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Artificial Intelligence (AI) plays a key role in modern software development, signifi-cantly transforming developers’ design, writing, testing, and maintaining their code. Currently, programmers at various levels have integrated AI-based tools into different stages of the software development life cycle (SDLC), from code generation to deploy-ment. This study analyzes the impact of these technologies on professional practice, identifies the most used tools, and proposes best practices for the responsible adoption of AI, aiming to optimize its implementation efficiently and ethically. As part of this study, a methodological artifact was developed to guide the structured formulation of prompts, functioning as a model to enhance the precision and utility of AI-generated outputs. This artifact was validated through three proof-of-concept use cases (SQL queries, backend development, and deployment in AWS), demonstrating its potential as a knowledge base for teams seeking to incorporate AI tools systematically into their workflows.