TL;DR: Every leap in LLMs, from GPT-1 to today's agents, came from changing one thing: what the model is trained to do. Next-token prediction gave models knowledge. Post-training made them assistants. Reinforcement learning made them reason. Tools made them agents. Underneath it all, the real engine is data designed to teach the right objective. Every few weeks, a new LLM launches and the feed calls it a revolution. Taken one at a time, the launches look like noise.
