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    Ts Floyd
    Ts Floyd@ts_floyd3mo
    💭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_floyd3mo
    💭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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    bad visual H3 Image3bad visual H3 ImageANSWR Moises AriasANSWR Moises AriasANSWR Moises Arias horror filmANSWR Moises Arias horror filmAbandoned PC Gamer Nvidia AI bubble2Abandoned PC Gamer Nvidia AI bubbleThanksgiving Turkey Drop feature2Thanksgiving Turkey Drop featureNatura's Interface controls Claude Code via RingNatura's Interface controls Claude Code via RingAI image model comparisonAI image model comparisonAI race shifts to power and permitsAI race shifts to power and permitsfrontier AI operational counterintelligencefrontier AI operational counterintelligenceInkbox AI agents with independent resourcesInkbox AI agents with independent resourcesRing Drone Cam and Ring Rover Cam2Ring Drone Cam and Ring Rover Cam