AI Coding Training
Empowering developers requires more than buying a subscription for a shiny AI-enhanced coding tool or sharing a few exemplary prompts. Successful AI-enhanced coding entails a fundamental mindset shift and new best practices. It is essential for developers to understand their instrumental role in driving efficient AI-based development, moving from traditional coding to AI-augmented collaboration.
Our AI “Dibe Coding” training initiates this transformation, teaching teams to effectively integrate AI into everyday practices. Instead of random trial-and-error, learn a structured process to delegate work with AI—turning tools like Copilot, Cursor, Windsurf, or Theia IDE into real productivity boosters. This tool-agnostic training covers context engineering techniques, steering AI output systematically, tailoring agentic behavior, and rigorous AI output validation.
This online training allows you to study anytime, anywhere at your own pace.
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AI-Native Software Engineering Methodology
Embracing AI-native software engineering means rethinking how software is developed. Deploying a successful AI-native methodology requires more than just crafting captivating ‘vibe coding’ prompts.
We help you establish and adapt AI-augmented processes that consider the entire software lifecycle. Whether integrating proven approaches like our Dibe Coding methodology or tailoring existing frameworks, we support you in defining processes that include context engineering, agent design and delegation, and hybrid workflows between humans and AI – from requirements analysis to code review and quality assurance phases. To achieve full efficiency and effectiveness, this methodology must be customized to fit your specific domain, project contexts and tool environment. Our consulting includes best practices for incorporating AI into software engineering lifecycles and evolving processes over time.
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AI-enhanced Tool Support
Tools are essential enablers of AI-native software engineering workflows. Whether you select an existing commercial tool such as GitHub Copilot, Cursor, adopt open source solutions such as Continue or the AI-powered Theia IDE, or create some tailored tooling, we’re here to help. We assist in evaluation, selection, potential adaptations, getting the best AI tools for your developers – and making sure the tool support fits your software engineering practices, integrates with your development infrastructure, and can be evolved in the future. From lightweight AI-enhanced UIs to full-featured AI agents, MCP servers and AI-powered IDEs, we support the selection, the development and deployment of your ideal solution.
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Also see our Services for Building AI-enhanced Tools and IDEs »
Blogs and Insights on AI-Native Software Engineering
- Dibe Coding: The Developer-First Approach to AI-native Development
- Delegating Code Tasks to AI: From Challenge to Breakthrough
- Theia AI: The Open Framework for Building AI-native Custom Tools and IDEs
- AI-powered Theia IDE: The Open Framework for Building AI-native Custom Tools and IDEs
- Why Good Context Matters for Efficient AI Assistance in Tools and IDEs
- The Rise of Closed Source AI Tool Integrations
Let’s build your AI-native software engineering future together
Let’s take the next step together — from vision to execution, from training to practice, from tool selection to customization and integration.
Methodology & Assessment
We help define what AI-native software engineering means for your context — from processes and artifacts to validation and collaboration.
Training & Coaching
Empower your users with the knowledge, tools, and confidence to work productively with AI assistants and workflows.
Evaluation & Evolution
We help you to continuously evaluate AI workflows, evolve your AI-native practices, and adopt new technical innovations and trends.
Tool Integration
From existing platforms to fully custom solutions, we support the tooling you need to make AI-native software engineering real.






