AI Systems Engineering Handbook

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Fourteen chapters for designing, building, evaluating, deploying, operating, and improving production AI systems.

01

Foundations of AI Systems Engineering

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02

The AI System Stack

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03

Requirements, Risk, and Product Fit

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04

Prompt Engineering for Production

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05

Context Engineering and Retrieval

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06

Harness Engineering and Control Loops

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07

Tool Use and Agentic Workflows

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08

Evaluation Engineering

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09

Security, Privacy, and Governance

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10

Deployment and Runtime Architecture

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11

Observability, Incidents, and AI SRE

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12

Reference Architectures and Design Reviews

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13

Case Studies

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14

Templates, Checklists, and Runbooks

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