AI agents lose performance over long conversations because their context window fills with chat history, tool calls, and metadata, forcing the model to hallucinate. Dynamic pruning fixes this: have the model summarize its state, then start fresh with that summary injected to reset the window.
Have you ever noticed your AI agents get dumber the longer your sessions go? By the way, that has nothing to do with your prompting. That's a technical problem called context prompt. You see, every foundation model has a context window. Think of it like your own brain. How much stuff can you possibly remember? What do you remember eating for dinner last Tuesday? Or remember from second grade in English class? You can only hold so much context in your brain at one time. The agent has chat history, tool calls, and metadata. All these things are fighting for space in that context window, and eventually Eventually the noise-to-signal ratio gets so high that the AI starts hallucinating just to cope. So stop treating the context window like a garbage bin. Instead, use dynamic pruning. It's really simple. Ask the AI to summarize the current state, copy that summary, and inject it into a fresh session. This helps the model stay focused and provide relevant output. That's easy, bare-bones context management. Comment context for the full technical breakdown.
