top of page
milvius.systems_transparent.png

Smart. Secure. Simply ahead.

Bunte Glasobjekte
Head of Software Development for secure software engineering, software architecture, DevSecOps, and AI-driven software development in enterprise environments.

"Implementing AI in software development introduces too many risks."

​

Is it actually possible to increase efficiency? Initial studies already show that experienced software developers can experience up to a 20% drop in speed.

Engineering leadership must address both technical considerations:

​

  • Determining which AI platforms to trust with source code
     

  • Ensuring maintainability and readability
     

as well as organizational and strategic challenges:

  • Preventing a loss of core engineering skills
     

  • Maintaining balance within the team
     

  • Navigating technological dependencies

Engineering leadership establishes the framework:
 

  • Clear policies on how and when to utilize AI tools
     

  • Guidelines for source code development and testing
     

  • A "Human-in-the-Loop" principle to prevent deviations from established standards
     

Team culture can also be leveraged to drive AI adoption:
 

  • Training and mentoring on AI utilization (Senior developers guiding Juniors)
     

  • Regular, open knowledge-sharing sessions on hands-on experiences
     

  • Collaborative workshops to define and refine the toolset

bottom of page