Training course · OpenAI Codex · C/C++ & Embedded

OpenAI Codex for C/C++ and Embedded 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 C/C++ and Embedded Developers” is a hands-on course for roles such as Embedded software engineers working with microcontrollers and RTOS-based systems, C++ developers in systems software, automotive and industrial automation and Firmware and device driver developers. Rather than learning OpenAI Codex in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from C/C++ & Embedded.

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.

In embedded and systems development, determinism, memory safety and tight resource budgets matter more than almost anywhere else. AI coding assistants and agents help you read datasheets and register maps, write drivers and hardware abstraction layers, clear compiler warnings and static analysis findings, and build unit tests with mocks for hardware access. The domain also demands particular care: undefined behaviour, race conditions in interrupt handlers or MISRA violations creep in quickly when generated code is accepted uncritically. In this course you learn to integrate AI into your cross-compilation workflow with CMake, debuggers and hardware-in-the-loop tests while meeting the quality and safety expectations of functionally safe products.

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?

  • Embedded software engineers working with microcontrollers and RTOS-based systems
  • C++ developers in systems software, automotive and industrial automation
  • Firmware and device driver developers
  • Embedded Linux and Yocto developers
  • Test and verification engineers for embedded systems

Typical challenges we address

  • Memory errors, undefined behaviour and concurrency bugs are hard to find and costly in the field
  • Legacy C codebases full of global state and macros with little test coverage
  • Significant effort to comply with and evidence coding standards such as MISRA C/C++ or AUTOSAR C++
  • Hardware knowledge locked in datasheets and in the heads of a few experts

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.
  • Apply AI agents to driver development, refactoring and debugging in C and C++ in a targeted, verifiable way.
  • Raise test coverage of low-level software with generated unit tests and mocks that run on the host.
  • Combine AI support with coding standards, static analysis and the evidence requirements of safety-related development.

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: C/C++ & Embedded
  • Drivers from datasheets
  • Making sense of static analysis
  • Unit tests with hardware mocks
  • Crash and memory analysis
  • Introducing modern C++
  • Build and toolchain upkeep
Module 7 Data protection, quality & transfer to daily work
  • Firmware is often core intellectual property and may be subject to export control or security requirements: you learn how to protect source code, assess licensing risks in generated code and reconcile AI use with the Cyber Resilience Act, IEC 62443 and functional safety under ISO 26262 or IEC 61508.
  • 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

Drivers from datasheets

Have register descriptions and timing diagrams structured from datasheets, then derive headers with bitfield definitions, initialisation routines and a lean hardware abstraction layer for SPI, I²C or UART peripherals.

Making sense of static analysis

Explain and prioritise findings from clang-tidy, cppcheck or MISRA checkers, propose compliant corrections and prepare justified deviations for your deviation records. Recurring patterns can then be fixed across the codebase.

Unit tests with hardware mocks

Extract testable interfaces from low-level code, generate mocks for register and HAL access and create unit tests with GoogleTest, Unity or CppUTest that run on the host.

Crash and memory analysis

Interpret HardFault registers, stack traces, core dumps and sanitiser output, narrow down likely causes such as stack overflows or use-after-free and suggest targeted debugging steps.

Introducing modern C++

Gradually replace raw pointers, manual memory management and macros with RAII, constexpr, smart pointers and type-safe abstractions without degrading real-time behaviour or the memory budget.

Build and toolchain upkeep

Structure CMake projects for cross-compilation, create toolchain files, linker scripts and CI jobs for firmware builds and analyse build failures in the context of the target platform.

Possible hands-on projects

Register header generator

A script that converts register tables from an SVD or CSV file into type-safe C headers with masks, offsets and accessor functions.

Serial protocol monitor

A desktop tool that reads from a serial port, decodes a custom binary protocol and displays frames with timestamps and filters.

MISRA report dashboard

A small web view that aggregates static analysis results, groups rule violations by module and tracks progress across builds. New violations are highlighted.

Prerequisites

You have hands-on programming experience, are comfortable with Git and the command line, and know pull-request-based workflows. You are proficient in C or C++ and experienced with build systems, debugging and low-level or systems programming.

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

Firmware is often core intellectual property and may be subject to export control or security requirements: you learn how to protect source code, assess licensing risks in generated code and reconcile AI use with the Cyber Resilience Act, IEC 62443 and functional safety under ISO 26262 or IEC 61508.

Suggested dates

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

  • Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Augsburg Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Online Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Bremen Request
  • Mon, 8 February 2027 – Tue, 9 February 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.

Is AI-generated code acceptable in safety-critical embedded systems?

Standards such as ISO 26262 or IEC 61508 do not prohibit AI tools, but they require traceable processes, reviews, testing and, where relevant, tool qualification. Generated code is therefore treated like any other code: reviewed, tested and verified against coding standards. In the course you develop working practices that support this evidence rather than bypass it.

Can an AI agent work with my target hardware?

Agents can trigger builds, flash devices, read serial output and run tests on the host or a hardware-in-the-loop rig, provided you expose the right command-line tools. We show you how to set up such loops in a controlled way, with clear permissions and without the agent accessing production devices unsupervised.

How much does “OpenAI Codex for C/C++ and Embedded 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.

More courses for C/C++ and Embedded Developers

More OpenAI Codex courses

All 32 OpenAI Codex courses

OpenAI Codex · MunichOpenAI Codex · SalzburgOpenAI Codex · BerlinOpenAI Codex · AugsburgOpenAI Codex · HanoverOpenAI Codex · BremenOpenAI Codex · StuttgartOpenAI Codex · KaiserslauternOpenAI Codex · Online