Training course · Agentic Coding · Game Development

Agentic Coding for Game 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 Game Developers” is designed for roles such as Gameplay programmers working in Unity, Unreal Engine or Godot, Indie developers and small studios and Technical artists and tools programmers and shows step by step how to use Agentic Coding productively, safely and transparently in Game Development – from the fundamentals to advanced workflows.

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.

Game development combines real-time performance, complex state logic and creative iteration like few other fields. AI coding assistants and agents help teams working in Unity, Unreal Engine and Godot prototype gameplay systems faster, automate editor tooling, write shaders, analyse performance bottlenecks and refactor long-lived codebases. Small indie teams gain time for game feel and content, while larger studios make tooling and pipelines more efficient. The domain also raises particular questions: frame budgets, garbage collection spikes, multiplayer synchronisation and the rights to generated content. In this course you learn to use AI purposefully within your engine workflow, from C# scripts in Unity and C++ and Blueprints in Unreal to GDScript in Godot, while keeping quality and playability firmly in view.

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?

  • Gameplay programmers working in Unity, Unreal Engine or Godot
  • Indie developers and small studios
  • Technical artists and tools programmers
  • Engine and performance specialists
  • Developers of serious games, simulations and interactive applications

Typical challenges we address

  • Intense iteration pressure when prototyping new game mechanics
  • Performance issues such as frame drops, memory spikes and long load times on target platforms
  • Tightly coupled legacy gameplay code that makes extensions difficult
  • Repetitive editor and pipeline tasks that eat into creative time

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.
  • Prototype game mechanics and editor tools much faster with AI while staying in control of the architecture.
  • Analyse and optimise performance issues with AI support based on real profiler data.
  • Apply AI agents in a way that suits Unity, Unreal Engine or Godot and understand the legal questions around generated content.

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: Game Development
  • Prototyping gameplay mechanics
  • Automating editor tools
  • Developing shaders
  • Analysing performance
  • Refactoring gameplay code
  • Implementing multiplayer logic
Module 7 Data protection, quality & transfer to daily work
  • Unreleased games, engine source code and assets are valuable intellectual property: you learn to respect the licence terms of engines and AI services, clarify rights to generated code and content, understand platform rules on disclosing AI-generated material and process player data in line with the GDPR.
  • 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

Prototyping gameplay mechanics

Generate working scripts for movement, combat systems, inventories or dialogue systems from a game description, exposing parameters that designers can fine-tune directly in the editor.

Automating editor tools

Write custom editor windows, import scripts, asset and level validation and batch operations that reliably handle recurring tasks in Unity, Unreal or Godot. Asset errors surface earlier.

Developing shaders

Describe visual effects and have them implemented in HLSL, Shader Graph, Unreal materials or Godot shading language, with explanations of the maths and notes on mobile performance.

Analysing performance

Interpret profiler output, identify allocations in the update loop and expensive physics or rendering calls, and propose optimisations such as object pooling, batching or data-oriented design.

Refactoring gameplay code

Turn monolithic manager classes into component-based, event-driven structures, model state machines cleanly and add tests for gameplay-critical logic. Game feel is preserved while new features become easier to add.

Implementing multiplayer logic

Design network synchronisation, client-side prediction, authoritative server logic and remote procedure calls, analyse typical causes of desyncs and build anti-cheat considerations into input validation. Latency and packet loss can be simulated.

Possible hands-on projects

Level validator

An editor tool that checks scenes for missing colliders, wrong layers, unused assets and naming conventions and produces a report with clickable links.

Dialogue editor

A small tool that lets writers build branching dialogue visually and export it as JSON for the engine to load at runtime.

Playable mini prototype

A complete small prototype, such as an arena shooter or puzzle level, with controls, scoring and simple enemy behaviour. It helps validate game feel early.

Prerequisites

You have several years of development experience, are confident with Git, testing and CI, and ideally have already used AI coding tools. You have programming experience in C#, C++ or GDScript and have worked with a game engine such as Unity, Unreal Engine or Godot.

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

Unreleased games, engine source code and assets are valuable intellectual property: you learn to respect the licence terms of engines and AI services, clarify rights to generated code and content, understand platform rules on disclosing AI-generated material and process player data in line with the GDPR.

Suggested dates

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 Salzburg Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Bremen Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Online Request
  • Wed, 10 February 2027 – Thu, 11 February 2027 Augsburg 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.

Which engine is the course designed for?

The course is engine-agnostic and covers Unity with C#, Unreal Engine with C++ and Blueprints, and Godot with GDScript or C#. You can complete the exercises in your preferred engine. For each, we show how to provide project structure, engine APIs and conventions as context so the AI assistant delivers fitting solutions.

Can AI-generated code and content be used in commercial games?

For code this is generally possible, provided the AI service’s terms allow it and you plan for review and licence checks. For artwork, audio and text, the legal situation and individual storefronts’ disclosure requirements need attention. We give a practical overview in the course, though it does not replace legal advice.

How much does “Agentic Coding for Game 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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