Reseña del libro "AI Forward Deployed Engineering (en Inglés)"
Build AI systems that work beyond the prototype.AI Forward Deployed Engineering: Fundamentals & System Design is a practical technical guide to designing, integrating, deploying, and operating production-ready AI and agentic systems in real enterprise environments.Forward Deployed Engineering sits at the intersection of AI, software engineering, enterprise systems, cloud infrastructure, security, and customer problems. This book focuses on the engineering decisions required to move from an AI capability or proof of concept to a reliable system that can operate with real data, APIs, permissions, business rules, latency requirements, and human decision points.The book covers: Foundation models, inference, structured outputs, prompt and context engineeringRetrieval-Augmented Generation (RAG), chunking, embeddings, hybrid search, reranking, and grounded generationTool calling, agentic workflows, ReAct, routing, orchestration, MCP, A2A, and multi-agent patternsState, memory, Human-in-the-Loop (HITL), guardrails, authorization, and deterministic control boundariesDiscovery and scoping, functional and non-functional requirements, and AI-versus-software decision boundariesMVP-to-production architecture, APIs, state management, asynchronous workflows, reliability, and failure handlingCloud deployment, containers, scaling, queues, caching, model routing, and cost-aware architectureEvaluation, tracing, observability, latency, quality metrics, safety, and production monitoringRather than forcing every problem into RAG, autonomous agents, or multi-agent architectures, the book emphasizes a fundamental engineering principle: Use the simplest architecture that reliably satisfies the business, technical, security, and operational requirements.The final part applies these principles through five realistic system-design scenarios: Enterprise RAG & Knowledge Assistant - permission-aware retrieval, hybrid search, reranking, grounding, citations, and enterprise knowledge architecture.Intelligent Invoice Automation Agent - AI-assisted extraction combined with deterministic validation, durable workflows, Human-in-the-Loop approval, and controlled financial execution.Agentic Commerce & Product Discovery - natural-language product discovery, parallel retailer tools, canonical normalization, deterministic ranking, graceful degradation, and bounded agentic search.Customer Service & Case Resolution Agent - RAG, transactional tools, policy controls, structured state, safe action execution, and human escalation.AI Sales & Customer Onboarding Agent - customer qualification, product knowledge, CRM and pricing integrations, commercial guardrails, and long-running onboarding workflows.Each design focuses not only on what to build, but also why the architecture is appropriate, where AI should and should not be used, what should remain deterministic, how failures should be handled, and how the system should be evaluated in production.Written for software engineers, AI engineers, Forward Deployed Engineers, agentic AI engineers, solution architects, and technical leaders, this book provides a practical framework for reasoning about modern enterprise AI systems-from discovery and MVP design through production deployment, scaling, evaluation, and observability.The goal is not maximum AI autonomy. The goal is reliable business outcomes through the right combination of probabilistic intelligence and deterministic engineering.
