Training course · Agentic Coding · C/C++ & Embedded

Agentic Coding for C/C++ and Embedded Developers

Use autonomous coding agents effectively: specs instead of prompts, task decomposition, test-driven loops, multi-agent setups and governance.

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

“Agentic Coding 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 Agentic Coding in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from C/C++ & Embedded.

Agentic coding means working with AI agents that carry out development tasks largely on their own: they read code, plan changes, run commands and tests, and correct themselves based on the results. Tools such as Claude Code, OpenAI Codex, the GitHub Copilot coding agent and Cursor’s agent mode have made this way of working practical for everyday use. This vendor-neutral course teaches the underlying methodology so that you achieve reliable results whatever the tool, and redefine the developer’s role within your engineering team.

The core shift is from ad hoc prompts to robust specifications. You will learn to decompose and describe tasks so that agents solve them reliably, to set up test-driven loops in which tests act as objective acceptance criteria, and to run several agents in parallel or with a division of labour. We also cover review strategies for agent-generated code and team governance: permissions, security boundaries, accountability, cost control and the gradual introduction of agentic workflows into your existing development processes.

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 understand how coding agents work and choose the right tool and level of autonomy.
  • You write specifications and project context that agents can work with reliably.
  • You break initiatives into verifiable sub-tasks and steer agents through test-driven loops.
  • You use multi-agent setups and parallel work in a controlled way.
  • 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 Foundations of agentic development
  • How coding agents work: tool calls, context windows and feedback loops
  • Comparing tools: terminal agents, IDE agents and cloud agents
  • Recognising suitable tasks and choosing levels of autonomy deliberately
  • The new role in the team: from implementation to steering and acceptance
Module 2 Specifications instead of prompts
  • Describing tasks with goal, context, constraints and acceptance criteria
  • Keeping project context in files such as CLAUDE.md, AGENTS.md or rules
  • Plan-first approach: let the agent draft a solution and review it before implementation
  • Versioning specifications and maintaining them as part of the repository
Module 3 Task decomposition and test-driven agent loops
  • Breaking large initiatives into independent, verifiable sub-tasks
  • Having tests written first and using them as an objective stopping criterion
  • Using linters, type checks and builds as automatic feedback
  • Recognising stuck loops and restarting with a new strategy
Module 4 Multi-agent setups and parallel work
  • Defining specialised subagents for research, implementation, testing and review
  • Organising parallel work with branches, worktrees and isolated environments
  • Orchestration: merging results and resolving conflicts
  • Sharing tools and data sources through MCP

Day 2

Module 5 Review, security and team governance
  • Review strategies for large, agent-generated changes
  • Defining permissions, sandboxing and protection against prompt injection
  • Embedding agents in CI pipelines and pull request processes
  • Planning team guidelines, accountability, costs and a phased rollout
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 several years of development experience, are confident with Git, testing and CI, and ideally have already used AI coding tools. 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 Git, a terminal and your development environment, plus access to at least one coding agent such as Claude Code, Codex, Copilot or Cursor.

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
  • Mon, 30 November 2026 – Tue, 1 December 2026 Augsburg Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Kaiserslautern Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Online Request

Frequently asked questions

How does agentic coding differ from vibe coding?

Vibe coding relies on fast, intuitive iteration in natural language and is particularly suited to prototypes. Agentic coding is an engineering discipline for professional codebases: precise specifications, tests as acceptance criteria, clear permissions and structured reviews ensure that agents deliver reliable, maintainable results even in complex, long-lived projects.

Is the course tied to a specific tool?

No. The course teaches methods that work with Claude Code, OpenAI Codex, the GitHub Copilot coding agent, Cursor and comparable tools. The exercises highlight differences and common ground, for example in context files, permissions and subagents. You can work with whichever tool your organisation already uses or plans to adopt.

How do we stay in control of quality and security with autonomous agents?

Control comes from several layers: tightly scoped permissions and sandboxing, tests and static analysis as automatic checks, mandatory human review before merging, and clear team rules on accountability. During the course you develop a governance concept that fits your processes, security requirements and regulatory obligations.

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 “Agentic Coding 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.

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