This invention discloses a method,
system, and computer-readable storage medium for real-time personalized
content generation, relating to the field of
artificial intelligence content generation technology. It constructs and continuously updates a real-time state base for interactive objects, forming a controlled context snapshot of the
current generation round based on this base. It jointly determines the target content's path location, single-generation
granularity, whether an intervention action is triggered, the
verification dimension after the current round's output, and the
verification triggering conditions. The target content for the current round is then generated. After output, process feedback and task progress results are collected, and the
verification results are combined to determine whether to continue generation, correct generation,
downgrade output, switch paths, or switch interventions. The process feedback, task progress results, verification results, and corresponding adjustment results are written back to the real-time state base for use in subsequent rounds. This invention is applicable to learning, training,
knowledge services, interest and skills guidance, task prompts, and other scenarios where content can be generated in real-time by
artificial intelligence.