Beyond RAG: Why Knowledge Engineering Becomes the Real Moat in the Agent Era

1. 1Study the limitations of RAG in providing context to AI agents
2. 2Explore Knowledge Engineering principles to improve agent decision-making
3. 3Design a memory architecture for agents to store and retrieve relevant information
4. 4Implement a Knowledge Engineering framework to teach agents to learn from data
5. 5Evaluate the performance of agents with and without Knowledge Engineering

Developers, data scientists, and product managers working with AI agents can benefit from understanding the importance of Knowledge Engineering in creating more effective and informed agents

💡 Knowledge Engineering is essential for creating agents that can learn, reason, and make decisions effectively

🤖 Agents need more than just RAG to make informed decisions. Knowledge Engineering is key! #AI #Agents