When you use an AI agent, the more contextual data the agent has about the job, the better it will perform.



But agents don’t have much memory, since the large language models (LLMs) they depend on are stateless. When their memory runs out, the agent glitches out, hangs up, or spews out nonsense. Tactics like truncating or compacting agent...