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Reliable AI Orchestration: Workflow Graphs, Agent Routing, Retries, State Management, and Human Oversight
Paperback
Publisher: Independently Published
Published: Sep 21 2026
Pages: 78
Weight: 0.26
Height: 0.16 Width: 6.00 Depth: 9.00
Language: English
- Agent and model routing based on capabilities, cost, load, and fallback policies
- Retry classification, exponential backoff, and randomized jitter
- Idempotency and compensation for workflows with external side effects
- Durable state, checkpoints, event logs, and version-aware replay
- Human approval, escalation, review, and audited manual intervention
- Concurrency limits, queues, scheduling, and resource fairness
- Distributed tracing, structured logs, metrics, and root-cause diagnosis
- Testing strategies for failures, recovery paths, routing changes, and workflow evolution
- Production orchestration platforms and cross-platform orchestration Rather than treating reliability as an assumption, this book approaches orchestration as a collection of explicit engineering decisions. Each topic examines how the mechanism works, the trade-offs involved, common implementation pitfalls, and practical checks that can be used to validate a real system. The examples are designed to help engineers reason about failure scenarios such as retry storms, dependency cycles, inconsistent state, unreliable routing, queue starvation, incorrect replay, and invisible manual fixes. Whether you are designing an AI agent platform, building multi-agent workflows, integrating multiple AI models, or operating AI systems in production, Reliable AI Orchestration provides a structured framework for understanding how workflow coordination can be made observable, recoverable, and dependable.
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