Code, Co-Creation & Engineering

This profound shift brings new opportunities and challenges:

• If every stakeholder can instantly generate a UI prototype, what becomes of traditional sprint planning?
• If large-scale code transformations and refactoring become push-button easy, does that change the role of testing, architecture or technical debt?
• If AI systems generate and interpret code at scale, how can human developers effectively review, validate, and maintain it?

We believe the industry is approaching a tipping point – and the CCE is where forward-looking organizations come to anticipate and shape that future.

At the competence field Code, Co-Creation & Engineering (CCE), we are dedicated to rethinking the fundamentals of software development in an era where AI, automation, and instantaneous prototyping are reshaping what is possible. Our mission is to explore how development methods, tools, and mindsets must evolve when traditional bottlenecks like user interface design, documentation, and refactoring become near-instantaneous, and AI-assisted co-creation is the new norm.

1. Beyond agile: rethinking software development processes and methods

Agile revolutionized development by emphasizing iterations, feedback, and working software. But when UI prototypes and backend scaffolding can be created on the spot -often by stakeholders themselves- the premise of iteration changes. We investigate:

• What replaces Agile when feedback cycles are measured in minutes, not weeks?
• Can design and development finally be unified in a single flow?
• How do roles change when product owners can generate working prototypes?
• How do development processes adapt when human review of AI-generated code becomes a critical quality and accountability step?

2. Testing: the new core activity

As generation and transformation become commoditized, testing may emerge as the true core of development. If you can build anything instantly, what ensures it is correct? We explore:

• How will testing evolve to remain meaningful in AI-generated systems?
• Will testing take over traditional tasks like requirements verification and architecture validation?
• How can integration and system tests be executed fast enough to support real-time quality assessment?
• How can abstract, and possibly formal, specifications guide code generation and verification?

3. Human/AI Co-Creation: preparing codebases for the future

As LLMs and code-interpreting agents become standard collaborators, our code needs to serve a new audience - not just humans, but machines that read and write code. We study:

• What does "machine-readable documentation" really mean?
• Can codebases become self-describing to support autonomous analysis, debugging, and evolution?
• How can we ensure that AI generated code is still understandable und accessible to human developers?
• How do we assess and improve the quality, reliability, and security of third-party libraries and repositories that AI systems draw from and reuse?

Whether you're modernizing legacy systems, building new AI-integrated products, or simply wondering what software engineering will look like in five years, we want to hear from you. At CCE, we do not just anticipate the future of software - we build it.

• Joint research projects: Long-term collaborations structured around shared questions and mutual benefit.
• Potential Analysis: Facilitating structured collaboration between researchers, developers, and managers.
• Experimental tool development: Prototyping and evaluating tools that embody new principles of software development.
• Empirical studies: Observing teams and workflows to gather evidence about emerging practices.

Where our expertise creates value:

• Software product companies seeking to shorten time-to-market without compromising quality.
• Tool vendors looking to embed AI into their platforms and improve their testing workflows.
• Enterprises rethinking software governance, documentation, and code quality at scale.
• Small and Medium-sized Enterprises modernizing legacy systems, developing new AI-integrated products, or aiming to shorten their time-to-market while maintaining high quality.
• Startups disrupting how software is written, tested, or maintained.

The world of software is changing faster than ever. Code generation, AI-assisted refactoring, and AI agents are rewriting the playbook. At CCE, we believe excellence in code starts not just with better tools, but with better questions.