The number one long-term thing you should do to spur economic growth is to encourage business formation and investment. This does the opposite.

AI Agents have the potential to democratize knowledge work in the same way that SaaS democratized software. And as we've seen in the past couple of decades with software, every time you make a service cheaper and more available, you dramatically increase the size of the total…

AI agents have the ability to fundamentally change the business model of enterprise software. Today, when you build a SaaS product, the primary business model is to sell seats that are tied to the end-users of your service. For 'same store' sales, you can essentially grow at the…

One constraint of SaaS is that revenue growth is mostly tied to your customer’s headcount growth. The AI Agent business model is unconstrained by headcount, and instead driven by the productivity of the agent. This has major positive economic implications to software.

The next big breakthrough in AI is AI Agents. This is when AI goes from being used as an assistant to chat with, to using AI to accomplish complete tasks that a human might otherwise have to perform. This moves AI from being a 'read-only' operation to fundamentally a 'read/write'…

The next big breakthrough in AI is AI Agents. This is when AI goes from being used as an assistant to chat with, to using AI to accomplish complete tasks that a human might otherwise have to perform. This moves AI from being a 'read-only' operation to fundamentally a 'read/write'…

Bill Joy, the cofounder of Sun Microsystems, famously said “no matter who you are, most of the smartest people work for someone else.” What’s crazy is that in the world of AI Agents, that could finally no longer be true.

Guaranteed we’re watching the origin story for a $100B robotics company play out.

The cool thing about AI is this is Zuck unleashed. There’s a brand new platform opportunity, the market is early and up for grabs (and there will be multiple winners!), and it uniquely leverages the strengths of Meta. The breakthroughs in this space will continue to be wild.

iRobot stock is down 90% since Amazon announced an intent to acquire it and then was blocked. Blocking non-monopolistic M&A only makes it less likely to fund risky ideas, because there are fewer exit opportunities. Bad for innovation, ironically fine for incumbents.

The Google situation is a reminder that if you build software for a living, there’s a chance at some point it will be used in areas not always aligned to your personal beliefs. This is true at every layer of the stack: from the chip to the app layer. This is what you sign up for.

Incredible to have Meta out here pushing open source AI forward in such a major way. An amazing moment to be building software when you have $100s of billions of dollars from the major tech players going into advanced R&D and infra that directly benefit you as a developer.

This makes no sense for any party involved. Salaries will drive viewership which drives revenue which drives salaries.

The two biggest biases you’ll run into when doing a startup are from people that know *too* much:

1. This problem is already solved and doesn’t need a new solution

2. Every time this problem has been attempted to be solved it never works

Sometimes you just need fresh eyes.

Generally speaking expect your hair to go gray at a rate of 10% per funding round, until you go public when the rest turns gray after your first earnings call.

Fun fact: during Box’s Series B we were in the midst of pivoting to the enterprise, with an untested freemium model, and running out of runway. The strategy was speculative. Every partner we pitched passed, but one associate (Mamoon Hamid) fought to push the deal through, saving us.

What a glorious time it is in the tech industry that there’s a raging debate on what level of investor you should be pitching. These are first world problems. Back in my day we’d pitch you if you had a working email address.

It is insane that just 18 months ago the state of the art AI model had a 4K token limit, and today state of the art can reach 1M tokens. There are essentially no examples in history of a technology improving at a rate of 250X in under 2 years.

Oh god “delve” is now stuck in my head and I’m probably going to start using it in like every 3rd sentence.

One of the most common concerns about AI is the risk that it takes a meaningful portion of jobs that humans currently do, leading to major economic dislocation. Often these headlines come out of economic studies that look at various job functions and estimate the impact that AI…