For the first few years of the generative AI boom, the public conversation focused almost entirely on general-purpose chatbots. The dominant question was simple: which model is smartest? People compared headline names, benchmark scores, coding ability, writing style, and reasoning performance. It made sense at the time because general models were new, exciting, and rapidly […]
A lot of people hear the term “AI-native” and assume it just means a company that uses ChatGPT a lot. That is not what it means. Plenty of businesses use AI as a feature, an add-on, or a productivity boost. An AI-native company is different. It is built from the ground up around the assumption
For most of the software era, digital tools became more specialized over time. One product handled email. Another stored notes. Another managed projects. Another organized calendars. Another created documents. Another searched the web. Another handled automation. Users gradually accepted a life of endless tabs, subscriptions, notifications, and context switching because that was simply how modern
For many people outside the technology industry, the phrase open vs closed AI models sounds like a debate reserved for engineers and researchers. In reality, it may become one of the most important business and policy questions of the decade. The outcome will influence who can build with artificial intelligence, how expensive it becomes, and
A lot of Western coverage of China’s technology rise still makes the same mistake. It treats each new push as though it appeared out of nowhere. One year the story is electric vehicles. Then it is batteries. Then it is AI. Then it is chips. Then it is drones, industrial software, or robotics. Each topic
Artificial intelligence has a talent for making weak habits feel efficient. That is part of what makes this moment so powerful and so dangerous. AI can summarize, rewrite, brainstorm, code, organize, translate, answer questions, and clean up messy work in seconds. For people buried under mental clutter or repetitive tasks, that feels almost miraculous. The
For a while, the AI developer market looked deceptively simple. A company had a strong model, exposed it through an API, and developers used that model to write code faster. That was the basic story. The competition looked straightforward too. Which model was smartest? Which one wrote cleaner code? Which one solved more benchmark tasks?
For years, the playbook for search felt relatively stable. You published content, targeted keywords, earned links, improved technical SEO, watched rankings, and hoped Google would reward the effort with steady organic traffic. It was never easy, but the rules felt legible. Brands knew where they were fighting, what the scoreboard looked like, and roughly how
For a while, vibe coding had a reputation problem. It was fun, flashy, and sometimes genuinely impressive, but serious developers often looked at it like a toy. You could prompt an AI tool and get a slick interface, a polished landing page, or a prototype that looked far better than something thrown together in a
For the past couple of years, the public face of artificial intelligence has been the demo. A chatbot that sounds eerily human. An image model that makes cinematic scenes in seconds. A coding tool that spits out an app faster than a junior developer could wire up a login page. That phase was important because
