How we handle LLM context window limits without losing conversation quality

Every developer building on LLMs hits the same wall eventually. Your chatbot works beautifully for the first 10 turns, then starts forgetting things. Your agent ran a 30-step workflow and lost track of the original goal halfway through. Your RAG system stuffed so much context into the prompt that response quality dropped. This is the context window problem, and it does not go away by switching to a model with a bigger window. We learned this the hard way while building an AI assistant for a tra...