DtC Framework
A framework for the user-centered path from idea to code.
The Design-to-Code framework structures the collaboration between humans and AI in building digital products and services.
It helps teams fully define requirements, make decisions visible, and develop solutions with AI step by step. This way AI doesn't become a black-box developer, but a controllable part of the design and development process.
What is the Design-to-Code framework?
The Design-to-Code framework structures everything needed to build a digital application with AI. It guides you from the first idea through requirements and design to implementation in code — structured, iterative, and with clear checkpoints for humans and AI.
What does that look like in practice?
At the core of the framework are two building-block canvas models: low fidelity and high fidelity. They help concretize requirements step by step and prepare them for AI-powered implementation. The framework is independent of any single tool or LLM and works across different AI and software ecosystems.
The key difference to other approaches:
It's not the tool that determines the process. The method determines how humans and AI work together.
What we offer
Corporate Training+
You're responsible for a project and want to help teams successfully build AI-powered, user-centered applications? In our Design-to-Code trainings, your team learns all the methods and tools you need. We tailor all content to your needs and your organization's context.
Workshops+
Built on a real project from your everyday work. Learn to apply the Design-to-Code framework to build a digital application with AI that is user-centered, scalable, and — above all — safe.
Our workshopsDtC Community+
As the DtC community, we stand for a shift in how work gets done through AI. Many AI Product Engineers from our workshops have already set out to improve team collaboration using the DtC framework. In the DtC community, we learn with and from each other, take on different perspectives, and find allies on our mission to close the AI competence gap. Curious?
Join usAI needs more than good models: it needs good requirements and good implementation.
Good AI-powered product development needs both: a well-founded, human-centered foundation and a concrete bridge to implementation. Our comparison table shows how different AI frameworks and the Design-to-Code model (DtC) make that connection. See the comparison table
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