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    Ts Floyd
    Ts Floyd@ts_floyd1mo
    💭AI💭Tech
    Andrew Ng Graph Engineering PDF

    @ts_floydAndrew Ng just released a 12-page PDF on 'Graph Engineering' for multi-agentic systems. It covers 4 design patterns: Reflection (add a critic for 10-30% quality lift), Tool Use (execute code, search web, query DB to stop hallucination), Planning (write a structured plan and reroute on tool failure), and Multi-Agent (split roles like coder, reviewer, tester). The key idea: graph architecture externalizes shared state so agent loops can persist overnight. Based on his courses and DeepLearning.AI curriculum.

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    Andrew Ng Graph Engineering PDF

    Foto de @ts_floyd· Jul 25, 2026· AI

    Sobre esta foto

    The image is a document page with text and a diagram. The diagram shows a user interacting with an Architect Agent, Tech Lead Agent, and Developer Agent, all connected to a Knowledge Graph. The text discusses "Graph Engineering for Multi-Agentic Systems: The Andrew Ng Playbook" and is based on Andrew Ng's courses and DeepLearning.AI curriculum. The mood is academic and informative. A notable detail is the DeepLearning.AI watermark at the bottom left. ON-SCREEN TEXT: Full Course From Scratch · 2026 Working Note on Agentic AI Practice Graph Engineering for Multi-Agentic Systems: The Andrew Ng Playbook Based on Andrew Ng's courses, presentations, and the DeepLearning.AI curriculum Including the July 2026 Agentic Knowledge Graphs course (DeepLearning.AI + Neo4j + Google ADK) Independently compiled, July 2026 — not affiliated with or endorsed by Andrew Ng or DeepLearning.AI User Architect Agent planning + reflection Tech Lead Agent

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    Foto
    Ts Floyd
    Ts Floyd@ts_floyd1mo
    💭AI💭Tech
    Andrew Ng Graph Engineering PDF

    @ts_floydAndrew Ng just released a 12-page PDF on 'Graph Engineering' for multi-agentic systems. It covers 4 design patterns: Reflection (add a critic for 10-30% quality lift), Tool Use (execute code, search web, query DB to stop hallucination), Planning (write a structured plan and reroute on tool failure), and Multi-Agent (split roles like coder, reviewer, tester). The key idea: graph architecture externalizes shared state so agent loops can persist overnight. Based on his courses and DeepLearning.AI curriculum.

    Ver publicación original

    Andrew Ng Graph Engineering PDF

    Foto de @ts_floyd· Jul 25, 2026· AI

    Sobre esta foto

    The image is a document page with text and a diagram. The diagram shows a user interacting with an Architect Agent, Tech Lead Agent, and Developer Agent, all connected to a Knowledge Graph. The text discusses "Graph Engineering for Multi-Agentic Systems: The Andrew Ng Playbook" and is based on Andrew Ng's courses and DeepLearning.AI curriculum. The mood is academic and informative. A notable detail is the DeepLearning.AI watermark at the bottom left. ON-SCREEN TEXT: Full Course From Scratch · 2026 Working Note on Agentic AI Practice Graph Engineering for Multi-Agentic Systems: The Andrew Ng Playbook Based on Andrew Ng's courses, presentations, and the DeepLearning.AI curriculum Including the July 2026 Agentic Knowledge Graphs course (DeepLearning.AI + Neo4j + Google ADK) Independently compiled, July 2026 — not affiliated with or endorsed by Andrew Ng or DeepLearning.AI User Architect Agent planning + reflection Tech Lead Agent

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