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    Build Production AI Workflows with TypeScript and Temporal

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    2026年4月8日
    TechnologyCareer & Business

    Learn to build production AI workflows using TypeScript and Temporal. Master prompt versioning, LLM-as-judge evaluators, and secure, scalable orchestration.

    Build Production AI Workflows with TypeScript and Temporal

    Build Production AI Workflows with TypeScript and Temporalのベスト引用

    “

    The number one mistake that causes systems to fail in production is mixing non-deterministic I/O, like LLM calls, directly into your main logic. You must treat orchestration like a distributed systems problem, keeping your pure orchestration logic in Workflows while pushing all messy I/O into a dedicated Step layer.

    ”
    P

    Generated by Patrick

    質問を入力

    Build a TypeScript framework for production AI workflows. Separate Workflows (pure orchestration) from Steps (the I/O layer — LLM calls, HTTP, DB queries — each result cached for replay). Store prompts as version-controlled .prompt files with YAML and Liquid templates; swap providers in one line. Add LLM-as-judge Evaluators for quality scoring. Scale via Temporal for retries, replay, and parallel execution. Encrypt secrets with AES-256-GCM. Stack: TypeScript, Temporal, Vercel AI SDK, Zod.

    ホストの声
    Lenaplay
    Milesplay
    知識ソース
    Hands-on Machine Learning With Scikit-learn And Tensorflow
    Artificial Intelligence and Generative AI for Beginners
    Make your own neural network
    Artificial Intelligence and Machine Learning for Business
    Developing Backbone.js Applications
    ChatGPT for Dummies

    よくある質問

    This framework utilizes Temporal to manage production AI orchestration, ensuring workflows are durable, scalable, and reliable. By separating pure orchestration logic from I/O-heavy steps like LLM calls or database queries, the system can leverage Temporal’s replay and retry capabilities. This architecture allows developers to execute complex parallel processes while maintaining a clear state, making it ideal for high-stakes production environments where consistency is critical.

    LLM-as-judge Evaluators provide a sophisticated layer for quality scoring within your AI workflows. By using specialized LLM calls to evaluate the output of other models, you can automate testing and ensure high-quality results at scale. This approach integrates seamlessly with the Vercel AI SDK and Zod validation, allowing you to define strict schemas and scoring rubrics that maintain the integrity of your production AI applications.

    Prompts are managed as version-controlled .prompt files using YAML and Liquid templates, allowing you to swap providers with a single line of code without redeploying logic. For security, sensitive data and API keys are protected using AES-256-GCM encryption. This combination ensures that your AI prompts remain flexible and organized while your production secrets stay encrypted and secure against unauthorized access.

    Separating Workflows from Steps creates a clean boundary between orchestration logic and the I/O layer. Steps handle specific tasks like HTTP requests or DB queries, with each result cached for replayability. This design ensures that the core workflow remains deterministic and pure, which is essential for Temporal’s replay functionality. It also simplifies debugging and testing, as individual steps can be mocked or updated without affecting the overall orchestration flow.

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    "Feels effortless compared to reading. I’ve finished 6 books this month already."

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    注目の書籍要約
    Crucial ConversationsThe Perfect MarriageInto the WildNever Split the DifferenceAttachedGood to GreatSay Nothing
    人気のカテゴリ
    Self HelpCommunication SkillRelationshipMindfulnessPhilosophyInspirationProductivity
    著名人の読書リスト
    Elon MuskCharlie KirkBill GatesSteve JobsAndrew HubermanJoe RoganJordan Peterson
    受賞作品コレクション
    Pulitzer PrizeNational Book AwardGoodreads Choice AwardsNobel Prize in LiteratureNew York TimesCaldecott MedalNebula Award
    注目のトピック
    ManagementAmerican HistoryWarTradingStoicismAnxietySex
    年別ベストブック
    2025 Best Non Fiction Books2024 Best Non Fiction Books2023 Best Non Fiction Books
    学習ツール
    Knowledge VisualizerAI Podcast Generator
    注目の著者
    Chimamanda Ngozi AdichieGeorge OrwellO. J. SimpsonBarbara O'NeillWinston ChurchillCharlie Kirk
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    重要なポイント

    1

    The Production-Ready AI Blueprint

    0:00
    0:14
    0:31
    0:49
    2

    The Architecture of Durable Intent

    1:03
    1:22
    1:50
    2:04
    2:31
    2:44
    3:14
    3:27
    3:50
    4:08
    4:37
    4:51
    3

    The Prompt as a Versioned Asset

    5:02
    5:16
    5:34
    0:14
    6:02
    6:17
    6:42
    6:58
    7:18
    7:33
    7:50
    8:04
    4

    LLM-as-Judge and the Quality Gate

    8:16
    8:25
    8:46
    3:27
    9:09
    9:18
    9:35
    9:46
    10:11
    10:25
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    10:58
    5

    Securing the Pulse of the System

    11:06
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    6

    The Language of Agent Collaboration

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    16:17
    16:33
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    7

    Scaling the Multi-Agent Mesh

    17:35
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    19:08
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    8

    The Production AI Playbook

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    Reflections on the Durable Future

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