Leanpub Header

Skip to main content

Filters

Category: "Agentic Engineering"

Books

  1. Android AI Agents. Building autonomous apps that use Tool Calling, Function Injection, and Screen Awareness to perform tasks for the user

    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.

  2. Cut Your Claude Code Token Usage in Half
    Cut Your Claude Code Token Usage in Half
    48 diagnostic symptoms for Claude Code cost: context window bloat, subagent cost, MCP server overhead and cache misses — what each looks like and what to change.
    yurukusa

    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.

  3. Building GenAI Systems for DFIR
    Building GenAI Systems for DFIR
    Designing Trustwothy GenAI Applications for Digital Forensics & Incident Responders
    Jonathan Pan

    This book presents an architecture-first approach to designing trustworthy GenAI applications. Using Digital Forensics and Incident Response (DFIR) as a continuous case study, you will progressively build an AI-assisted investigation system. If you want to move beyond building AI applications that simply work, and start architecting AI systems that professionals can trust, this book is for you.

  4. Architecting the End of Chaos
    Architecting the End of Chaos
    Mastering Complexity through Distributed Hive Governance
    Mickael Lamare

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

  5. Architecting Production-Ready Gen AI and Agentic AI Systems
    Architecting Production-Ready Gen AI and Agentic AI Systems
    A Practitioner’s Guide to Architecture, Retrieval, Agents, Evaluation, Security, Governance, FinOps, and Production Operations
    Srinivas Bommena

    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.

  6. MCP Integrations for Microsoft 365
    MCP Integrations for Microsoft 365
    Design practical AI workflows with Excel, Word, and various MS Office tools using Model Context Protocol
    GitforGits | Asian Publishing House

    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.

  7. C# & AI Masterclass: The Core of AI Engineering: Microsoft Semantic Kernel & Agentic Patterns.

    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.

  8. C# & AI Masterclass: Cloud-Native AI & Microservices. Containerizing Agents and Scaling Inference.

    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.

  9. AI with JavaScript & TypeScript: Autonomous Agents. Building Multi-Agent Systems and Workflows with LangGraph.js

    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.

  10. Astrophysics & AI with Python Programming
    Astrophysics & AI with Python Programming
    Building Research Agents for Astronomy, Cosmology, and SETI
    Edgar Milvus

    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.

  11. Geospatial AI (GeoAI) with Python Programming
    Geospatial AI (GeoAI) with Python Programming
    Building Autonomous GIS Agents, Deep Learning Models, and Interactive Dashboards
    Edgar Milvus

    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.

  12. Bioinformatics & AI with Python Programming
    Bioinformatics & AI with Python Programming
    Master Genomic Data Science, Protein Folding with AlphaFold, and AI-Driven Drug Discovery
    Edgar Milvus

    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.

  13. Cloud-Native Python, DevOps & LLMOps. Containerization, Kubernetes, and Serving AI Models at Scale
    Cloud-Native Python, DevOps & LLMOps. Containerization, Kubernetes, and Serving AI Models at Scale
    From Docker and Kubernetes to Serving LLMs with Pulumi
    Edgar Milvus

    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.

  14. Finance & AI Trading with Python Programming
    Finance & AI Trading with Python Programming
    Master Algorithmic Trading, Financial NLP, and Vectorized Backtesting to Build Autonomous 'News + Math' Strategies
    Edgar Milvus

    Stop Watching the Market. Start Coding It. 📈 Welcome to the era of "Quantamental" AI Trading. Volume 7 is your engineering manual for building professional-grade trading infrastructure. Bridge the gap between classical technical analysis and LLMs—designing systems that trade on both Math (price action) and News (sentiment). From vectorized backtesting to sentiment analysis with FinBERT, it’s time to engineer your edge.

  15. Architecting Neuro-Symbolic Agents with Python Programming
    Architecting Neuro-Symbolic Agents with Python Programming
    Integrating LLMs, Wolfram Alpha, IBM Watson and Open Source Stacks for Near-Zero Hallucination Systems
    Edgar Milvus

    What You Will Master: The Enterprise Stack: Google Gemini + Wolfram + Watson. The Open Source Stack: Llama 3 + SymPy + ChromaDB (fully offline). The Outcome: Self-healing, near-infallible agents that never lie about data