of AI to get in the door, build out the full workflows, go from co-pilot chatbot to full autopilot tool, and then provide the communication channel between counterparties so that if I have agents that can autopilot do the work, I can actually transact for you. I don't need to build the communication channel for humans to transact, I need to build the communication channel for the agents to transact across these investment firms. Think about what is the system that would allow a large private equity firm to feel comfortable having an agent negotiate a deal on its behalf. You need to replace email, you need to replace the data room providers, you need to replace all the governance and calls that happen on top. There's a huge amount of software to be built out."

Favorite part of the episode was Gabe's pitch to talent: "AI is going to completely transform the world. The place that is gonna be the most interesting is applied AI, because that's where AI intersects with humanity. The companies that dictate how AI intersects with humans are gonna do the most interesting creative engineering and product work in the world. Finance is the catalyst for all human progress and innovation, and capital allocation is upstream of the financing of every company, every idea, every economy. If you can make that more efficient, you can supercharge the world. We're the category leading player who has the best shot on goal to not just be the $100 billion business to do it, but the $500 billion business that completely transforms capital markets. There's such a depth and a complexity and an amount of interesting problems that's so exciting, and we have a killer group of people that is super smart, hungry, curious, and low ego that's gonna do it."

The reason money motivated people make for bad venture backed founders is precisely because they have not actually internalized this truth about the nature of venture. Failure does not mean walking with nothing, it means taking the $30,$50 or $100MM personal liquid stake you have in hand and betting double or nothing on it over and over to have a slim chance at it becoming $10bn. It’s a bet no person who’s in it to be rich would take. It’s only those who are in it for status, glory and power.

The best investors amplify the sense of destiny of founders. Great example from Mike Moritz below, where he compared a fledgling Yahoo to Apple.

A big part of an investor's job is making founders more ambitious "Pat Grady (@gradypb) was at our board meeting and we presented an extremely aggressive plan for next year in terms of hiring goals, commercial goals, product goals. He goes, 'Gabe, if everyone in finance is gonna make a buying decision on AI in the next 18 months, and they are definitely gonna buy something no matter what, even if you're not there, then the only thing that matters is that you can blitz the market as quickly as possible to make sure that you are there. Given that, do you think this plan is aggressive enough or no?' The answer was no. And the reason it wasn't aggressive enough is because I was being soft. My goal as a venture-backed business is to increase the tails of the distribution. It's fine if it gets 30% more likelihood that I fail if the odds that I become a $100 billion company also increase by 20%. But you actually have to be okay with raising both of those tails at the same time."

I laughed at loud at Gabe explaining low reception to the Series A, saying "they didn't invest because the product was terrible". I first got my hands on Rogo in fall of 2024, and can confirm: the product was terrible. The remarkable thing about Gabe and the Rogo team has been the accelerated pace of improvement. Fast forward two years, I had a moment this summer where I ran a number of my investment research workflows through Rogo and ran evals vs. my Claude system and Rogo routinely won in head to heads. Rogo's Felix is this sort of malleable agentic substrate that has become flexible to deploy and delightful to use. And importantly, I'm too obtuse to predict the future but I've learned to trace the curve of the exponential. I am super excited to see what this team builds for investors, and think the next 6-18 months for investors deploying AI is going to get very exciting.

Gabe on why he doesn't think Anthropic or OpenAI will own finance: "The reason people get confused when they look at app layer businesses like mine or Harvey or Legora or Sierra is because there's a spectrum of perpendicularity to what the labs are building. There's a whole bunch of stuff underneath the surface that the labs are never going to build, that we need to build for finance. All of finance is a collection of different niches with different data sets, different regulatory requirements. And we can get to $5 billion in revenue by going deep across those things and creating the systems of record that help manage them. That for Anthropic would be like stopping on the side of the road to pick up a penny, because they're on the pathway of trying to go from $100 billion in revenue to a trillion in revenue. Say you are a big public company buying another big public company and you need to send data back and forth. You actually need some sort of data room, something that is compliant, safe and secure. And I don't think OpenAI or Anthropic will ever want to build a data room business. If you actually want to be the exchange for all of high finance, you don't just need to own the intelligence, you need to own the transaction venue, the communication venue, the workflows, and all the data inputs that go into it. Think about the fundamental difference between Claude Code when it came out versus ChatGPT. The models were actually fairly similar, but the harness and the way that it was presented from Claude was far better. The way that you harness these models is so, so important."