Imagine a world where AI not only learns but also designs its own curriculum. That's the intriguing premise behind AgentGen, a new framework that pushes the boundaries of Large Language Model (LLM) training. LLMs, like the ones powering chatbots and virtual assistants, are typically trained on massive datasets crafted by humans. But what if AI could take the reins and generate its own training environments and tasks? AgentGen explores this exciting possibility, allowing LLMs to construct their own learning experiences. This innovative approach addresses a key limitation in current AI training: the laborious and costly process of manually designing environments and tasks. AgentGen automates this process, using the power of LLMs to create diverse scenarios, ranging from simple to complex. Think of it as an AI teacher crafting custom lesson plans for its AI students. The system works in two stages. First, it generates environment specifications using an “inspiration corpus” of diverse text segments. This corpus sparks the LLM’s creativity, leading to a wide range of scenarios, like designing a healthy recipe book or navigating a virtual household. Second, AgentGen uses a bidirectional evolution method to create tasks within these environments. This method starts with randomly generated tasks and then evolves them in two directions: simplifying them to create easier exercises and complexifying them to create more challenging problems. This two-pronged approach ensures a smooth learning curve, allowing the AI to master both basic and advanced skills. The results are promising. When tested on a series of planning tasks, LLMs trained with AgentGen showed significant improvements in performance, even outperforming established models like GPT-3.5 in some cases. The implications are vast. By automating the creation of training data, AgentGen could drastically reduce the time and resources needed to develop advanced AI systems. It also opens doors for more personalized and adaptive learning experiences, where AI can tailor its own training to its specific needs and goals. While the technology is still in its early stages, AgentGen offers a glimpse into a future where AI not only learns but also shapes its own learning journey.