Business
The biggest companies in the world are talking about AI agents. The smallest companies in the world are actually using them. Q1 2026 data tells a story that should surprise no one who has ever tried to get a purchase order approved at a Fortune 500: SMBs are leading AI
Business
Ben Broca runs a company generating $4.5 million a year. He has zero employees. Not "a lean team." Not "mostly contractors." Zero. His product, Polsia, is an AI co-founder platform. You give it a business idea, and it builds the product, fixes bugs, handles customer
AI Agents
OpenAI just announced they're merging ChatGPT, Codex, and their Atlas browser into a single desktop "superapp." Their VP of Applications, Fidji Simo, admitted in an internal memo that they were "spreading efforts across too many apps and stacks" and needed to simplify. In the
Business
When Mastercard — a company that processes 175 billion transactions a year — decides to build AI employees for small businesses, you stop calling it a startup idea. On March 10, Mastercard unveiled Virtual C-Suite: a collection of AI agents designed to serve as digital executives for SMBs. The first module is
Business
There are 30 million solopreneurs in the United States. They generate $1.8 trillion in annual revenue. And 81.9% of all U.S. small businesses have zero employees. That last number is the one that matters. The default mode of American business is not the ten-person startup or the
Trends
Somewhere in a data centre right now, an AI agent is placing a bet. Not a metaphorical bet on the future of technology — a real bet, with real money, on a prediction market. And it is probably winning. A CoinDesk investigation published last week found that 14 of the 20
Business
Every SaaS product you use was designed for a human. A human who clicks buttons, reads dashboards, fills out forms, and solves CAPTCHAs. That assumption is about to age very badly. AI agents are becoming the primary users of software. Not as a futuristic thought experiment — right now, today, at
AI Agents
The terms get thrown around interchangeably, and it's costing businesses real money. Someone tells you to "just add a chatbot," you spend three months building one, and then your customers complain it can't actually do anything. Or you deploy an AI assistant, expecting it
Business
The average company now uses 106 SaaS applications. Small teams with fewer than 200 people still manage 42. And every single one of those tools came with the same promise: save time, do more, work smarter. Then AI showed up, and the stack got worse. The Tool-Stacking Trap AI-native app
AI Employees
Here's a test I run on every AI tool before I trust it with real work: can it do something useful at 3 AM on a Tuesday while I'm asleep? Not "generate a response when prompted." Not "auto-reply with a template." Actually
AI Employees
Everyone asks the same question before hiring an AI employee: "But what can it actually do?" The honest answer is: not much on day one. And that's fine. Because the interesting part isn't what it does on day one. It's what happens
AI Employees
There is a freelancer in London who publishes a blog post every morning, sends 200 personalized cold emails a week, posts to LinkedIn and X daily, responds to customer inquiries within minutes, and delivers weekly analytics reports to her clients. She has no employees. No VA. No agency. Just herself