Context Engineering Explained: Context Filtering and Autonomous Context Engineering

Is it possible to reduce the amount of information entering the context from the very beginning?

Previous Articles:

• How AI Agents Work: The OpenClaw Case
• Context Engineering Explained
• A Core Technology Behind AI Agents （LLM Summary, Observation Masking & Memory）
• What to Do When Tasks an AI Agent Could Originally Complete Fail After Context Engineering
• Mechanisms for Deciding When to Compress Context

Contents:

1. Where Do All Those Tokens Come From?
2. Filtering: Loading Only What Is Needed
3. Filtering in the System Prompt
4. Letting the Model Perform Context Engineering by Itself
5. Context Stored on Disk

Where Do All Those Tokens Come From?

In the previous articles, we introduced several ways to compress context. However, you may have noticed something: these methods usually come into play only after the context has already become very long.

This is certainly one way to control context length. But we can take the question one step further…