Training course · OpenAI Codex · React & Front End

OpenAI Codex for React and Front-End 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

“OpenAI Codex for React and Front-End Developers” is designed for roles such as React developers in product teams and agencies, Front-end engineers working with Next.js, Vite or similar frameworks and Maintainers of design systems and component libraries and shows step by step how to use OpenAI Codex productively, safely and transparently in React & Front End – from the fundamentals to advanced workflows.

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.

Front-end development today means component architectures, state management, server components, design systems, accessibility and performance budgets – often all at once. AI coding assistants and agents speed up exactly the work that eats time: deriving components from designs, converting class components to hooks, writing Storybook stories and Testing Library tests, fixing ARIA issues or tracking down unnecessary re-renders. Because front-end code thrives on conventions, context is everything: design tokens, folder structure, styling approach and preferred libraries must be known to the assistant. This course shows you how to set those guardrails and how to verify results reliably, both visually and technically.

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?

  • React developers in product teams and agencies
  • Front-end engineers working with Next.js, Vite or similar frameworks
  • Maintainers of design systems and component libraries
  • Full-stack developers with a front-end focus
  • UI engineers responsible for accessibility and performance

Typical challenges we address

  • Inconsistent components and styles despite an existing design system
  • Hard-to-trace re-renders, bloated bundles and weak Core Web Vitals
  • Accessibility gaps and growing pressure from legal requirements
  • Legacy code with class components, outdated patterns and missing tests

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.
  • Have AI agents generate components, stories and tests that match your design system.
  • Use AI deliberately to improve accessibility, performance and legacy code in a systematic way.
  • Check generated front-end code visually, functionally and for maintainability before it ships.

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: React & Front End
  • Building components from designs
  • Testing Library tests
  • Auditing and improving accessibility
  • Modernising legacy code
  • Optimising performance
  • Forms and data fetching
Module 7 Data protection, quality & transfer to daily work
  • Under the European Accessibility Act and its national implementations, many digital services must be accessible, so generated UI code needs proper checks. Also watch the licences of reused components and icons, keep secrets out of the client bundle and make sure tracking and consent logic complies with GDPR and ePrivacy rules.
  • 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

Building components from designs

From screenshots, design specs or Figma exports, the assistant produces typed React components that use your existing design tokens and libraries, and adds Storybook stories covering every state.

Testing Library tests

The AI writes user-centred component tests with React Testing Library and Vitest or Jest, simulates interactions, mocks API calls and covers loading, error and empty states.

Auditing and improving accessibility

The agent reviews components for semantic HTML, ARIA attributes, focus management and contrast, interprets axe results and fixes findings transparently against WCAG success criteria. Keyboard and screen reader behaviour is covered too.

Modernising legacy code

Class components are converted to function components with hooks, prop drilling is replaced by context or a proper state management approach and PropTypes give way to TypeScript types – with tests as a safety net.

Optimising performance

The AI pinpoints unnecessary re-renders, proposes memoisation, code splitting and lazy loading, analyses bundle reports and explains how each measure affects metrics such as LCP and INP.

Forms and data fetching

Complex forms with validation schemas, error messages and optimistic updates are generated alongside data-fetching logic with caching, retries and clean handling of loading and error states.

Possible hands-on projects

Interactive KPI dashboard

A React dashboard with charts, filters and a responsive layout that loads data from a REST API, built entirely by an AI agent from a short specification.

Component library with Storybook

A small, accessible component library with buttons, dialogs and form fields, including design tokens, Storybook documentation and automated tests. It forms the basis for consistent interfaces across several projects.

Accessibility checker for pull requests

A script that runs axe against Storybook stories automatically and turns the findings into a clear report attached to pull requests.

Prerequisites

You have hands-on programming experience, are comfortable with Git and the command line, and know pull-request-based workflows. Hands-on experience with React and modern JavaScript or TypeScript, plus a working knowledge of CSS, npm 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

Under the European Accessibility Act and its national implementations, many digital services must be accessible, so generated UI code needs proper checks. Also watch the licences of reused components and icons, keep secrets out of the client bundle and make sure tracking and consent logic complies with GDPR and ePrivacy rules.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Bremen Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Salzburg Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Online Request
  • Tue, 16 February 2027 – Wed, 17 February 2027 Kaiserslautern 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.

Can AI implement designs pixel-perfectly?

AI assistants now translate layouts from screenshots or specs remarkably well, especially when they know your design tokens and components. Pixel-perfect results still come from iteration, though. On the course you learn to feed back visual deviations precisely and to use Storybook and visual tests as your control mechanism.

Does the framework I use matter?

The course centres on React, but the working methods transfer to Next.js, Remix or Vite-based setups. We show how to capture framework-specific rules such as server and client components or routing conventions in instruction files, so the assistant produces code that fits your stack.

How much does “OpenAI Codex for React and Front-End 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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