PERSPECTIVE
AI in the software development lifecycle
A practical approach to closing the workflow gap
Organizations are already using AI to accelerate coding, requirements, and testing, yet many are not seeing proportional improvements in delivery outcomes. This perspective examines why task-level gains often fail to improve the broader software delivery workflow and explores practical approaches for reducing ambiguity, improving handoffs, shifting validation earlier, and creating more predictable delivery across the SDLC.
What you'll learn
- Identify where the workflow gap creates ambiguity and rework
- Understand how AI improves the flow of work across the SDLC
- Explore how consistent requirements, ticket structure, and earlier validation support delivery
- Measure AI impact using workflow and delivery metrics rather than individual productivity
- Recognize common adoption pitfalls that limit system-level improvement
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