Your Agent Doesn't Need a Bigger Model

Thanks to Redis for making this video possible. Your AI agents don't fail because the model isn't smart enough. They fail because of the context you give them. In this video I break down why context engineering, not prompt engineering, decides whether agents work in production, using findings from Redis's State of Context Engineering report, then wire up a live coding agent with cross-session memory using the Redis Agent Memory Server. Read the State of Context Engineering report: https://fandf.co/4ixN2Zo Agent Memory: https://fandf.co/4xtvkdm #AI #Agents #ContextEngineering #Redis #AIMemory My voice to text App: whryte.com Website: https://engineerprompt.ai/ RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/courses/rag Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 00:00 Why Agents Really Fail 00:50 Three Context Failure Modes 02:24 Context vs Prompt Engineering 03:26 Four Rules of Great Context 04:48 Why Teams Get Stuck 05:39 Memory Layers and Compounding 07:27 Redis MCP Demo