I just bought a new Model Y and can confidently say cars and Teslas are no longer the same product. A car is like a pony or horse. I still like driving a stick shift, it’s fun! Tesla with FSD is a transportation robot. I had one of the first Model 3s in 2017. FSD was basically slightly better cruise control. Great on the highway. But honestly felt oversold. So I have been driving a BMW for the past 3 years. Great horse, fun to drive. But tried FSD recently and holy shit — it’s a personal Waymo. Works perfectly. I just went to the Fremont factory to get my new car, entered my address 30+ mins away, pushed a button, and got home without doing a thing. I don’t think most people realize how good this is, probably because they only experienced an early version previously. This is 1000x better. Metaphor for AI writ large. Like trying GPT 3.5 and thinking it’s cute and hallucinates, and dismissing it…while Astra launches in 2026 and is orders of magnitude more capable.

The payments market is going to massively expand over the next decade because: 1. ANYONE can now build anything digital — AI code creation means exponentially more digital SKUs that can be created and, of course, paid for. We are in the very early innings here. The gating item is just human creativity. Combined with: 2. Almost anything that was “payroll” (paying PEOPLE) can now be “payments” (paying for THINGS). For example: “Hiring an assistant” or “hiring a paralegal” (both payroll) -> paying for a SKU. We don’t think of ADP or Paychex as payments companies because they aren’t; they are payroll companies. Paying people != paying things. But more tasks/outputs that were once only available through “paying for people” now become available for purchase on a credit or debit card. This is already starting to happen and accelerate. And of course, this is not zero sum! Much of this is “everything to the right” of the supply-demand equilibrium point, where there’s conceptually high quantity demanded at a very low price where there’s heretofore no (human) labor supplied. Lots of people will want to purchase a SKU who were unable to hire a person historically.

The Principal-Agent vs. Agents Problem Every human in the workforce has two crude goals: 1. Be richer. 2. Be lazier. Get paid 2x more, or keep salary flat? Get paid more! Go home at 11:01 PM, or stay up until 5 AM? Go home at 11:01 PM! This isn’t a moral judgment. It’s just…economics. Which brings us to one of the stranger problems with enterprise AI: AI can make every employee dramatically more productive without making the enterprise any more productive. Imagine a Goldman Sachs analyst. At 11 PM, the boss sends over a presentation with the traditional two-word demand: “please fix.” In the old world, the analyst spends six hours changing fonts, updating charts, reconciling numbers, and moving logos three pixels to the left. The deck is finished at 5 AM. In the new world, the analyst secretly gives it to AI. The deck is finished at 11:01 PM. The analyst goes home and goes to sleep. This is obviously a massive productivity improvement for the analyst. What changed for Goldman Sachs? Nothing! The same presentation was delivered. The same analyst is employed. The same salary is paid. The same client is billed. Goldman doesn’t get a bigger fee because its analyst slept six extra hours. AI created an enormous economic surplus. The analyst captured 100% of it in the form of leisure. This is the classic principal-agent problem—with a new set of agents. The enterprise is an ethereal “principal.” It wants more revenue, lower costs, faster turnaround, happier customers, etc. But an enterprise can’t actually do anything. It needs human agents—employees—to act on its behalf. Now those human agents have AI agents acting on their behalf. So the chain looks something like: Enterprise principal -> human agent -> AI agent The enterprise wants more output per dollar. The human wants more dollars per unit of effort. The AI agent generally follows the instructions of the human sitting at the keyboard. Guess whose objective function gets optimized first? This is why AI “adoption” inside an enterprise can be wildly misleading. Maybe 90% of employees use AI every day. Maybe every analyst, associate, paralegal, recruiter, consultant, and salesperson has become 5x more productive. But if headcount is the same, output is the same, and revenue is the same, the enterprise has adopted AI technologically—not economically. The employees are richer in time. The principal is not richer in money. This also relates to a point I made recently ( sometimes the user is not the customer. User = person who actually uses the product. Customer = person who actually pays for the product. Normally, user != customer is a strong negative for product quality. If the user and customer are the same person, the product, sign-up flow, onboarding, etc. all have to be great. If they’re different, the customer can force the user to tolerate an awful product. But AI introduces a different—and more interesting—version of user != customer. The human agent is the user. The enterprise principal is the customer. And their goals are not necessarily aligned. The Goldman analyst might LOVE a product that turns six hours of work into sixty seconds. But the analyst might love it precisely because Goldman doesn’t know how much time it saves. What happens if Goldman finds out that every analyst is secretly producing presentations in sixty seconds? Two logical options: 1. The analyst class can be smaller. 2. The existing analysts can produce 5x more work. Both benefit Goldman. Neither necessarily benefits the analyst. So the analyst has a perfectly rational incentive to use AI—and an equally rational incentive to hide the productivity gain. The best product for the user might be one that the customer can’t see! This is also why banning AI inside enterprises will often just create “shadow AI.” If a tool gives somebody back six hours of sleep, a corporate policy memo is unlikely to stop its use. The tool is effectively part of the employee’s compensation. The real enterprise opportunity, then, isn’t merely to get employees to use AI. They’re going to do that anyway. The opportunity is to get the principal to capture some of the benefit. That might mean selling completed outcomes instead of employee tools. Don’t give the analyst a faster way to make the presentation; make the presentation. It might mean redesigning workflows around the new level of output. If something that took six hours now takes one minute, the deadline shouldn’t remain six hours away forever. It might mean measuring throughput, turnaround time, revenue, resolutions, or other outcomes—rather than counting licenses and declaring victory because “80% of employees used AI this month.” And it probably means sharing some of the gains. If every productivity improvement results in more work, layoffs, or lower compensation, employees will rationally conceal productivity improvements. If employees participate in the upside—more pay, promotion, flexibility, or even permission to go home at 11:01 PM—they have a reason to reveal what AI can actually do. Otherwise, the enterprise will spend billions of dollars buying AI tools that its employees use to work less. AI can make the agent lazier. AI can make the principal richer. The trillion-dollar question is whether it can do both.

Sometimes the user is not the customer User = person who actually uses the product Customer = person who actually pays for the product If they are one and the same, then the product, sign-up flow, etc have to be great You know they’re not when you see something like this:

Today we're launching Macro 1.0 — a new office suite for the intelligence age. Macro is a unified workspace for your entire company, your team and your agents. 1. Fully open source. Built in Rust + SolidJS. Self-host if you want. 2. Designed as a single system: email, messaging, docs, tasks, agents, calls, and CRM all @-linked together in one tab. 3. Unified team-level memory for agents built over emails, team chat, tasks, PR's and CRM. Access the memory from Macro or AI or external agents via MCP. We built Macro for ourselves because we wanted a single system for our whole company. We didn't want to get slowed down by rate limits and 2FA'ing into 17 different tabs. Let's take a look at each block 🧵👇

“The most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of doubt, what is laid before him.” -Tolstoy, The Kingdom of God Is Within You (1894)

You chose 1973 as your baseline. Let me tell you what happened in 1973. The dollar fully floated after Nixon severed gold. The first Pell Grants were awarded. The HMO Act was signed. Your chart does not start before the crisis, Bernie. It starts at the scene of the crime. Healthcare up 35x because Medicare, CON laws, and the AMA cartel run medicine. Homes up 13x because zoning makes building illegal and the Fed prints. Rent up 15x because price controls and zoning strangle supply. Tuition up 23x because federal loans gave colleges a blank check. General prices rose 7x in that span. Everything government controls rose 13x to 35x. Everything it leaves alone got cheaper. You are not the prosecutor of this case. You are the defendant.

Don't (Start) Work in Venture Capital Almost every day I get a note from a student saying they want to get into venture investing. got a nice one yesterday from a rising senior at Harvard (comp sci major), here was my response: my strong, strong recommendation: don't start in venture capital or even investing! this is the greatest time in the world to *build* something. investors are parasites. they (we) need a host. as an investor, your destiny is basically whether you can find somebody to hitch your wagon to. but if you're technical and determined, you can now create anything! that having been said, when you are 21 you aren't exposed to a broad array of problems in the world. most college students i meet just know homework, dating, and food -- and consequently start companies/build products around those areas. so my recommendation (even if you want to end up as an investor): join a very exciting company now. there are only two jobs at real companies: making the thing, or selling the thing. choose which path you want. and as you get more experience there, and are exposed to more problems in the world, and more people in a work environment, maybe you'll start something. and THEN, you'll have a powerful network, an understanding of how products work vs don't work, deep insights that you can coach people with, etc. and you'll probably already have done a few little investments here and there. and THEN you will be interesting for a venture firm. i didn't reach out to any vcs to get a job, they all pursued me, which is not meant to sound arrogant -- rather it's how most firms operate. most venture firms don't hire mbas anymore. we want people who enhance our ability to find, pick, and win deals, and overwhelmingly this means people who worked at a startup. there are exceptions, but they're rare. it's the inverse of the world 30 years ago. good luck!

Well, it seems @WellsFargo is up to their old tricks! Opened a small “fee free” checking account (no fees with >$500 balance), they changed the terms to $15/month fee, never notified me, froze account for inactivity while still charging $15/month, and steadfastly refuse to refund