Inside OpenAI’s Mission to Build AI That Can Do Anything for You Shortly after joining OpenAI in 2022, researcher Hunter Lightman watched in awe as ChatGPT exploded into the global spotlight. While others celebrated the viral success, Lightman was quietly leading a team focused on a far more ambitious goal: teaching AI to solve high school math competitions. That effort, known as MathGen, would become a cornerstone of OpenAI’s breakthrough in AI reasoning — the engine behind the next generation of intelligent agents. Today, OpenAI’s models are capable of tackling complex problems once thought beyond AI’s reach. One model recently earned a gold medal at the International Math Olympiad, a feat that underscores a dramatic leap in reasoning ability. This progress is not just about math — it’s a critical step toward realizing OpenAI’s long-held vision: general-purpose AI agents that can autonomously perform any task a human can, from coding to shopping to planning trips. The journey began years before the public knew about it. While ChatGPT was a serendipitous success born from a research experiment, the development of AI agents has been a deliberate, years-long effort. At the heart of this push is a powerful training technique called reinforcement learning (RL), which teaches AI systems to learn from feedback in simulated environments. Inspired by milestones like DeepMind’s AlphaGo, OpenAI began exploring how RL could be used to create AI that doesn’t just generate text, but thinks and acts. By 2023, OpenAI combined large language models with RL and a novel method called test-time computation — giving models extra time and resources to plan, verify, and refine their answers. This led to the emergence of “chain-of-thought” reasoning, where AI models begin to mimic human-like thought processes, retracing steps, catching errors, and even showing signs of frustration. “It really felt like reading the thoughts of a person,” said researcher El Kishky. The result was a system dubbed “Strawberry,” which laid the foundation for o1 — OpenAI’s first true reasoning model. Released in late 2024, o1 stunned the tech world. Within months, the 21 researchers behind it became the most coveted talent in Silicon Valley. Meta recruited five of them, offering multimillion-dollar packages, with one, Shengjia Zhao, named chief scientist of Meta’s new superintelligence unit. This success was not accidental. OpenAI’s strategy centered on two new levers: scaling computational power during training and allowing models more time to reason when answering questions. “We’re not just improving models — we’re redefining how they work,” said Lightman. The company responded by forming a dedicated “Agents” team led by Daniel Selsam, later integrated into the broader o1 project. Under the leadership of Ilya Sutskever, Mark Chen, and Jakub Pachocki, OpenAI poured resources into this vision — a move made possible by its singular focus on advancing artificial general intelligence (AGI), not just marketable products. Critics debate whether these models truly “reason” in the human sense. But OpenAI researchers argue that the definition matters less than the outcome. “If the model does hard things, then it’s doing whatever it needs to do to succeed,” said Lightman. For AI2 researcher Nathan Lambert, the comparison is apt: just as airplanes fly without flapping wings, AI can reason without mimicking the human brain — and still achieve remarkable results. Now, the frontier is shifting from objective tasks like math and coding to subjective ones: online shopping, travel planning, personal decision-making. Current agents still struggle here — making slow, silly mistakes. But OpenAI is working on new reinforcement learning techniques that can train AI on tasks without clear right-or-wrong answers. Noam Brown, a key researcher on the IMO-winning model, revealed that OpenAI is using systems where multiple AI agents collaborate, explore ideas in parallel, and converge on the best solution — a method gaining traction at Google and xAI. These advances could power GPT-5, which OpenAI hopes will cement its lead in the race for the most capable AI agent. But the company isn’t just chasing performance — it wants simplicity. “We want agents that intuitively understand what you want, without you having to specify every detail,” said El Kishky. The future vision: a ChatGPT that doesn’t just answer questions, but acts on your behalf across the internet, flawlessly and autonomously. Yet OpenAI is no longer alone. Google, Anthropic, Meta, and xAI are closing in fast. The real question isn’t just whether OpenAI can deliver its vision — it’s whether it can do so before its rivals do. The race is on to build the first true AI agent — not just smart, but capable of doing anything for you. And OpenAI, with its relentless focus on reasoning, may be leading the charge — but the finish line is closer than ever.