18 minutesAWS re:Invent 2025 - Implementing Human-in-the-Loop Controls for Multi-Agent AI Systems (CNS428)
See how approval gates can be implemented as explicit workflow checkpoints rather than informal manual review after something goes wrong.
Prompt Engineering. A focused walkthrough of Microsoft's GraphRAG — entity extraction, community summaries, query-focused summarization — set up on a local machine with cost notes. Watch it for the graph-RAG section of the article specifically; the cost discussion is the part most write-ups skip.
Setup commands and costs can drift, but the architecture is useful. Recalculate current token costs and validate whether graph construction is justified before adopting this pattern.
Understand the Microsoft-style GraphRAG flow: entity extraction, communities, summaries and query-focused synthesis.
Know why plain vector search can miss relationship-heavy questions.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
18 minutesSee how approval gates can be implemented as explicit workflow checkpoints rather than informal manual review after something goes wrong.
4 minutesUnderstand why multilingual embeddings matter for private internal search and where local retrieval can reduce data-exposure risk.
17 minutesSet up a multi-agent coding workflow with explicit review boundaries so generated changes stay small, tested and owned.
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