Blog series
AI Engineering.
A chapter-by-chapter guide to building production AI features with Laravel: the SDK, agents, prompts, structured output, reliability, model costs, RAG, MCP, streaming, security and observability.
About the series
What this series is about.
AI engineering means using an existing AI model to add useful features to a real software application, and then making the whole feature reliable. This series approaches that from the Laravel side: the model is one component, and the application still owns authorization, validation, persistence and the final business decision.
The chapters build on each other. The fundamentals article sets the vocabulary and a first architecture; later chapters go deeper into the Laravel AI SDK, agents and tool calling, prompt and structured-output contracts, reliability and multi-provider design, token economics, retrieval-augmented generation and vector search, the Model Context Protocol, and the production concerns of streaming, security, observability and performance.
Chapters
Chapter 01The Fundamentals of AI Engineering
A practical guide to AI engineering for Laravel developers: core concepts, architecture, tools, RAG, reliability, security, and the boundaries that keep production systems safe.
Chapter 02Getting Started with the Laravel AI SDK
A practical introduction to the Laravel AI SDK for PHP developers building AI-powered Laravel applications with providers, prompts, and responses.
Chapter 03Understanding Agents in the Laravel AI SDK
Understand how agents work in the Laravel AI SDK, including goals, tools, context, execution loops, and production design trade-offs.
Chapter 04Prompt Engineering in Laravel Applications
Learn practical prompt engineering patterns for Laravel applications, including prompt structure, context management, and reusable prompt contracts.
Chapter 05Structured Outputs in Laravel AI Applications
Build reliable structured outputs in Laravel AI applications using schemas, validation, parsing, and predictable response formats.
Chapter 06Reliability Patterns for AI Responses: Validation and Retry
Design validation and retry patterns that make AI responses more dependable in production Laravel applications.
Chapter 07Multi-Provider Architecture for Laravel AI Applications
Plan a multi-provider Laravel AI architecture that can switch models, reduce vendor lock-in, and improve reliability across AI services.
Chapter 08Understanding AI Model Costs and Token Economics
Understand AI model pricing, token usage, context windows, and cost drivers before shipping AI features in Laravel applications.
Chapter 09AI Model Selection and Cost Optimization
Choose the right AI models for Laravel workloads by balancing quality, latency, context length, reliability, and cost.
Chapter 10Tool Calling and Function Execution in Laravel AI
Use tool calling and function execution to let Laravel AI applications safely interact with APIs, databases, and product workflows.
Chapter 11Retrieval-Augmented Generation (RAG) in Laravel
Learn how retrieval-augmented generation works in Laravel and how to ground AI answers with trusted application data.
Chapter 12Embeddings and Vector Search in Laravel
Understand embeddings and vector search for Laravel applications, including indexing, similarity search, and semantic retrieval patterns.
Chapter 13Designing AI Knowledge Bases with Laravel
Design AI knowledge bases in Laravel that keep content structured, searchable, maintainable, and ready for retrieval-augmented generation.
Chapter 14Conversation Memory and Context Management
Manage conversation memory and context in AI applications without losing control of cost, privacy, relevance, or response quality.
Chapter 15Understanding the Model Context Protocol (MCP)
Understand the Model Context Protocol, why MCP matters, and how it standardizes tool and context access for AI applications.
Chapter 16MCP Server Architecture in Laravel
Explore MCP server architecture in Laravel, including transports, tools, resources, prompts, authentication, and lifecycle design.
Chapter 17Core Components of a Laravel MCP Server
Learn the core building blocks of a Laravel MCP server and how tools, resources, schemas, and handlers fit together.
Chapter 18Designing a Production-Ready MCP Server with Laravel
Design a production-ready MCP server with Laravel using authentication, validation, logging, error handling, and deployment patterns.
Chapter 19Streaming AI Responses in Laravel Applications
Implement streaming AI responses in Laravel applications to improve perceived speed and create responsive user experiences.
Chapter 20Security Considerations for Laravel AI Applications
Review security considerations for Laravel AI applications, including prompt injection, tool permissions, data exposure, and audit trails.
Chapter 21Observability and Debugging in AI Applications
Add observability and debugging to AI applications with logs, traces, evaluations, token tracking, and failure analysis.
Chapter 22Caching, Rate Limiting, and Performance in Laravel AI Applications
Improve Laravel AI application performance with caching, rate limiting, queue design, response reuse, and provider-aware throttling.
Questions
About the AI Engineering series
- What does the AI Engineering series cover?
- It covers how to add AI features to Laravel applications in production: the Laravel AI SDK, agents, prompt engineering, structured outputs, validation and retry patterns, multi-provider architecture, model costs and selection, tool calling, RAG, embeddings and vector search, conversation memory, the Model Context Protocol and MCP servers, streaming, security, observability, and caching and rate limiting.
- Who is the series written for?
- Laravel and PHP developers who want to ship AI-powered features without training models themselves. It assumes working knowledge of Laravel and explains the AI concepts as they come up.
- Where should I start?
- Start with The Fundamentals of AI Engineering. It introduces the core terms (LLM, provider, model, prompt, agent, tool, RAG, MCP) and a first production architecture that the rest of the series builds on. After that, the chapters can be read in order or by topic.
New chapters in progress
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1 of 22 chapters are live. Leave your email and I will let you know as the rest of the series goes out.