Two developers in front of a screen showing an IDE and Claude Code in the terminal

Training

Professional AI Coding

The Hands-On Training for Development Teams

  • Ship features reliably
  • Safeguard quality and accountability
  • Build lasting AI competence
  • Establish ways of working across the team

From ad hoc AI use to a professional way of working

Many development teams already use AI - but inconsistently, superficially, or disconnected from their actual development environment. In this training, your team builds a shared, traceable way of working: handing off tasks to AI agents in a structured way, critically reviewing results, and using the right tools responsibly.

From your first prompt to multi-agent orchestration.

In this training, you'll learn to integrate AI tools safely and confidently into your everyday development work. You work directly in your IDE and on your own codebase, review results in a traceable way, and develop workflows your team can keep using long after the training ends.

  • Choose the right AI tool for every task - understand where Claude Code, GitHub Copilot, Codex and Cursor each fit
  • Guide agents reliably towards the desired outcome - break down tasks, hand them off in a structured way and review the results
  • Make good practices reusable across your team - build your own skills and agents for recurring tasks
  • Connect AI to your tools and data sources - integrate internal systems via MCP servers
  • Handle complex tasks efficiently in parallel - coordinate multiple agents on a shared codebase
  • Automate repetitive browser work - hand research, testing and click-through flows over to an agent
  • Get up to speed in unfamiliar codebases faster - use AI for code comprehension and reviews

From the fundamentals to scaling up

2 days - core training: Over two intensive days, you work through the full learning path: setting up the tools, developing agentic ways of working, and building your own skills, agents and MCP integrations. From there, you learn how to apply these approaches across the team and for more demanding tasks.

Optional: day 3 - advanced: The third day goes deeper on scaling: you learn to keep agents working reliably over many hours and to coordinate multiple agents productively on the same project.

Get started

Set up the tools, understand the fundamentals, tackle your first real tasks in your own project

Go deeper

Control context deliberately, AI-assisted code review, get to grips with unfamiliar codebases

Extend

your own skills, your own agents, your own MCP servers

Scale up

Multi-agent orchestration, browser automation, reusable setups for the whole team

Topics in focus

Tool Landscape and Where to Draw the Line

Claude Code, GitHub Copilot, Codex and Cursor compared side by side: how they work, their strengths, limitations and where each one fits best.

From Prompt to Agentic Task

How a task becomes a clearly scoped assignment - with the right context, verifiable intermediate steps and a defined outcome.

Skills and Agents as a Team Standard

Capture recurring ways of working as executable building blocks, maintain them together, and make them usable independently of any one machine or person.

MCP as the Interface to Your Own Environment

How AI agents access tools, data sources and internal systems in a controlled way - and what actually happens behind the scenes.

Multiple Agents Working Together

Split up tasks, isolate workspaces, and merge separately produced results back into a shared codebase.

AI for Code Comprehension and Review

Make sense of existing and unfamiliar code, investigate changes, and use AI as an extra pair of eyes in the review process.

How the training works

Apply It Directly to Your Own Project

Short conceptual input alternates with hands-on work on your own project. You try out new ways of working immediately, get feedback, and review together with the trainer what works - and where the AI goes off track.

The result is more than new knowledge: the training produces skills, agents and conventions your team can keep using afterwards.

  • Apply directly - to tasks from your own project
  • Review together - understand results and spot mistakes
  • Make it stick - embed reusable workflows across your team
IDE terminal: Claude Code asks for approval before creating a test file
Screen showing the Claude start page: “Meet your thinking partner”

Who is this training for?

For development teams who want to integrate AI tools into their everyday project work professionally, transparently and responsibly.

  • Developers with some initial AI experience who want to move beyond occasional, ad hoc use
  • Experienced AI users who want to systematise their way of working and develop it further across the team
  • Tech leads and architects who want to establish shared standards for using AI

Prerequisites: Programming experience in at least one language. No specific prior AI knowledge is required.

Your benefits from the AI training

  • Clarity on the Tool Landscape

    You know which tool fits which task - no more guessing between competing vendor promises.

  • A Setup That Lasts

    Instead of a handful of tricks, you take away your own skills, agents and conventions that your team can keep using.

  • Control, Not Guesswork

    You understand when AI can be trusted to work independently, and stay in control of the code at every step.

  • Hands-On, First-Hand Experience

    You try out every tool on your own project instead of just watching a demo - and take away only what actually works.

Luka Breitig

Your trainer

Luka Breitig - AI-Assisted Coding Trainer.

Luka trains developer teams in AI-assisted coding and agentic workflows, working as a practitioner who uses the same tools every day in his own product. He works with developers as well as with non-technical business teams, from the first use of these tools all the way to building custom agents and MCP servers.

AI-assisted coding isn't a side project at tangible concepts - it's a core part of our everyday project work, and that experience flows directly into this training.

More trainings by Luka Breitig

AI training: format & organisation

  • Duration

    2-3 days

  • Format

    In-house company training, on-site or remote

  • Prerequisites

    Programming experience in at least one language

  • Language

    German or English

  • Dates

    Training dates are arranged to suit your schedule.

  • Group Size

    4-10 participants per training

Kathi Asel

Your contact: Kathi Asel
I'm happy to answer your questions and find the right setup for your in-house training with you.

Ready for Professional AI Coding?

Want to train your whole team? This in-house training is tailored to your context - on-site or remote. Use the contact form to tell us your preferred date and a few key details. We'll check availability and send you a tailored proposal for the training.