SAAF AI Agile Sprint Backlog

Time to Complete: Recurring sprint cycle (1–2 weeks recommended)

Purpose: Define, track, and deliver AI-specific tasks during agile sprints. Supports iterative development, experimentation, ethical review, and validation of AI-powered features.

Why Use This?

AI work is different from traditional software: results are probabilistic, outputs need interpretation, and risks are nuanced. This backlog template helps product, data, and engineering teams work transparently and iteratively with AI—including prompt refinement, bias audits, and human-in-the-loop review.

Backlog Setup

Each sprint backlog item includes:

• Story or task name

• AI-specific acceptance criteria

• Tags for AI category (e.g., generation, summarization, AI Agent)

• Review requirements (e.g., human validation, bias check)

Sample AI Agile Backlog Table

Task / Story	Description	AI Category	Acceptance Criteria	Assignee	Status
Summarize project comment threads	Use AI tool to summarize 5+ long comment threads	Summarization	90%+ rated helpful by users; under 3 edits required per summary	QA Lead	To Do
Build onboarding assistant agent	Create AI agent using HR docs and tone guidelines	Virtual Agent / LLM	Answers top 5 onboarding FAQs accurately; reviewed by HR team	AI Engineer	In Progress
Run bias audit checklist	Evaluate AI-generated responses for tone, fairness, and representation	Governance / QA	No biased language detected; meets tone and inclusivity standards for 3 personas	Ethics Lead	To Do
Prompt refinement session	Test and improve prompts for content generation or summarization	Prompt Engineering	At least 2 versions tested; improved satisfaction based on user feedback	UX Writer	In Progress
Draft red flag escalation process	Document protocol for escalating harmful or misleading AI outputs	Governance	Reviewed by Ethics Lead; published in enablement resources	Compliance	To Do
Set up AI feedback collection form	Create form to collect user feedback on AI tool performance	Feedback / QA	80% completion rate; insights shared during sprint review	PM / Ops	Done
Human-in-the-loop checklist	Define when human validation is required for AI-generated content	Ethics / Review	Checklist created and reviewed with at least 2 stakeholder teams	PM / QA Lead	In Progress

Sprint Tips for AI Work

Best Practice	Why It Matters
Include acceptance criteria for accuracy, bias, and usability	Output quality is variable—set clear success thresholds
Track prompt iterations as discrete stories	Prompts are code—track them like you would functions
Log user feedback in each sprint	AI usability is user experience; collect early and often
Plan bias/ethics review for every public or external feature	Build trust and compliance into the sprint process

Sprint Rituals to Add

Agile Ceremony	Add These AI Elements
Sprint Planning	Define “Definition of Done” for AI outputs
Daily Standup	Share prompt testing results, issues with AI output
Sprint Review	Demo AI outputs, share what was accepted or flagged
Retrospective	Discuss surprises in output, trustworthiness, team comfort

Completion Checklist

• AI tasks and stories added to sprint backlog

• AI-specific acceptance criteria defined

• Bias audit and user feedback items included

• AI outputs scheduled for human review where needed

• Success metrics agreed upon (e.g., output accuracy, user edits, satisfaction)