Machine learning is on the rise and is having an impact on the software development life cycle (SDLC) in a number of ways. This marriage of ML and DevOps is sometimes refered to as autonomous DevOps. In this session, we'll discuss:

• A brief intro to the concept of autonomous DevOps
• The comparisons and contrasts with the shift to low-code/no-code
• The landscape of various projects and tools that are achieving the vision (things like GH CoPilot), across every phase of the SDLC and the role of large language models, etc.
• The future and the art of the possible (e.g., What types of skills will developers require in five or 10 years?)