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All digests tagged Knowledge Graph
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Learn how to build a self-improving company by turning agent failures into reusable skills. We discuss using MCP as the distribution layer and creating an organizational flywheel that captures hard-won knowledge.
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Agent memory is solved, but shared learning across agents is not. The solution requires an agent-native persistence layer (Meko) to promote private memories into governed, shared data packs.
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This guide details building LLM knowledge bases by transforming raw notes into structured wikis and graphs. The pipeline uses voice dictation for capture, agents for enrichment (tagging, linking), and cloud automation for scheduled updates.
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The talk outlines how building robust AI agents requires moving beyond simple LLM calls. Key guardrails include whitelisting tools, using Knowledge Graphs over RAG, and enforcing structured citations.
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CQ (Stack Overflow for agents) standardizes knowledge sharing across AI agents. It allows lessons learned from solving novel problems to be captured as Knowledge Units (KUs), preventing repeated mistakes in automated workflows.
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