Modern LLMs face several fundamental challenges when deployed as agents:
Limited Context Windows: Fixed token limits restrict information processing capacity
Memory Management: Difficulty balancing active context vs. long-term storage
Relevance Determination: Challenges in identifying the most pertinent information
Information Organization: Need for optimal structuring of contextual data
These limitations create bottlenecks for complex, multi-turn interactions where agents must maintain coherent conversations while accessing relevant historical information. As agents become more sophisticated, effective context management becomes the determining factor between a functional system and one that can truly understand and respond to complex, evolving user needs.
Learn how to solve these issues in this episode of Encyclopedia Autonomica
