Agent Context Window Management: Long-Running Agents

Long-running agents need context management; ignoring it produces failures or runaway costs.

What AI does well here

• Design summarization checkpoints that compress context as it grows
• Maintain key state in structured form (not pure prose) for reliability
• Use external storage for information that doesn't need to be in active context
• Test long-running behavior (most agents are demoed for 5 minutes, deployed for hours)

What AI cannot do

• Stuff infinite context into the model
• Substitute long context for actual state management
• Eliminate the cost growth of long-running agents

Practice this safely

Use a small project example from your own work. The useful move is to compare the AI's draft against your goal, sources, and constraints before you trust it.

1. 1Ask AI to explain context management in plain language, then underline anything that sounds uncertain or too broad.
2. 2Give it one detail from "Agent Context Window Management: Long-Running Agents" and ask for two possible next steps plus one reason each step might be wrong.
3. 3Check long-running agents against a trusted source, teacher, adult, expert, or original document before you use it.