Agentic Coding training online

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

All 32 Agentic Coding courses can be booked as interactive live online training – with a trainer, exercises and breakout sessions.

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.

Every course is also available as live online training: with a real trainer, interactive exercises, breakout rooms and a shared lab environment. All you need is a laptop, a headset and a stable internet connection – join from anywhere in Germany, Austria, Switzerland and beyond.

Suggested dates – Online

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

Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
Wed, 9 December 2026 – Thu, 10 December 2026 Online Request
Wed, 13 January 2027 – Thu, 14 January 2027 Online Request
Tue, 26 January 2027 – Wed, 27 January 2027 Online Request
Mon, 8 February 2027 – Tue, 9 February 2027 Online Request
Thu, 18 February 2027 – Fri, 19 February 2027 Online Request

Core content of every Agentic Coding course

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

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

Agentic Coding courses in Online

Agentic Coding · Munich Agentic Coding · Salzburg Agentic Coding · Berlin Agentic Coding · Augsburg Agentic Coding · Hanover Agentic Coding · Bremen Agentic Coding · Stuttgart Agentic Coding · Kaiserslautern

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