small context windows + no persistent memory = hard to solve multi-step or long-horizon tasks. For those who have built serious local setups: How do you give your model persistent memory? Vector DBs? RAG? Fine-tuned adapters? Some kind of external state management loop? Or a custom “memory module” you wrote yourself? I’m looking for practical approaches that let a local model remember past steps, keep working on long tasks, and behave more like an agent with continuity.