AI agent memory is not a hidden capability of the language model, but an external system for storing, retrieving, and updating context. It allows the agent to continue working between sessions, take user preferences into account, use accumulated facts, and avoid repeating the same mistakes. A practical architecture…
Short answer: LLM Wiki does not replace RAG and does not guarantee 100% accuracy. But for a small core of critically important knowledge — regulations, contracts, technical documentation, and complex research — a connected semantic map can be more reliable than naive RAG with mechanical text chunking.…
In short: an AI agent retains context not because it constantly keeps the entire conversation, documents, and instructions in memory. A reliable architecture separates operating rules, process state, and knowledge base search. The agent receives only the data needed for the current step, and then…
