Developer guides (14 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condizione: Neu. Neuware.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. AI coding assistants like GitHub Copilot, Cursor, and Claude Code make it incredibly easy to generate hundreds of lines of code in seconds. But this speed creates a massive bottleneck at the pull request stage. How do you review code you didn't write, generated by an assistant that doesn't understand your production environment, without slowing down your team or letting critical bugs slip into production?This book provides a systematic, disciplined review model to inspect AI-assisted changes for correctness, security, architecture, tests, and dependencies. You will learn how to establish rigorous quality gates, detect hidden semantic bugs, and maintain complete engineering control over your codebase.Designed for professional software developers, tech leads, and engineering managers, this guide is for anyone working with AI coding tools who wants to maintain high standards of code quality and security. You do not need machine learning theory; the focus is entirely on practical engineering control.You will learn to identify and classify unique AI failure modes, such as plausible wrongness, context loss, and silent requirement drift, before they reach production. The book shows you how to evaluate AI-generated tests to ensure they actually challenge the implementation rather than merely confirming the generator's assumptions. You will also learn to conduct targeted security reviews to detect object-level authorization gaps, input validation bypasses, and accidental credential leaks, while managing architectural drift and dependency risks by keeping code aligned with your system's established design patterns and licensing policies.This guide uses a highly practical, example-driven approach. It bypasses abstract theory to focus entirely on real-world engineering workflows, pull request strategies, and team governance. It concludes with a complete, adaptable review playbook that you can immediately integrate into your team's daily operations.By implementing this structured review playbook, you can confidently adopt AI coding assistants to accelerate development while keeping your production systems secure, reliable, and maintainable. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condizione: new. Paperback. Preparing for the EU Cyber Resilience Act can feel overwhelming when legal duties must be translated into product boundaries, engineering decisions, release gates, vulnerability workflows, and evidence that teams can actually retrieve.This practical implementation guide helps you turn CRA requirements into an operational cybersecurity program for digital products. You will learn how to establish a readiness baseline, document CRA scope, assign ownership, assess product cybersecurity risk, and connect security requirements to architecture, development, verification, release, support, and end-of-support decisions.Written for software vendors, SaaS providers, IoT manufacturers, DevSecOps teams, security managers, product managers, CTOs, technical founders, compliance consultants, and engineering leaders, the book assumes practical technical or product experience rather than specialist legal training. It is especially suited to small and mid-sized organizations preparing products for the EU market.You will learn how to govern dependencies and SBOMs, preserve component provenance, operate vulnerability intake and triage, coordinate remediation and secure updates, establish coordinated vulnerability disclosure, prepare time-bound incident and exploited-vulnerability reporting, and build product security documentation linked to specific releases.The approach is example-driven and operational. It uses decision records, obligation matrices, risk assessments, architecture records, lifecycle gates, supplier reviews, evidence indexes, templates, exercises, tabletop scenarios, and release-aligned work packages. Examples involving cloud backends, APIs, mobile clients, connected devices, firmware, remote services, open-source components, and hardware partners show how to handle uncertainty without making unsupported compliance claims.Use this book to build a repeatable CRA readiness blueprint that improves ownership, traceability, vulnerability response, supplier governance, and release confidence while keeping legal interpretation and engineering implementation properly connected but distinct. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condizione: new. Paperback. AI automation is easy to demonstrate and difficult to operate responsibly. A model can classify an email, extract fields from a document, or summarize research-but without boundaries, validation, approvals, and recovery paths, a useful experiment can become an unreliable business process.This project-driven guide shows you how to build practical AI workflows in n8n for email triage, document intake, evidence-based research, operational reporting, controlled content, knowledge-base questions, approvals, monitoring, and recovery. You will learn to separate deterministic rules from model-assisted judgment, preserve stable data contracts, validate structured outputs, and route uncertain cases to accountable human review.Designed for n8n users, automation consultants, developers, operations professionals, and technical business users, the book assumes basic familiarity with workflows and APIs rather than advanced machine-learning theory. You will compare local Ollama-based inference with OpenAI-compatible cloud APIs, using equivalent inputs and provider-neutral interfaces so you can evaluate privacy, quality, latency, capacity, and cost for each use case.Build workflows that can classify and extract information from varied documents, triage shared inboxes without unauthorized sending, gather traceable research evidence, generate reports from validated metrics, and answer governed knowledge-base questions with source references. Add structured-output parsing, JSON Schema validation, confidence-aware routing, idempotency, retries, fallbacks, dead-letter recovery, monitoring, and budget controls.Through hands-on projects and a capstone AI Operations Desk, you will connect intake, retrieval, document processing, recommendations, human approval, audit history, notifications, and controlled handoff. The emphasis is practical: define the outcome, test representative cases, preserve evidence, make failure visible, and keep consequential decisions under accountable control.By the end, you will have a disciplined method for turning AI capabilities into repeatable n8n workflows that are understandable, testable, and safer to operate in real business environments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…