How AI is Getting Smarter

For years, AI was either good at thinking (Reasoners) or doing (Agents). Now, those two have joined forces, and the result is mind-blowing—AI that can research like a human but at super-speed. OpenAI’s Deep Research is the first glimpse of this, and it’s going to change everything. The internet as we know it is shifting, and soon, AI won’t just answer your questions—it’ll actually think about them like a real researcher.

AI Thinks Before It Speaks (Finally!)

Old-school AI chatbots? They just blurted out the next word without much thought. But now, Reasoners actually stop and think before answering. Imagine trying to solve a hard math problem. If you rush, you’ll mess up. Reasoners don’t rush. They generate “thinking tokens” first, which makes them way smarter at solving complex problems.

This ability isn’t just cool—it’s a game-changer. The GPQA Test (fancy name for a hard quiz) shows how much AI is improving. Even PhDs get only 34% right outside their specialty. But the latest Reasoners, like OpenAI’s o3, are now tackling these problems like pros—scoring 85% on the same test, more than doubling expert human performance. That means AI can now solve problems that even trained experts struggle with.

AI Gets Off the Couch and Starts Doing Stuff

If Reasoners are the brains, Agents are the hands. They get tasks done—like an AI assistant that books flights, edits videos, or organizes files. OpenAI’s Operator is a top-tier example. But here’s the problem: it's great at some tasks but struggles with anything tricky. When asked to read a blog, create an image, and download it, it nailed the first steps but totally failed at the last one.

Why? Because AI still isn’t great at handling unexpected obstacles. That’s why narrow agents—specialized AIs that crush one specific task—are already proving to be far more useful. And that’s exactly what Deep Research does.

Deep Research: AI as a Research Nerd

Deep Research is a laser-focused research AI that doesn’t just find articles—it thinks about them. When asked, “When should startups stop experimenting and start scaling?” it didn’t just throw out a bunch of random links. Instead, it asked smart follow-up questions, dug into top academic sources, and wrote a 3,778-word report with real citations.

And guess what? The sources were real. No made-up stuff. It even highlighted the exact quotes in the papers. That’s a game-changer. Imagine an AI that doesn’t just summarize Wikipedia but analyzes real academic papers and gives you insights as if you had a team of experts working for you.

Google vs. OpenAI: Who Wins?

Google also has a product called Deep Research (awkward), but it’s more like a solid high school essay—lots of sources but not much depth. OpenAI’s version? Feels like an early PhD student. It’s not perfect, but it’s really close.

Google’s AI tends to surface a massive pile of sources, but OpenAI’s AI actually engages with them, breaking down conflicts, highlighting key arguments, and making real academic connections. It’s the difference between having a librarian hand you a giant stack of books and having a researcher actually summarize the best parts for you.

The Future: AI That Actually Works for You

Right now, we’re in the “specialist AI” era—where AI researchers are smarter than humans in specific areas. But the goal? General-purpose AI that can do everything.

Think about it: Today, we still have to search for information, cross-check sources, and manually filter through results. In the near future, AI won’t just find answers—it’ll do the research for us. Imagine asking an AI to summarize the latest climate science, draft a compelling argument for a debate, or even analyze historical trends in seconds. That’s where we’re headed.

We’re not there yet, but Deep Research proves we’re on the way. Once AI can think, research, and act seamlessly, it won’t just change how we use the internet—it’ll redefine what knowledge means in the first place.