Training course · OpenAI Codex · PHP & Laravel/Symfony

OpenAI Codex for PHP Developers

Delegate development work with OpenAI Codex: CLI and cloud agent, AGENTS.md, sandboxing, approvals and team PR workflows.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects OpenAI Codex with the everyday processes of PHP & Laravel/Symfony. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

OpenAI Codex is a coding agent that runs both locally, as a command-line tool and IDE extension, and as a cloud agent. Locally, Codex reads your repository, proposes changes and runs commands inside a sandboxed environment. In the cloud, it works on delegated tasks in parallel inside isolated containers and returns results as traceable diffs or pull requests. Over two days you will learn how to combine both modes effectively and how to scope tasks so that the agent can complete them reliably and with minimal back-and-forth.

Control and security sit at the heart of the course. With AGENTS.md you hand Codex project knowledge, build and test commands, and conventions. You configure approval modes and sandboxing so that the agent only does what you permit, and you set up cloud environments with suitable setup scripts. You will also integrate Codex into your pull request workflows, use automated code review, and define team rules on which tasks are delegated and how results are checked before they are merged into the main branch.

PHP powers a large share of the web – from Laravel and Symfony applications to Shopware and Magento stores and bespoke platforms that have evolved over many years. As a result, modern framework projects frequently sit alongside legacy code without types, tests or Composer structure. AI coding assistants and agents help on both fronts: they write PHPUnit and Pest tests, bring code up to modern language standards with Rector, work through PHPStan findings level by level, generate Eloquent or Doctrine models with migrations and explain tangled legacy logic. The prerequisite is good context on framework conventions, coding standards and the test environment. This course teaches you to use agents so that modernisation becomes predictable and safe.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • PHP developers working with Laravel or Symfony
  • Developers of e-commerce systems such as Shopware or Magento
  • Agency teams juggling many client projects in parallel
  • Teams modernising legacy PHP applications

Typical challenges we address

  • Legacy code without type declarations, namespaces or automated tests
  • Laborious upgrades of PHP versions and major framework releases
  • Security risks from SQL injection, XSS and unsafe file uploads in old code
  • Tight deadlines on agency projects combined with high quality expectations

What you will be able to do

  • You use Codex locally and in the cloud for the development tasks each mode suits best.
  • You write an AGENTS.md that guides the agent reliably through your project.
  • You configure approval modes and sandboxing to match your security requirements.
  • You delegate tasks to the cloud agent and review the results systematically.
  • Use AI agents for tests, static analysis and upgrades in Laravel, Symfony and legacy projects.
  • Modernise legacy code incrementally and safely with AI support.
  • Recognise typical security flaws in generated and existing PHP code and fix them in a targeted way.

Course outline

Day 1

Module 1 Codex at a glance: CLI, IDE and cloud
  • Comparing how Codex works locally and in the cloud
  • Installing the Codex CLI, signing in and starting it in a repository
  • Interactive sessions, non-interactive execution and model choice
  • Distinguishing tasks that suit a coding agent from those that do not
Module 2 Project knowledge with AGENTS.md
  • Building an AGENTS.md with build, test and lint commands
  • Stating conventions, architectural notes and prohibitions precisely
  • Using nested AGENTS.md files for monorepos and sub-projects
  • Checking effectiveness and refining instructions iteratively
Module 3 Sandboxing, approvals and security
  • Choosing approval modes deliberately, from read-only to largely autonomous
  • Understanding sandbox boundaries for file system and network access
  • Handling secrets, dependencies from the internet and prompt injection
  • Configuration files for team standards and safe defaults
Module 4 Delegating tasks to the cloud agent
  • Configuring cloud environments with setup scripts and dependencies
  • Writing tasks with a clear goal, context and acceptance criteria
  • Launching several tasks in parallel and comparing the results
  • Using logs and test output to understand the proposed solutions

Day 2

Module 5 PR workflows and code review in the team
  • Turning results into pull requests and requesting follow-up changes
  • Using automated Codex code review on GitHub
  • Embedding Codex in scripts and CI pipelines
  • Setting team rules for delegation, review duties and accountability
Module 6 Practice lab: PHP & Laravel/Symfony
  • Generating PHPUnit and Pest tests
  • Raising PHPStan levels step by step
  • Upgrades with Rector
  • Building Laravel and Symfony features
  • Understanding and untangling legacy code
  • Finding security vulnerabilities
Module 7 Data protection, quality & transfer to daily work
  • PHP applications frequently process customer data from shops and portals, so database dumps and logs containing personal data must never go into prompts unfiltered. Check new Composer packages for licence and vulnerabilities, keep credentials from .env files out of context and, as an agency, agree contractually whether client code may be processed by AI services.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Generating PHPUnit and Pest tests

The agent writes unit and feature tests for controllers, services and models, uses factories and database transactions, and runs the tests iteratively until they pass consistently.

Raising PHPStan levels step by step

The AI works through static analysis findings systematically, adds type declarations, generics annotations and return types, and raises the analysis level in controlled steps without changing behaviour.

Upgrades with Rector

Rector rules are configured and run, remaining incompatibilities in PHP or framework upgrades are fixed by hand and deprecations surfaced in logs and tests are cleared systematically.

Building Laravel and Symfony features

From a functional description, the assistant creates migrations, Eloquent or Doctrine entities, form requests or validators, controllers, policies and tests – all in line with framework conventions.

Understanding and untangling legacy code

The assistant explains procedural legacy logic, extracts functions into namespaced classes and introduces Composer autoloading, laying the groundwork for further modernisation. Characterisation tests pin down the existing behaviour first.

Finding security vulnerabilities

The AI checks code for unsafe SQL queries, missing output escaping, CSRF gaps and insecure uploads, replacing problem areas with prepared statements and built-in framework mechanisms.

Possible hands-on projects

Laravel admin panel

A small management back end with authentication, roles, CRUD screens and feature tests, built by an AI agent from a short specification.

Symfony console importer

A Symfony console command that validates CSV or XML data, imports it into Doctrine entities and logs errors in a clear, readable way.

Upgrade readiness check

A script that runs PHPStan, a Rector dry run and Composer audit against a PHP project and produces a plain-language report on upgrade effort.

Prerequisites

You have hands-on programming experience, are comfortable with Git and the command line, and know pull-request-based workflows. Solid PHP skills and experience with Laravel or Symfony, Composer and Git.

Technical requirements

Your own laptop with a terminal, Git and a Node.js runtime; a ChatGPT plan with Codex access or an OpenAI API key, plus a GitHub account for the cloud exercises.

Data protection & compliance

PHP applications frequently process customer data from shops and portals, so database dumps and logs containing personal data must never go into prompts unfiltered. Check new Composer packages for licence and vulnerabilities, keep credentials from .env files out of context and, as an agency, agree contractually whether client code may be processed by AI services.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Wed, 2 December 2026 – Thu, 3 December 2026 Hanover Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Munich Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Online Request
  • Wed, 17 February 2027 – Thu, 18 February 2027 Stuttgart Request

Frequently asked questions

When should I use Codex locally and when in the cloud?

Locally you work interactively and close to the code, for example when debugging or making exploratory changes where you want to follow every step. The cloud agent suits well-defined tasks that can run independently, such as adding tests or fixing smaller bugs. You can start several of these in parallel and review each one as a pull request.

What belongs in a good AGENTS.md?

A good AGENTS.md explains how the project is built, tested and checked, which conventions apply and which areas must not be touched. It is concise, concrete and kept up to date. Notes on architecture and common pitfalls also help. During the course you write an AGENTS.md for a project of your own and test how it changes the agent’s behaviour.

How safe is it to let Codex run commands?

By default Codex works inside a sandbox with restricted file and network access and asks for approval before risky steps. You decide how much autonomy to grant through approval modes and configuration. In the course you learn to choose these settings deliberately and to limit risks such as prompt injection or running unfamiliar dependencies.

Is AI-assisted coding worthwhile for old PHP code without a framework?

That is exactly where it shines. AI assistants explain convoluted procedural logic, write characterisation tests that pin down existing behaviour and then introduce namespaces, autoloading and types step by step. This gives you a safe foundation for modernising legacy applications instead of attempting a risky full rewrite.

How should agencies handle client code and AI?

Agencies should agree with their clients contractually whether, and with which services, source code may be processed. On the course we discuss options such as business licences with no training on your data, exclusion rules for sensitive files and documented review processes that give your clients full transparency.

How much does “OpenAI Codex for PHP Developers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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