Reviewing and testing with Codex

How to have a change reviewed and tested by Codex before validating it?

  • Codex

1250 € per session, excl. VAT

In short

Improve your code quality and reduce review time using AI. This course shows you how to integrate Codex into your workflow to have it analyze, test, and suggest improvements on your code changes, all within a secure environment, even before a human peer review.

Why this training?

The problem
Fragmented uses and results that are hard to verify.
What it costs today
Manual rework and decisions based on incomplete information.
Why this skill
A reviewed diff with executed tests and risks still requiring validation.
What you gain
A reviewed diff with executed tests and risks still requiring validation.

Objectives of this training

  • Submit a code change to Codex for a structured analysis.
  • Ask Codex to write and run relevant tests within its sandbox.
  • Interpret the 'diff' and review suggestions provided by the AI.
  • Configure an auto-review rule to automate the assignment of reviews.
  • Apply a decision checklist to accept or reject an AI-assisted change.
  • A reviewed diff with executed tests and risks still requiring validation.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Developers
  • Tech Leads and Software Architects
  • DevOps Engineers

Prior skills

  • AI Fundamentals and AI Prompting completed, or equivalent experience (a learning prerequisite, not a registration condition).
  • Have practised: Understand Codex and get started, or have equivalent skills. Compatible Codex account and authorised demonstration environment; verify repository, terminal, tests and connectors with least privilege. No secrets or live deployment; human review is required, with no automatic production validation.
  • A paid subscription to an AI solution offering the features used, the organisation’s authorisation for third-party tools, and the actual accounts and access rights.

To prepare before the session

  • Compatible Codex account and authorised demonstration environment; verify repository, terminal, tests and connectors with least privilege. No secrets or live deployment; human review is required, with no automatic production validation.

What you will work on

  1. Initiating a Code Review with Codex

    Understanding the Codex sandbox and its approval policy.

  2. Having AI Generate and Run Tests

    Formulating effective prompts to request the creation of relevant tests.

  3. Analyzing the 'diff' and Feedback from Codex

    Reading and understanding the generated 'diff' view that highlights the AI's suggestions.

  4. Validating, Rejecting, and Automating the Process

    Using a decision checklist to accept or reject the modification.

What you take away

  • A validation checklist for AI-reviewed changes.
  • A prompt template for requesting code tests from Codex.
  • A summary of best practices for an AI-assisted review workflow.

Method and assessment

  • Demonstration of available features, guided exercises and an independent case.
  • Peer review of the deliverable and correction against original sources.

The participant presents the stated deliverable, justifies sources and permissions, identifies and corrects an error and explains limitations. Assessment rubric: accuracy, traceability, access control and handover to a colleague.

Frequently asked questions

What concrete outcome is assessed?

A reviewed diff with executed tests and risks still requiring validation.

What access is needed before the session?

Compatible Codex account and authorised demonstration environment; verify repository, terminal, tests and connectors with least privilege. No secrets or live deployment; human review is required, with no automatic production validation.

Which step should come before this course?

Have practised: Understand Codex and get started, or have equivalent skills.

How are data protected and results validated?

Use fictional, anonymised or explicitly authorised data. Your organisation’s designated person checks sources, rights and results before use; subscriptions and external access are not assumed to be included.

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