Integrating AI fine-tuning into your development process can revolutionize how your Scrum team works, improving code quality, boosting productivity, and delivering exceptional business value. This blog post will guide Scrum Masters, Product Owners, and key sponsors through implementing AI fine-tuning in a practical, jargon-free way. We will also discuss the benefits of transitioning from large language models (LLMs) to specialized fine-tuned distilled models for better performance and cost efficiency. Understanding AI Fine-Tuning AI fine-tuning involves customizing pre-trained AI models to meet specific needs. For a software development team, this means training the AI to generate code that adheres to your company’s standards, performance metrics, and security requirements. By integrating this into your Scrum workflow, you can produce higher-quality code faster and more efficiently. Step-by-Step Implementation 1. Set Clear Objectives For the Scrum Master and Product Owner: Defi...