7 items
AIBA and QA are an important couple to turn requirements into test scenarios. This article explains how to coordinate with QA, classify severity/priority, triage defects, and manage regression scope before release.
Duy Tran11 minAIA good handoff helps Dev/QA understand the requirements correctly before the sprint starts. This article provides a handoff checklist, Three Amigos agenda, examples of converting acceptance criteria into test scenarios and how to manage open questions.
Duy Tran11 min
AINew BAs often learn BABOK, SDLC, Scrum, BRD, SRS, and user stories in pieces, so it's easy to get confused. This article maps the whole thing into a practical work flow from idea to release.
Duy Tran12 min
AIAI stories are harder to estimate than regular features because they depend on data readiness, model iterations, and experiment uncertainty. A guide to adapted Planning Poker for AI work, 3-point estimation, spike stories, and how to communicate uncertainty to stakeholders.
Duy Tran11 min
AIBacklog refinement consumes more BA hours than anything else — yet it's also where AI can help the most: duplicate detection, story splitting, AC suggestion, and dependency mapping. A practical guide to integrating AI into your refinement workflow without losing control.
Duy Tran11 min
AIUAT for AI features isn't like traditional UAT — you test not just business logic but AI output quality, edge cases, bias, and whether users actually trust the AI. Complete guide from UAT plan, business readiness checklist to go/no-go decision framework for BA.
Duy Tran10 minAIPoorly written user stories are the root cause of 80% of "spec mismatch" bugs and sprint rework. This guide teaches BA to write stories using the INVEST standard, acceptance criteria in BDD Given/When/Then format, and use AI to automatically detect missing edge cases.
Duy Tran11 minNo results found