Thoughts on AI and Agile Development

AI-Enhanced Agile DoD: Improving Agile Workflows with AI

In Agile software development, the Definition of Done (DoD) is critical for ensuring that teams share a clear understanding of when a task or user story is fully complete. It’s not just about checking boxes but ensuring the deliverable meets certain quality standards, is testable, and can be released into production with confidence. A solid DoD serves as a benchmark for delivering high-quality software that aligns with both customer expectations and regulatory requirements. Yet, despite its importance, defining and managing a robust DoD can be challenging. ...more

September 19, 2024 #AI #agile #definition of done #software development #compliance
Improving Acceptance Criteria in Agile with AI: Best Practices for Quality and Efficiency

In Agile software development, Acceptance Criteria play a crucial role in defining the conditions under which a user story or feature is considered complete and functional. These criteria act as a shared understanding between stakeholders and development teams, outlining the expected behavior of the system under different conditions. Well-written acceptance criteria provide clarity, prevent scope creep, and make testing more straightforward. ...more

September 14, 2024 #AI #agile #acceptance criteria #software development #automation
Agentic AI for Autonomous Project Management: Revolutionizing Workflows

There’s something thrilling about autonomy. The idea of a machine, not simply a tool to be used, but a participant in the decision-making process of a complex system like project management, carries with it a mix of awe and uncertainty. It’s not about replacing human roles but rather augmenting them—allowing artificial intelligence to take on an agentic role where it acts with a degree of independence and adaptability. Welcome to the world of agentic AI. ...more

September 13, 2024 #AI #agile #project management #autonomous systems #decision-making #agentic