Part 1 of 3 — "Memory for AI agents" Deconstructing the long-term memory myth in LLM systems Article It's 3 AM. I'm on my third night debugging an AI agent. I'm standing in the kitchen with a mug of tea, staring at a diff, swearing quietly. The agent has confidently rewritten the auth function — based on a chunk that belongs to a branch that was deleted from the repo two months ago. The chunk lives in Qdrant. Its cosine similarity to my query is high. Top-1 in the retrieval. The agent honestly grabbed it, honestly stitched it into the prompt, honestly generated the "correct" patch. Against code from a different reality. I close the laptop and think: okay, I have RAG. I have vectors. I have long-term memory. I have everything every AI conference deck has been promising for the last two years. Why did my agent just propose a fix based on code that doesn't exist anymore? Because my agent doesn't have memory. My agent has search results with cosine instead of BM25.…