Agent memory is why your AI agent forgets what it did ten tool calls ago, and a bigger context window does not fix it.
In this video we break down what agent memory actually is and why context is not the same thing. We walk through the three tricks the field leaned on before dedicated memory systems existed, RAG, summaries, and profiles, and where each one quietly falls apart. Then we get to the part most people skip: memory is not storage, it is a loop, and getting that loop right is what separates today's chatbots from the long-horizon agents coming next.
? What you'll learn:
1️⃣ The real difference between context and memory
2️⃣ Why RAG, summaries, and profiles each break down as tasks get longer
3️⃣ The memory loop: what an agent should write, what it should skip, and when to load it back
4️⃣ Why long-horizon agents need to remember experience, not just facts
? Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX
⏰ Timestamps:
00:00 - Why Memory became a problem for agents
00:51 - Context vs Memory
01:55 - RAG, Summaries, and Profiles
02:40 - Where each workaround breaks down
03:25 - Why a bigger context window is not the fix
04:00 - Memory is a Loop
? Subscribe for more AI engineering and agent design
#AgentMemory #AIAgents #LLM #ContextWindow #RAG #AgenticAI #LongTermMemory #MemoryManagement #AIEngineering #LLMAgents #ContextEngineering #kodekloud