I got a lot of pushback for saying that one product manager and one engineer can now be the entire team. Now @danshipper has a name for it: the pirate and the architect. I ain’t crazy after all. :-)

😆

AI FOMO is real. Every week brings something new. Every launch makes you feel you’re falling behind. Every new opportunity makes you question your direction. You chase everything and finish nothing. The people who stay focused will win, while everyone else keeps getting distracted.

My next experiment: “Inbox Development.” What if every requirement arrived like an email? Each engineer has an inbox. A requirement from the PM comes in. She forwards it to her coding agents. A few hours later, she replies: “Done. Tested. Deployed.” We got used to replying to emails within hours. What if we got used to shipping requirements just as quickly? The goal: Inbox Zero.

We told our developers, “No more hand-written code,” six months ago. Today, 99% of our code is written by AI. Now Epic Games is telling its teams the same thing - and getting the same pushback.

Since this post took off, I looked at Instinct, the AI assistant my whole family uses. It was started roughly a year ago. Last month, it raised $1 billion at a $10 billion valuation. Team size: fewer than 20. From what I could find, for every engineer, there is roughly one non-engineer across the product, strategy, and operations. One person deciding what to build for every person building it. The 1:1 team is already here. At least, that is how it looks from the outside. Only @noahrshinn can confirm :-)

Everyone has to market themselves. Even APIs. An MCP server is basically an API’s marketing brochure for agents :-)

ALL CODE IS NOW OPEN SOURCE Not legally. Practically. For a long time, we assumed that compiling code and hiding the source code protected it. AI changes this. AI can take a binary, decompile it, and reconstruct readable source code that behaves like the original. It may not reproduce the exact source file you wrote. But it does not need to. All code you ship is now effectively open source. Open source may have won without everyone agreeing to open-source their code.

In the new AI world, we need a lot more product managers. Perhaps even one product manager for every engineer. The old ratio of one PM to five engineers assumed that development was the bottleneck. That is no longer true. AI is making implementation fast and increasingly straightforward. What remains difficult is deciding what to build, understanding who needs it, defining how it should work, and prioritizing ruthlessly. When execution becomes cheap, judgment becomes the bottleneck. Anyone else thinking this way? Would love to compare notes.

Woke up to this message: my domain registrar had closed my account. After some digging, I found the culprit. My agents had been trying to buy a LOT of .si domain names. Apparently, they had smelled an opportunity. Further digging revealed the real masterminds: my kiddos. After Trump’s speech rebranding AI as “Super Intelligence,” they had instructed the agents to hunt for .si domains. The agents couldn’t complete the purchases. But they did build an Excel sheet with hundreds of .si domains, and the kiddos were adamant that I “invest.” I tried explaining why this was a bad idea. In vain. I finally conceded and allowed them to buy 25 domain names. Just another regular morning in my household. 😄

Okay, allow me to brag a little today. Please excuse me. :-) Today, Silq is the leading embedded-finance platform in Saudi Arabia. And I may have been the first to conceive and patent embedded checkout, an early precursor to today’s embedded finance. Here is that story. In 2008, paying through a third-party payment service such as PayPal typically meant leaving the merchant's website. Customers clicked a payment button, were redirected to the payment provider's website, authenticated themselves, gave the payment info, and then returned to complete the purchase. I was working on Amazon Pay at that time and thought there had to be a better way. My idea was to embed checkout within the merchant's website instead of redirecting the customer elsewhere. The payment provider should be able to present the checkout experience inside the merchant's page. Customers should be able to use their stored payment and shipping info, while their sensitive credentials travel directly to the payment provider and remain invisible to the merchant. I came up with two ways of achieving this. 1. Quick Checkout (U.S. Patent No. 10528931) The "Quick Checkout" architecture used provider-controlled components embedded within the merchant's page. Sensitive information went directly to the provider, rather than passing through the merchant. The architectural principle eventually became standard across modern payments: - Braintree Hosted Fields uses provider-controlled iFrames, so raw card information never reaches the merchant's server. - Stripe Elements uses Stripe-hosted components embedded within the merchant's checkout, with sensitive card details going directly to Stripe. - Adyen similarly embeds provider-managed payment experiences within merchants' websites. 2. Instant Checkout (U.S. Patent No. 9324098) Instant Checkout took the idea further. The payment provider could recognize the customer through its cookie, retrieve the customer’s default payment and shipping information, and deliver a one-click experience within the merchant’s website. That idea also grew into a major category: - Bolt created a cross-merchant shopper network offering embedded one-click checkout. - Shop Pay made stored payment and shipping info reusable across Shopify merchants. - PayPal also allowed customers to complete purchases without leaving the merchant experience. Embedded checkout brought payments into the purchasing journey. Embedded financing brings capital into the same journey. Both reflect the same conviction: services should appear naturally at the moment of need - not force customers into a separate process.

Context switching is becoming a key skill in the AI era. AI will slow you down if you work on one task at a time. It is like the mainframe days again. You give it a task, then sit and wait for the result. You may be slower than you were before AI. The skill that matters now is not doing one task faster. It is switching between several tasks, so you can stop waiting for one agent and run five at once.

So I forwarded the Instinct message to my wife and she is now banning my AI assistants 😆

See? I told you the Claude team was watching 😄

Yesterday, I complained that Claude takes over my browser while ChatGPT browses inside the chat. Today, Claude launched a built-in browser inside Cowork. Clearly, they built it overnight after reading my post. 😄

A clarification, because I think the phrase landed differently than I intended. I said “No more tech teams.” What I meant: “No more teams.” Yeah, still probably radical. A single engineer managing an agent swarm is the team. She is no longer an individual contributor. She is an engineering organization. One senior engineer can mentor several such one-person teams.

Lately, Claude, especially Fable, has not been good at web research for me. It keeps hitting firewalls and bot checks, and its computer use interferes with my browsing. ChatGPT somehow rarely gets blocked, and browses right inside the chat. So most of my web research has moved to ChatGPT. Claude now just reviews what ChatGPT found.

We have successfully adopted "No more typing of code." We are halfway to "No more code reviews." Now I am pushing the next idea: "No more tech teams." One engineer per team, managing an agent swarm. One senior engineer mentoring several such teams.

Back to O'Reilly after two decades. New animal on the cover, same yellow highlighter.

Weird. So if someone writes an entire document with AI and then rephrases the text alone, there is no watermark. Someone writes it by himself and uses AI to just fix their grammar: watermarked as AI.