Thesis AI-Powered Knowledge Sharing for Embedded Software Team

The rapid emergence of AI-powered development tools, coding assistants, and knowledge agents is changing the way software teams work. These tools have the potential to improve development eAiciency, code quality, onboarding, and knowledge sharing. However, it remains unclear which tools provide the most value in an industrial software development environment and how company-specific knowledge can be eAectively integrated.

Problem Statement

Software teams often rely on fragmented documentation, coding guidelines, and expert knowledge that may be diAicult to access or maintain. While AI tools oAer new possibilities for knowledge retrieval and development assistance, their benefits, limitations, and integration requirements within a professional software team are not yet fully understood.

Methodology

The work will involve a market study of existing AI tools, the development of evaluation criteria, and the implementation of one or more proof-of-concept solutions. DiAerent approaches for providing company-specific knowledge to AI systems will be investigated, such as document repositories, retrieval-augmented generation (RAG), and custom AI assistants. The solutions will be evaluated based on usability, accuracy, maintainability, security, and practical value for the development team. This research aims to evaluate the applicability of AI tools and agents within the application software team. The objectives include: - Evaluating available AI development and knowledge-assistance tools - - - - Identifying benefits, drawbacks, and risks of diAerent solutions Investigating methods for integrating team-specific documentation, coding guidelines, and development practices into AI agents Exploring approaches for maintaining and sharing AI-based knowledge across the team Assessing the impact on developer productivity, onboarding, and software quality

Expected Outcomes

- - - - - Overview and comparison of relevant AI tools for software development teams in an industrial environment Recommendations for AI adoption within the application software team Proof-of-concept implementation of a team-specific AI assistant Guidelines for managing and sharing AI-based knowledge Assessment of benefits, limitations, and implementation eAort

Who are we looking for?

A motivated thesis student with a hands-on mindset, strong problem-solving skills and an interest in industrial automation, robotics and product development.

Relevant skills

Control Engineering +++

Software Engineering ++++

What we offer you?

• A place in an enthusiastic, young organisation with the necessary ambitions
• The necessary freedom and the opportunity to take initiatives
• Location Office : Lokeren
• Satellite office in Berchem ( Antwerp )

Unsolicited representations by third parties (recruitment agencies, headhunters, ...) of CVs via mail and/or telephone for our vacancies are considered as direct applications where no compensation is provided to the third party. Any T&Cs from these third parties will not be accepted unless upon signature of the T&Cs by a person in charge of HR. Candidates remain registered in the system for 12 months and cannot be proposed again during this period.