Retrieval-Augmented Generation

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The New Stack Amazon Bedrock Amazon Web Services MarkTechPost OpenAI GraphRAG

Monday, 5 October 2026

Connecting AI agents to enterprise knowledge

MIT Technology Review 1 week ago 25 ● 15 sources

Enterprise AI agents are being blocked by insufficient organizational knowledge, which leads to unreliable decisions and prevents many agent projects from reaching production. Only 34% of organizations’ agentic AI projects make it into production, and data fragmentation (55%) alongside knowledge/context gaps are major causes. The report urges organizations to build a knowledge layer and invest in retrieval infrastructure such as ingestion pipelines, AI-ready APIs, RAG, and knowledge graphs to improve scaling of agentic deployments.

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Enterprise AI AI Agents & Workflows Retrieval-Augmented Generation

Agents Don't Need Memory. They Need Documentation.

liao.gg 1 week ago 24

A memory plugin ecosystem for AI agents turns past chat transcripts into RAG snippets, retrieves the top 5 similar items on each prompt, and optionally searches more when the agent is unsure. The article says these systems store data like “10,000 embeddings in SQLite,” but it argues the result is unauditable and can surface stale or incorrect memories. Instead of adding more retrieval features, it proposes document-based “Markdown brain” memory that agents consult and update through a prompt→consult→build→update loop, with no vector database or embeddings.

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AI Agents Agentic Workflows Retrieval-Augmented Generation

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