AI Memory

AI memory allows models and agents to recall past interactions, adapt over time, and reason more effectively. We examined the most popular LLMs' ability to store information in both long-term and short-term memory, along with their context window capabilities.

AI Memory: Most Popular AI Models with the Best Memory

AI MemoryDec 4

AI models can remember earlier parts of a conversation, but their memory capacity varies wildly. Interestingly, smarter models often have worse memory. We tested 23 popular large language models to see which ones actually remember information during long conversations.

AI MemoryDec 1

Best LLMs for Extended Context Windows

We analyzed the context window performance of 22 leading AI models by testing them using a proprietary 32-message conversation that includes complex synthesis tasks requiring information recall from earlier in the conversation. Our findings are interesting. Smaller models often beat their larger counterparts, and most models fail well before their advertised limits.

AI MemoryNov 26

AI Apps with MCP Memory Benchmark & Tutorial

We tested memory tools to find out which ones actually work best for AI agents. Using LangChain’s ReAct Agent, we connected four different Model Context Protocol (MCP) memory servers and measured their performance in real scenarios. Beyond benchmarking, we built a working demo that connects Claude with Cursor through OpenMemory MCP.

AI MemoryNov 26

Cognitive Agents: Creating a Mind with LangChain

A cognitive agent isn’t just a chatbot responding on command; it’s a system that perceives, reasons, and adapts as its environment changes. AI agent memory capability helps AI agents to keep track of what’s happening now, what happened before, and which pieces of information are worth carrying forward. Without this, every conversation becomes a blank slate.