Ai Agents

Introduction Most of what we learned in the Internet era is no longer compounding. DAU is losing relevance. SaaS is no longer the growth engine it once was. The attention economy is in structural decline. The classic path from tools to platforms is breaking down. The term “AI application” no longer describes what is actually being built. Network effects. Communities. Platforms. SaaS. Applications. Attention economy. These concepts once formed a shared framework for understanding technology and business. We used them to design products, explain strategy, and communicate with investors. But more and more often, it becomes clear that the world these concepts describe is no longer the center of gravity. Not because the Internet suddenly disappeared, but because its core assumptions are no longer where growth comes from. The Internet era was built on one fundamental premise: Humans are the users of software. That premise is now eroding. A new one is taking its place: Agents are becoming the primary operators of software. This is not a sudden collapse. It is a gradual handover. ...

Introduction: Agents Are at Their DOS Moment In 2025, AI agents are exploding in capability. Tools like Claude Code can write code, run tests, fix bugs, and autonomously complete complex engineering tasks. For many people, this feels like the second major shift since ChatGPT first appeared. But if you look closely at how today’s agents actually operate, a quieter and more uncomfortable truth emerges: Their foundations are still extremely primitive. Most agents today manipulate your file system and terminal directly. There may be confirmation prompts or guardrails, but the underlying model remains trust-based, not isolation-based. Safety depends largely on the agent behaving well. This should feel familiar. It closely resembles DOS-era computing in the 1980s. DOS worked. You could write programs, edit files, and build real software. But it lacked nearly everything we now associate with a modern operating system: No memory protection No true multitasking No standardized device abstraction Applications talked directly to hardware. Developers were responsible for everything. AI agents are standing at the same starting line today. What took traditional computing nearly three decades—from DOS to Unix, Windows, and modern kernels—will likely replay in a much shorter window for agents. ...