Training course · OpenAI Codex · Java & Spring

OpenAI Codex for Java and Spring 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 Java and Spring Developers” is a hands-on course for roles such as Java back-end developers using Spring Boot or Jakarta EE, Teams modernising legacy Java applications and Software architects for enterprise and microservice landscapes. Rather than learning OpenAI Codex in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Java & Spring.

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.

Java and Spring carry business-critical systems in many organisations: banking back ends, ERP integrations, public-sector applications and large microservice estates. These systems have often grown over many years, and modernisation never stops. AI coding assistants and agents change the heaviest routine work in particular: major Spring Boot upgrades including the javax-to-jakarta switch, JUnit and Mockito tests for poorly covered code, refactorings towards records and modern language features, and analysis of stack traces and Hibernate issues. Clear guardrails are essential: build tool, module structure, architecture rules and test strategy all need to be in context. This course shows you how to use agents productively and in a controlled way in Maven or Gradle projects.

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?

  • Java back-end developers using Spring Boot or Jakarta EE
  • Teams modernising legacy Java applications
  • Software architects for enterprise and microservice landscapes
  • Developers in banking, insurance and the public sector
  • Tech leads responsible for upgrades and technical debt

Typical challenges we address

  • Laborious framework and JDK upgrades with numerous breaking changes
  • Large legacy codebases with low test coverage and tight coupling
  • Hard-to-analyse performance issues in JPA, Hibernate and transactions
  • Heavy boilerplate in configuration, mapping and interface code

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 Spring Boot upgrades, refactorings and test generation in Maven and Gradle projects.
  • Diagnose Hibernate, performance and production issues faster with AI support.
  • Embed architecture rules and quality standards so that generated Java code adheres to them reliably.

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: Java & Spring
  • Driving a Spring Boot upgrade
  • Generating JUnit and Mockito tests
  • Refactoring legacy code
  • Analysing JPA and Hibernate issues
  • REST APIs and interfaces
  • Making sense of stack traces and production errors
Module 7 Data protection, quality & transfer to daily work
  • Java systems often run in regulated sectors: agree with information security and data protection which code may be sent to external models, and take requirements such as DORA, NIS2 or national banking IT rules into account. Generated code and new Maven dependencies should be checked for licences and known vulnerabilities and recorded in an SBOM.
  • 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

Driving a Spring Boot upgrade

The agent analyses dependencies, applies OpenRewrite recipes, switches javax packages to jakarta, adapts deprecated configuration and security setups and iterates over build and tests until the application is green again.

Generating JUnit and Mockito tests

Services and controllers get unit tests with JUnit and Mockito plus slice tests using WebMvcTest or DataJpaTest. The AI deliberately raises coverage on critical paths and documents test assumptions.

Refactoring legacy code

Large classes are split up, DTOs turned into records, null checks replaced with Optional and streams used where they help. Existing tests safeguard behaviour at every step.

Analysing JPA and Hibernate issues

The AI reads SQL logs and stack traces, spots N+1 queries, LazyInitializationExceptions and poor fetch strategies, and proposes entity graphs, projections or index changes. Each optimisation is backed by SQL logs.

REST APIs and interfaces

OpenAPI specifications are turned into controllers, DTOs, MapStruct mappers and Bean Validation, complete with consistent error handling via ControllerAdvice and integration tests. Existing package and naming conventions are respected.

Making sense of stack traces and production errors

Long stack traces, thread dumps and log excerpts are summarised, the likely root cause is narrowed down and a reproducing test case plus fix is proposed.

Possible hands-on projects

Spring Boot microservice

A REST service with Spring Data JPA, Flyway migrations, Bean Validation, Actuator endpoints and Testcontainers tests, developed entirely by an AI agent from a specification.

Dependency report for Maven and Gradle

A command-line tool that analyses build files, lists outdated and vulnerable libraries and describes upgrade paths along with expected breaking changes.

Architecture rule checks

An ArchUnit test suite that automatically enforces your project’s layering rules, package dependencies and naming conventions and runs in the CI pipeline.

Prerequisites

You have hands-on programming experience, are comfortable with Git and the command line, and know pull-request-based workflows. In-depth Java knowledge and practical experience with Spring Boot or Jakarta EE, Maven or Gradle 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

Java systems often run in regulated sectors: agree with information security and data protection which code may be sent to external models, and take requirements such as DORA, NIS2 or national banking IT rules into account. Generated code and new Maven dependencies should be checked for licences and known vulnerabilities and recorded in an SBOM.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Munich Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Online Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Online Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Hanover Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Online 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 an AI agent carry out a major Spring Boot upgrade on its own?

An agent can take on much of the mechanical work – package switches, configuration changes and iteratively fixing compile and test failures – especially when combined with OpenRewrite. Architecture decisions, functional sign-off and testing in realistic environments remain the team’s job. On the course you practise this workflow on a sample project.

Is AI-assisted coding allowed in regulated environments?

In principle yes, but with clear rules. What matters is the choice of provider and operating model, contractual commitments on data use, approval processes and traceable reviews. We discuss how banks, insurers and public authorities typically approach this and which questions you should settle with your information security team.

How much does “OpenAI Codex for Java and Spring 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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