Paperback. Build AI systems that work in production. Not demos. Not prototypes. Production.This book is for architects, senior developers, and technical leads who need to design, build, and govern AI systems on Azure and AWS using Microsoft Copilot, GitHub Copilot, Semantic Kernel, and AWS Bedrock. Every pattern in this book meets real requirements of regulated industries: security, compliance, cost control, and operational stability.What you will build across 13 hands-on labs: End-to-end RAG pipelines with Azure AI Search, hybrid search, semantic ranking, and automated RAGAS evaluation gates in CI/CDMulti-agent systems using Semantic Kernel, covering intent classification, agent handoffs, context pruning, and cost guardrailsCustom GitHub Copilot Extensions that connect Copilot Chat to your internal tools and incident management systemsAzure API Management as a governance gateway for OpenAI calls, covering rate limiting, key rotation, cost chargeback, and audit loggingMulti-cloud AI pipelines using Azure OpenAI and AWS Bedrock together, with Terraform provisioning and private networking throughoutFull MLOps for AI: prompt regression testing, RAGAS quality gates in CI/CD, and deployment gates that block on hallucination ratesWho this book is for: Developers moving from writing code with Copilot to designing systems built on CopilotTech leads responsible for AI adoption, tooling decisions, and developer productivity programsCloud and AI architects designing AI infrastructure for FinTech and regulated enterprise environmentsWhat makes this book different: Every statistic is cited with source and year. Every lab includes error handling, pinned dependency versions, and patterns appropriate for enterprise deployment. The productivity numbers are analyzed critically, including what they mean in regulated financial services environments where change management cycles reduce realized gains. No hype. No filler. No demos that stop at the whiteboard.Coverage includes: GitHub Copilot (Individual, Business, Enterprise), Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Azure API Management, Semantic Kernel 1.3, LangChain, LangGraph, AWS Bedrock (Claude 3.5 Sonnet, Titan, Llama 3), Terraform, Bicep, GitHub Actions, RAGAS evaluation, Responsible AI, GDPR, SOC 2, PCI-DSS compliance mapping.First Edition, 2026. All pricing and feature references verified at time of publication. Verify current pricing at official vendor pages before deployment decisions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Bibliographic Details

Title: Mastering Microsoft Copilot for AI Architects (Paperback)
Publisher: Independently Published
Publication Date: 2026
Language: English
ISBN 13: 9798181329232
Binding: Paperback
Condition: new

About this title

Synopsis

Build AI systems that work in production. Not demos. Not prototypes. Production.

This book is for architects, senior developers, and technical leads who need to design, build, and govern AI systems on Azure and AWS using Microsoft Copilot, GitHub Copilot, Semantic Kernel, and AWS Bedrock. Every pattern in this book meets real requirements of regulated industries: security, compliance, cost control, and operational stability.

What you will build across 13 hands-on labs:

End-to-end RAG pipelines with Azure AI Search, hybrid search, semantic ranking, and automated RAGAS evaluation gates in CI/CD
Multi-agent systems using Semantic Kernel, covering intent classification, agent handoffs, context pruning, and cost guardrails
Custom GitHub Copilot Extensions that connect Copilot Chat to your internal tools and incident management systems
Azure API Management as a governance gateway for OpenAI calls, covering rate limiting, key rotation, cost chargeback, and audit logging
Multi-cloud AI pipelines using Azure OpenAI and AWS Bedrock together, with Terraform provisioning and private networking throughout
Full MLOps for AI: prompt regression testing, RAGAS quality gates in CI/CD, and deployment gates that block on hallucination rates

Who this book is for:

Developers moving from writing code with Copilot to designing systems built on Copilot
Tech leads responsible for AI adoption, tooling decisions, and developer productivity programs
Cloud and AI architects designing AI infrastructure for FinTech and regulated enterprise environments

What makes this book different:

Every statistic is cited with source and year. Every lab includes error handling, pinned dependency versions, and patterns appropriate for enterprise deployment. The productivity numbers are analyzed critically, including what they mean in regulated financial services environments where change management cycles reduce realized gains. No hype. No filler. No demos that stop at the whiteboard.

Coverage includes:GitHub Copilot (Individual, Business, Enterprise), Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Azure API Management, Semantic Kernel 1.3, LangChain, LangGraph, AWS Bedrock (Claude 3.5 Sonnet, Titan, Llama 3), Terraform, Bicep, GitHub Actions, RAGAS evaluation, Responsible AI, GDPR, SOC 2, PCI-DSS compliance mapping.

First Edition, 2026. All pricing and feature references verified at time of publication. Verify current pricing at official vendor pages before deployment decisions.

"About this title" may belong to another edition of this title.

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