AJ

Most engineering processes were designed around a simple loop: a developer picks up a ticket, writes code, opens a pull request, and moves on. That assumption is breaking. An engineer can now orchestrate multiple AI agents, generate several implementations, discard most of them, review hundreds of lines of code, run experiments, and spend their time deciding what should exist rather than typing it.

I saw this shift while building AI-native systems for enterprises at 4good AI and leading a team of developers. The bottleneck is moving from producing code to directing, validating and integrating it.

A few years ago, I read the book The Four by Scott Galloway.

The book, published in 2017, focused on the four companies that dominated the market at the time: Amazon, Apple, Facebook (now Meta), and Google.

A few days ago, I read a post on Reddit saying that if you don t reach 200 users for your tool in the first month (in this particular case, the guy was talking about a Chrome extension), then your tool is no good and you should move on.

I was scared for a moment because I definitely don t meet this with my extension (now I m somewhere around 75 users in 5 weeks).