tl;dr: This five-part series walks you through building an Agentic AI Agent with Laravel, React, and OpenAI. You'll start by setting up your Laravel project and making a simple “Hello World” call to OpenAI, then layer on real-time streaming, custom tool interfaces, stateful contexts, and automated planning. In the end, your agent will generate a multi-step execution plan via OpenAI, then loop through each step—communicating with users, gathering input, generating content, and invoking tools registered via a standard interface—to complete complex tasks autonomously.
Building an Agentic AI Agent
In this series, we'll create an Agentic AI Agent—driven by natural language—to interpret user requests, generate step-by-step execution plans, and invoke custom tools. By the end, you'll have a Laravel-based agent that can:
- Derive a multi-step action plan from a single prompt
- Invoke PHP-based tools to manipulate data
- Maintain context across messages for richer conversations
- Stream responses to the browser in real time
We'll leverage Laravel 12, React + Inertia.js, Tailwind CSS, and OpenAI's o4-mini model.
Want to know more about Agentic AI Agents? I recently wrote a post about what is an agentic AI agent?
Over five progressively deeper chapters, this series will guide you through building an Agentic AI Agent with Laravel and OpenAI - each installment layering on the last:
- Preface 👈 You are here
- Part 1 - Getting Started with Laravel OpenAI Calls Next Post 👍
- Part 2 - Creating a Basic AI Chat App with Laravel Stream React
- Part 3 - Building Custom AI Tools in Laravel & React
- Part 4 - Adding Stateful Context to Your Agent
- Part 5 - Implementing Automated Planning
You'll come away with a solid foundation for crafting agentic workflows—without diving into security/authentication or alternative frameworks (e.g., LangChain, OpenAI Assistants API).
Let's get started with Part 1 - Getting Started with Laravel OpenAI Calls