Mem0
Open-source persistent memory layer for LLMs
Episodes
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#4786: Markdown vs Vectors for Agent MemoryWhy coding agents need two kinds of memory — and why mixing them creates a sync nightmare. -
#4457: OpenViking: A Filesystem for AI Agent MemoryOpenViking unifies memory, RAG, and skills into a browsable filesystem for AI agents — no vector database abstraction needed. -
#2936: Why AI Still Can't Really Teach You to CodeCode generators ship code. Real tutors build understanding. Why the gap is bigger than you think. -
#2755: How to Build AI Memory That Actually WorksStop jumping to conflict resolution. The real challenge is getting data in and out cleanly. -
#2677: Memory Layers for AI Agents: SaaS vs Self-HostedZep, mem0, Letta, Graphiti, Cognee — which memory layer should you commit to for your AI agent? -
#2206: What Actually Works in AI MemoryMost AI memory systems are just vector databases with similarity search. We break down what mem0, Zep, and Letta are actually doing—and why benchma... -
#2204: Memory Without RAG: The Real Architecturemem0, Letta, Zep, and LangMem solve agent memory differently than RAG. Here's what's actually happening under the hood. -
#2010: Building Better AI Memory SystemsWe obsess over AI inputs but treat outputs like Snapchat messages. Here's why that's a massive blind spot. -
#1834: Owning Your AI Memory: The Data Exit StrategyWhy your AI remembers your coffee order but forgets your son’s name—and how to build a portable, federated memory layer you actually own. -
#144: AI Memory vs. RAG: Building Long-Term IntelligenceExplore why AI needs a "diary" and not just a "library" as we dive into the architectural differences between RAG and long-term agentic memory. -
#30: Which AI Tools Will You Still Use Next Year?RAG vs. Memory: Are you building resilient AI? Discover the crucial difference between these two foundational pillars.