AI Training for Software Developers

For development teams that want to do more than just try out GitHub Copilot, Claude Code, Cursor, and others—they want to integrate them productively into their daily workflows.

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✓ 80+ AI experts ✓ 25+ years of technology expertise ✓ ISO-certified ✓ Made in Germany

AI-powered coding is more than just auto-complete

AI is currently transforming software development more fundamentally than any framework shift in the last twenty years. Tools like GitHub Copilot, Claude Code, and Cursor are no longer just auto-complete gimmicks, but full-fledged pair programmers that handle entire refactorings, test suites, and architectural sparring sessions—if used correctly. But that’s exactly where the problem lies: Many development teams are far from making full use of these tools in their day-to-day work because they lack a structured introduction.

Our AI training courses for software developers bridge this gap. We work with your developers on their actual code—not on demo repos. They learn how to clearly convey context to the AI, where code review steps must remain human-led even with AI, and which workflows actually accelerate development. And just as important: where AI tools reliably produce incorrect results, which licensing and IP issues are changing, and what code should never be fed into an LLM.

Engineering teams that fail to systematically integrate AI tools today are leaving significant productivity gains on the table. Those who integrate them without guidance risk code quality issues and legal complications surrounding open-source licenses and customer IP. We’ll work with your team to find the right balance.

What Participants Will Learn

The training starts with the fundamentals —how an LLM works, how to effectively control prompting and context—and leads to productive workflows that your team can put to use right away. The focus: Beyond Vibe Coding —building maintainable, secure, and efficient software using agents and specification-driven development, rather than relying on the AI’s gut instinct.

How does an LLM work?

Easy to Understand, No Math Required: Tokens, Transformers, Context Windows, and Why Models Hallucinate. The mental model that helps you accurately assess how these tools behave in everyday use.

Prompting in Practice

Strategically balancing consistency and creativity. Which tools (system prompts, temperature, few-shot examples, roles) achieve what—and when should you use which option?

Context Engineering

Provide the model with the necessary knowledge at the right time: repo conventions (CLAUDE.md, .cursorrules, copilot-instructions.md), RAG setups, and MCP servers for tool access.

Tool Setup & Workflow Integration

GitHub Copilot, Claude Code, Cursor, JetBrains AI Assistant — how to effectively integrate them into your IDE and CI. We'll show you which tool is best suited for which task and how they work together.

Code Review with AI

Automating preliminary PR reviews, architecture sparring in pull requests, generating security notes. Which reviews can AI handle—and which ones absolutely must remain in human hands?

Refactoring & Migration

Document legacy code, improve test coverage, and systematically tackle framework upgrades (.NET Framework → .NET 8, AngularJS → Angular, etc.) using AI.

Beyond Vibe Coding

Build maintainable, secure, and—above all—efficient software using agents (Agentic Skills) and specification-driven development—from a Vibe hack to a productive engineering workflow.

Prompt Evaluation

Systematically evaluate prompts and AI-generated code—not based on “feels right,” but on measurable criteria: test sets, evaluation frameworks, and regression checks for your AI-powered workflows.

Data Protection & the EU AI Act

An overview for guidance—we provide guidelines, not legal opinions: which code is allowed in which LLM, differences between Enterprise and Free plans, and obligations for software companies.

Bring Your Own Code

We train using your team’s actual repository—not demo projects. The focus is on real-world problems.

Tool-agnostic

GitHub Copilot, Claude Code, Cursor, JetBrains AI — we’ll show you which tool is best suited for which task.

Senior Trainer

Training for senior developers based on real-world prodot experience. They discuss on an equal footing.

Polyglot

.NET, Java, TypeScript, Python, Go, Rust — our trainers are experts in your language and framework.

Hands-on, not theory

The training is hands-on. Your developers should bring their own computers, their configured IDE, and, ideally, a live project. We train using real code, not contrived examples—because the problems that AI tools struggle with in everyday use simply don’t appear in tutorials.

Standard format:

Duration: 1–2 days, depending on prior knowledge and depth of content. Can be split into two days within the same week or two sessions spaced 4 weeks apart (recommended for learning transfer)
Group size: Max. 10 participants for intensive hands-on work
Delivery: Remote (via Teams/Zoom with screen sharing for each participant), on-site at your location, or hybrid
Training Certificate: Each participant receives a certificate of attendance detailing the covered content—relevant for Article 4 of the EU AI Act and your company’s documentation requirements.
Prerequisites: Personal work laptop, set-up IDE (VS Code, JetBrains, Cursor—all acceptable), access to at least one AI coding tool (Copilot license or Claude API access—we can provide temporary access if necessary)
Bring your own code: Ideally, bring a running project (anonymized or public repositories are also acceptable)

Tool-Specific Training — Cross-Link to Our Specialized Training Courses

This page provides a cross-tool overview of AI-assisted coding. If you need in-depth knowledge of a specific tool, we offer dedicated specialized training courses:

Claude Code Training — The Anthropic CLI for autonomous coding workflows. Focus on agent-based tasks, MCP servers, and confidential repos.
Microsoft Copilot Training — GitHub Copilot, Copilot in Visual Studio, and the Microsoft 365 stack. Focus on .NET environments, Azure integration, and enterprise compliance.

If you’re unsure which tools are relevant for your team, we’ll clarify that during our initial consultation. A common approach: Start with cross-tool training, followed by in-depth training on the specific tools your team actually uses.

Schedule a free initial consultation now

Your contact person

Daniel Ludewig

sales@prodot.de

0203 3965080

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Frequently Asked Questions About AI Training for Development Teams

Can our team use our own production code during the training?
Which IDEs and AI tools are covered in the training?
What happens to our code when it is sent to an LLM?

This very question is covered in the training. We’ll go through each tool one by one: What data goes where? Does the code remain with the provider (use of training data)? Which enterprise licenses exclude this (GitHub Copilot Enterprise, Claude API Business)? Which clauses in customer NDAs are relevant? You’ll leave the training with a clear understanding of which code is allowed in which tools.
Can we split the training into several sessions or sprints?
What qualifications must our developers have?
We already have Copilot licenses—so why do we still need training?

prodot as a Partner for AI Developer Training

prodot has been a software development company for over 25 years. We have around 80 IT experts at our Duisburg location who develop software for medium-sized clients every day—now largely with AI support. Our trainers come from this day-to-day development practice, not from the training room.

Firsthand AI coding experience. We use GitHub Copilot, Claude Code, Cursor, and JetBrains AI in our own projects. We know these tools from a user’s perspective—including the pitfalls that never show up in tutorials.

End-to-End. If, after the training, you want to set up workflows in CI/CD, code review processes, or your own MCP servers, we can guide you through that as well—from training all the way to a production-ready AI workflow.

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