Durable AI Agents with Temporal

Build Reliable Production Agent Workflows in Python with MCP, Human Approval, Retries, Testing, and Deployment

Produkt bewerten

Lucian Verne

Verlag:

Independently Published

Unsere-Artikel-Nr.: P36965816

EAN: 9798191362380

Erhältlich:

Nicht auf Lager

Zustellung: Di, 08.09.2026

Versand: Kostenlos

CHF 54.50

Beschreibung

Building an AI agent is exciting. Keeping it reliable when APIs fail, workers restart, approvals take hours, or tools run twice is the real challenge. Durable AI Agents with Temporal. shows you how to build AI workflows that are designed to survive real production conditions. You do not need prior experience with Temporal, MCP, durable workflow engines, or distributed systems. With basic familiarity with Python and APIs, you can follow the book step by step as you build a practical Durable Research-to-Action Operations Agent. from the ground up. Instead of overwhelming you with theory or huge code listings, the book introduces each concept in manageable stages. You will run the system, inspect what happens, test failures, fix problems, and build confidence through small, working milestones. Mistakes are treated as part of the learning process, not something to fear. Key FeaturesPractical, step-by-step introduction to Temporal durable execution. Reliable LLM and agentic AI workflow orchestration. Retrieval and Model Context Protocol (MCP). integration. Durable human-in-the-loop approval. Retries, timeouts, checkpoints, and long-running workflows. Idempotency. and protection against duplicate side effects. Saga compensation. for recovering partial operations. Testing, replay verification, and failure injection. Security, prompt-injection protection, auditing, and observability. Docker, CI/CD, Temporal Cloud, Worker Versioning, and rollback. What You Will LearnYou will learn how to:. Separate deterministic Workflow logic from external Activities. Build AI agents that recover after worker and dependency failures. Generate and validate structured LLM plans. Integrate retrieval and governed MCP tools. Pause safely for human approval and resume hours or days later. Manage Workflow state, agent context, and long-running operations. Prevent duplicate external actions. Test failures before they happen in production. Monitor logs, metrics, traces, model usage, and cost. Deploy and operate reliable AI-agent systems. Who Is This Book For. This book is ideal for Python developers, AI application builders, students, self-learners, software engineers, and professionals who want to understand production AI systems. without needing previous Temporal or distributed-systems experience. Table of ContentsChapter 1:. Engineering AI Agents for Real Production ConditionsChapter 2:. Workflows, Activities, Workers, and Durable RecoveryChapter 3:. Building Reliable LLM Planning and ExecutionChapter 4:. Retrieval, Tools, and MCP IntegrationChapter 5:. Workflow State, Agent Memory, and Long-Running ExecutionChapter 6:. Human Approval and Resumable Agent WorkflowsChapter 7:. Idempotency, Side Effects, and CompensationChapter 8:. Testing and Evaluating Durable AI AgentsChapter 9:. Securing, Auditing, and Observing Durable AgentsChapter 10:. Docker, CI/CD, Deployment, and Production Operations. Stop building AI agents that only work when everything goes right. Start building systems that can recover when things go wrong. Begin Durable AI Agents with Temporal. today and turn fragile AI prototypes into reliable, production-ready workflows-one practical step at a time.

Spezifikationen

Sprache

Englisch

Autor

Lucian Verne

Erscheinungsjahr

2026

Format

Buch (Softcover)

Anzahl Seiten