14 articles
Master the logic of Linux memory allocation. Learn why 'Free RAM' is actually a waste. Understand the 'Swappiness' parameter and how it affects performance. Learn to handle the 'OOM (Out of Memory) Killer'—the kernel's final tool for survival.
Memory in the Cloud. How to maintain conversation context across multiple API requests.
Breaking the Amnesia. Understanding why LLMs are stateless and how we provide 'history' to simulate a conversation.
The Raw Transcript. Using the simplest memory type to keep a literal record of every message in a conversation.
Dense context. How to use an LLM to periodically summarize a conversation to keep the memory footprint small.
Production State. How to move your memory from local RAM to persistent databases for multi-user applications.
Hands-on: Build a persistent chatbot that remembers your name across different CLI sessions.
The Long-Term Memory. Learning how to use Pinecone, Chroma, and PGVector to give your agents a massive knowledge base.
The two speeds of learning. Understanding conversation buffers vs vector databases.
Connecting the threads. How to implement chat history and windowed memory in LangChain agents.
Choosing your memory model. When to build agents that remember the past vs agents that treat every event as new.
The math behind LLM files. Understanding how many GBs you need to store and run your favorite models.
How much can the AI remember? Understanding the relationship between context windows and RAM usage.
How Ollama handles memory. Understanding why the 'second' run is always faster than the 'first'.