Verleger: K-i-s-publishing
AI For Everyday Automation. 7 AI Workflows to Save Hours at Work Every Week
Dipankar Sarkar
Most professionals get bogged down by repetitive work that eats up hours every week. Emails, meetings, reports, research, spreadsheets, and follow-ups quickly pile up, leaving little time for the work that actually matters. AI for Everyday Automation shows you how to use AI as a practical everyday assistant to handle these recurring tasks faster and more efficiently. Using tools like ChatGPT, Claude, and Perplexity, this book walks you through seven practical workflows for automating emails, meetings, research, reports, task tracking, spreadsheets, and communication. Each workflow includes prompts, templates, and simple step-by-step guidance that you can immediately apply to your own work. By the end of the book, you’ll have a set of repeatable AI-assisted systems that help you save time, reduce repetitive work, and get through your workday with far less friction.
AI Networking Cookbook. Practical recipes for AI-assisted network automation and development
Eric Chou, John Capobianco
Transform your approach to network automation with the power of AI LLM assistants guided by hands-on recipes for building custom automation solutions quickly using artificial intelligence.You’ll learn tools and techniques such as Vibe coding for conversational development, OpenAI API scripts, prompt engineering for better outputs, local LLM fine-tuning, combining models with LangChain, and Streamlit-based frontends development. The book progresses from simple Python scripts to advanced AI-assisted automation techniques, including multi-vendor API integration, showing you how AI can enhance network configuration, monitoring, security, and troubleshooting.Each recipe presents realistic mock data, complete code examples, and step-by-step guidance, creating a safe environment for experimentation while building a solid foundation for future production use. Whether you want to automate routine configuration, implement AI-driven troubleshooting, or build compliance monitoring systems, this cookbook helps you connect your networking expertise with the capabilities of modern AI.
Irene Bratsis
AI is rapidly transforming product management, presenting new challenges and business opportunities. As AI-driven solutions become more complex, product managers must bridge the gap between technological capabilities and business needs. This book provides a detailed roadmap for successfully building and maintaining AI-driven products, serving as an indispensable companion on your journey to becoming an effective AI product manager. In this second edition, you'll find fresh insights into generative AI, and responsible AI practices with the most relevant tools for building AI-powered products.Authored by a leading AI product expert with years of hands-on experience in developing and managing AI solutions, this guide translates complex AI concepts into actionable strategies. Whether you're an aspiring AI PM or an experienced professional, this book offers a structured approach to defining AI product vision, leveraging data effectively, and aligning AI with business objectives. With new case studies and refined frameworks, this edition provides deeper insights into ethical AI, cross-functional collaboration, and deployment challenges.By the end of this book, you’ll be equipped with the knowledge to drive AI product success with key techniques for identifying AI opportunities and managing risks in a rapidly evolving landscape.*Email sign-up and proof of purchase required
Anderson Soares Furtado Oliveira, Elijah Low, Marcelo...
If you’re a web developer looking to leverage the power of AI in your projects, then this book is for you. Written by an AI and ML expert with more than 15 years of experience, AI Strategies for Web Development takes you on a transformative journey through the dynamic intersection of AI and web development, offering a hands-on learning experience.The first part of the book focuses on uncovering the profound impact of AI on web projects, exploring fundamental concepts, and navigating popular frameworks and tools. As you progress, you’ll learn how to build smart AI applications with design intelligence, personalized user journeys, and coding assistants. Later, you’ll explore how to future-proof your web development projects using advanced AI strategies and understand AI’s impact on jobs. Toward the end, you’ll immerse yourself in AI-augmented development, crafting intelligent web applications and navigating the ethical landscape.Packed with insights into next-gen development environments, AI-augmented practices, emerging realities, interfaces, and security governance, this web development book acts as your roadmap to staying ahead in the AI and web development domain.
AI Under Attack. A Practical Guide to Threats, Defenses, and Governance for AI Systems
Kris Kimmerle, David Okeyode
Contrary to general AI texts or cybersecurity books with limited AI coverage, this guide offers a comprehensive dive into securing the generative AI ecosystem.It moves through five parts: Foundations explains why AI security is unique, covering threat modeling, attack surfaces, and defense principles. Attacks examines vectors against system anatomy, data/models, prompt injection, memory, RAG, and agents, concluding with red teaming and evaluation. Designing, Deploying, and Architecting Secure AI Systems covers secure infrastructure/MLOps, APIs, defensive prompting, agent security, supply chain integrity, and Zero Trust patterns. Operationalizing AI Security and Responsibility addresses governance, risk, compliance (GRC), security operations, safety/alignment, and AI-driven misinformation. Building Sustainable AI Security Programs focuses on organizational capability, threat intelligence, collaboration, and the future of AI security. Throughout, you will gain access to practical insights and structured approaches applicable to real-world scenarios.By the end, you will be able to design, implement, and maintain security programs for generative AI, defend against advanced threats, communicate risks to stakeholders, and establish governance ensuring secure, compliant operations across the lifecycle.
AI-Assisted Coding. Enhancing Programming with AI Tools and Techniques
Rheinwerk Publishing, Inc, Michael Kofler, Bernd Öggl,...
This book takes programmers through the process of enhancing their workflow using AI tools. It begins by introducing the basics of coding with AI assistants, such as GitHub Copilot and ChatGPT, and shows how these tools can assist in writing and optimizing code. The next section focuses on using AI in debugging, refactoring, and generating software documentation, helping readers master techniques for coding with AI support. Pair programming with AI is explored in detail, with practical examples demonstrating its real-world applications. The book also dives into advanced tools like Ollama and Aider, giving readers the knowledge to build local language models and integrate them into their development workflows. The final chapters highlight how AI can be incorporated into projects, enabling more efficient, innovative coding processes. By the end of the book, readers will have the necessary skills to use AI-powered tools seamlessly, ultimately improving their programming productivity and broadening their AI integration capabilities.
Christoffer Noring, Anjali Jain, Marina Fernandez, Ayşe...
AI-Assisted Programming for Web and Machine Learning shows you how to build applications and machine learning models and automate repetitive tasks.Part 1 focuses on coding, from building a user interface to the backend. You’ll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, you’ll build a web API with Python and Flask and refactor the code to improve code readability. Part 1 ends with using GitHub Copilot to improve the maintainability and performance of existing code. Part 2 provides a prompting toolkit for data science from data checking (inspecting data and creating distribution graphs and correlation matrices) to building and optimizing a neural network. You’ll use different prompt strategies for data preprocessing, feature engineering, model selection, training, hyperparameter optimization, and model evaluation for various machine learning models and use cases. The book closes with chapters on advanced techniques on GitHub Copilot and software agents. There are tips on code generation, debugging, and troubleshooting code. You’ll see how simpler and AI-powered agents work and discover tool calling.
AI-Native LLM Security. Threats, defenses, and best practices for building safe and trustworthy AI
Vaibhav Malik, Ken Huang, Ads Dawson
Adversarial AI attacks present a unique set of security challenges, exploiting the very foundation of how AI learns. This book explores these threats in depth, equipping cybersecurity professionals with the tools needed to secure generative AI and LLM applications. Rather than skimming the surface of emerging risks, it focuses on practical strategies, industry standards, and recent research to build a robust defense framework.Structured around actionable insights, the chapters introduce a secure-by-design methodology, integrating threat modeling and MLSecOps practices to fortify AI systems. You’ll discover how to leverage established taxonomies from OWASP, NIST, and MITRE to identify and mitigate vulnerabilities. Through real-world examples, the book highlights best practices for incorporating security controls into AI development life cycles, covering key areas such as CI/CD, MLOps, and open-access LLMs.Built on the expertise of its co-authors—pioneers in the OWASP Top 10 for LLM applications—this guide also addresses the ethical implications of AI security, contributing to the broader conversation on trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI technologies with confidence and clarity.*Email sign-up and proof of purchase required