AI Insights - Ep.7: Building Better Memory for Smarter AI Agents

AI Insights - Ep.7: Building Better Memory for Smarter AI Agents

This month on The Cisco AI Insights Podcast, hosts Rafael Herrera and Sónia Marques are joined by Cisco software engineer João Costa to explore Andrej Karpathy’s GitHub Gist on the LLM wiki pattern concept. It imagines how Large Language Models can move beyond one-off chat sessions and help build a persistent, interconnected knowledge base that grows and improves over time. The conversation examines how an LLM wiki turns raw sources such as meeting transcripts, research papers, websites, and project notes into structured markdown pages with cross-links between related concepts, creating something closer to a living digital brain than a static document store. João explains how tools like Obsidian can provide a clear window into this knowledge graph, while the LLM acts as a scribe that summarizes, curates, connects, and updates information for personal productivity, software development, research, and collaborative work. The episode also highlights the importance of linting, the ongoing process of detecting contradictions, removing stale details, and reducing hallucinated information before it spreads through the wider knowledge base. A special thank you to Andrej Karpathy for developing and sharing his GitHub Gist. To explore the Gist yourself, visit this link: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f

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