Lamp + Laundry Folding + Massage Curious what the price point will be

The trillion dollar opportunity in enterprise software is AI Agents. The reason for this is AI Agents expand many software categories because most tools have been constrained by the number of users on the other end of the tool. Enterprise software traditionally enabled people to do their work. But now the software also comes with actual productive output as well. This then breaks the traditional limits that many software markets have had, because smaller customers can use these tools more, new departments and industries open up, and previously scarce areas of work can be scaled more. For instance, most estimates put the code IDE category at a few billion dollars just a few years ago. This has - amazingly - always been a very small category of software. Well, now with AI Agents, the IDE market and coding in general is one of the fastest categories of spend in tech. This is because it’s bringing automation to a high value activity and supplying the world with a traditionally very scarce and high cost resource, engineers. The same is going to be true for many other categories of work across legal, financial services, healthcare, and more. Amazingly, this now opens up many niche categories that just wouldn’t have been economically viable for a software company before. For instance, making a business out of selling software to life sciences regulatory compliance managers would have been sub-scale before, but in a world of AI Agents this all of a sudden becomes possible. We’re already seeing this in our initial Box AI Agent use cases. Many of the early Agents being created by customers are for automating or augmenting work in previously underserved areas. This is letting customers automate a process they never would have gotten around to before, or dramatically expanding the output of work they were already doing. In all cases it’s more TAM that software wasn’t touching before. In all, it’s clear that AI Agents are going to grow many software categories. It’s an incredible time to be going after these spaces because even the small ones will now be massive, and the big ones will just get bigger. Tons of opportunity.

Our team is hosting a big event for interns in NYC this week. RSVP at the link below if you're interested in mixing it up with some VCs and top operators from Ramp, Tabs and other great companies

Wild to think that BNPL volume went from basically $0 to $125B over the last 6 years This doesn’t feel like it’ll end well

Unitree is the new DJI. Undercut the competition massively on price Unitree vs. Competition - $5,600 vs. $20K-100K DJI vs. Competition in the early days - 12-40% less expensive In a guaranteed massive market - Humanoids - $30-38B by 2035 Drones - $40-73B Gobble up market share to keep competition from even getting out of the gates DJI Market Share Consumer Drones - 70-80% Commercial Drones - 65-75%

1/ The U.S. just took a major step toward streamlining nuclear energy—and it’s being powered by AI. Oak Ridge National Lab is partnering with Atomic Canyon to use an AI trained on 53 million pages of nuclear regulatory data to accelerate reactor approvals. Here’s why it matters 🧵

80% of the VCs in SF that I reached out to for meetings next week are OOO Dear Founders, who wants a TS?

High ROI investment Offering to buy great founders every meal until they exit Then they always have to pay 50:1 LTV/CAC

Ill bet big money that @joerogan ends up taking a daily supplement with human lactoferrin in it, created by the startup Helaina within the next 12 months

A decade ago my boss made me read a book that still holds most of the blueprint for how breakout AI-native companies can scale today. When I first read Exponential Organizations, it changed the way I thought about building businesses. It unpacked what made companies like Uber, Airbnb, Amazon, and Spotify capable of growing 10x faster than their competitors—not by owning more assets, but by leveraging information, networks, and purpose. Today, those same principles are more relevant than ever—especially for AI-native startups. Exponential Organizations (ExOs) are built for scale. They tap into external resources—like communities, algorithms, and on-demand labor—and organize around a Massive Transformative Purpose (MTP) to drive alignment, speed, and adaptability. Here’s what they get right: SCALE – the external drivers of growth: (S)taff on Demand – flexible teams instead of full-time headcount (C)ommunity & Crowd – ideas, feedback, and distribution from users (A)lgorithms – decision-making and automation at scale (L)everaged Assets – use, don’t own, the infrastructure (E)ngagement – reward participation through platform dynamics IDEAS – the internal operating system: (I)nterfaces – intuitive experiences for all stakeholders (D)ashboards – real-time data to guide execution (E)xperimentation – constant testing and iteration (A)utonomy – teams empowered to move fast (S)ocial Technologies – digital tools for transparent collaboration AI-native companies that follow this playbook don’t just build faster. They build differently. If you’re scaling a vertical AI startup right now—or thinking about how to—this framework is still one of the sharpest tools you can use. Building an AI Native business? I'd love to learn about it. #VerticalAI #Startups #Scaling