Agentic Engineering

Master AI integration on Apple platforms by bridging Swift 6 with OpenAI, LangChain, and autonomous agents. Build high-performance RAG pipelines using hardware-accelerated vector math and persistent local semantic memory. Architect thread-safe, real-time apps with strict concurrency, intelligent function calling, and efficient token streaming. Move from basic API calls to production-grade intelligence with the definitive guide for modern Apple developers.

Most writing about AI and infrastructure stops at the demo. This book starts on the day the model is confidently wrong at 3 a.m. and an auditor asks who authorised the action it took. Seven working labs — MCP servers with real identity and audit, closed-loop remediation behind a reversibility gate, and autonomy that can be revoked — for platform engineers in safety-critical and regulated industries.

Stop building chatbots and start building agents that interact directly with the Android OS. Master Gemini Nano and AICore to architect autonomous systems that see, think, and take action. Implement production-ready Tool Calling, Screen Awareness, and the ReAct loop using Kotlin 2.x. Move beyond the API call—embrace the Agentic Era and build the future of mobile intelligence.

Claude Code users routinely spend more on tokens than they expect, and cannot see where the money goes. Chapter 8 catalogues 48 diagnostic symptoms — what each one looks like, what it costs you, and what to change — with a fix where a fix exists, and an honest "unresolved" where none does yet. Chapter 7 puts before-and-after numbers against the changes, measured on the author's own unattended runs, and Chapter 9 collects the settings templates.

A governance framework for taming complexity in distributed systems. From solo platforms to AI agents.

An AI system becomes an architecture problem when it can influence decisions, invoke tools, carry state or change the outside world. This practitioner playbook shows how to design Gen AI and Agentic AI systems that remain reliable, governable and defensible once they reach production.

I strongly recommend this book to developers, platform engineers, and technical architects who work with Microsoft 365. These professionals will learn to integrate AI-assisted workflows into existing business processes without unnecessary complexity.

Evolve from building static applications to architecting sophisticated cognitive systems. Master the Microsoft Semantic Kernel to bridge deterministic C# code with LLM reasoning. Build autonomous agents that plan, execute, and adapt using advanced enterprise patterns. Stop writing scripts and start engineering the future of intelligent .NET software.

Stop scripting and start engineering the next generation of cloud-native AI. Master C# and Kubernetes to build resilient, distributed agent swarms at scale. Bridge the gap between experimental logic and high-performance, production-grade systems. Architect the future of intelligence—from event-driven scaling to secure service meshes.

Unlock the power of Cyclical AI and move beyond linear chains with LangGraph.js. This deep-dive guide teaches TypeScript developers to build autonomous agents that can reason, loop, self-correct, and collaborate. Master the architecture of stateful, multi-agent systems, from advanced state management to production deployment. Stop building scripts and start engineering the intelligent, resilient systems of the future.

The universe is no longer just observed; it is computed through the lens of Python and Artificial Intelligence. Master NASA-grade orbital simulations, classify galaxy morphologies with CNNs, and deploy Vision Transformers. Create autonomous LLM agents that mine ArXiv for breakthroughs and GANs that generate realistic nebulae. Join the new breed of scientist-programmers and build the future of computational astronomy today.

Transform static maps into intelligent systems with Geospatial AI (GeoAI) with Python Programming. Bridge the gap between GIS and AI, from satellite image analysis to autonomous LangChain agents. Master production-ready code for GNNs, U-Net architectures, and real-time spatial dashboards. Stop just looking at the map—teach your code to understand it.

DNA is the ultimate code. Learn how to program it. Bridge the gap between classic bioinformatics and the AI revolution. From DNA sequence manipulation with Biopython to predicting protein structures with AlphaFold and building autonomous RAG agents for drug discovery, this volume is your roadmap to the future of life sciences. Don’t just process data—engineer the future of medicine with Python.

Your Code Works Locally. Now, Make It Run for the World. 🌍 Mastered Python? Now face the ultimate challenge: Production. Volume 8: Cloud-Native Python, DevOps & LLMOps takes you beyond the IDE and into the data center. Learn to containerize with Docker, orchestrate with Kubernetes, and serve 70B+ parameter models with enterprise-grade LLMOps. Don’t just write software—architect it.