AI Backlog for Jira

Defining Work Topics

• Select your industry and review the predefined list of work topics.
  We encourage you to fine-tune the groups and items.

Choose what the AI should analyze

• Select Jira fields the AI can use to understand the work and your patterns.
  
  AI Backlog for Jira doesn’t “guess” based on one field. It builds recommendations from the same signals your team uses when grooming and planning. That’s why selecting the right Jira fields matters: it tells the AI what evidence to consider when it categorizes issues, understands effort, and drafts sprint candidates.

Discover and set your strategy (how the AI should plan)

• Your team already has a “strategy”, even if it’s not written down.
  
  Over time, you’ve developed patterns in how you prioritize work (bugs vs. features), how you estimate, what you tend to pull into sprints, and what usually gets deprioritized. Strategy Discovery is the step where AI Backlog for Jira learns those patterns from your historical Jira data and turns them into a clear, editable planning baseline.
  
  What “strategy” means in AI Backlog for Jira
  ‍In the app, your strategy is a set of planning rules that guide decisions like:what tends to be prioritized first (e.g., production bugs > improvements > new features), how different work types are treated (Bug vs Story vs Task), what “small enough” or “too large” looks like for your team, how to balance sprint composition across topics (stability, customer value, tech debt, etc.)

Sprint Templates (repeatable planning presets)

• Sprint Templates let you save your most common sprint-planning approaches as reusable presets.
  
  Instead of rewriting instructions every time you generate a sprint, you can pick a template (or create your own) and instantly guide the AI toward the outcome you want.

Indicators (spot risks early and improve sprint drafts)

• Indicators add lightweight “signals” next to issues in your backlog so you can quickly see potential risks before they turn into surprises during planning.
  
  They also help the AI generate cleaner sprint drafts by avoiding items that are likely to waste time or get stuck.
  On this screen you can enable/disable each indicator and fine-tune how it behaves.

Accessing AI Backlog for Jira

• Select your industry and review the predefined list of work topics.
  We encourage you to fine-tune the groups and items.

Set team capacity

• Tell the app how much you can realistically take on this sprint.

Generate a sprint draft

• The Generate Sprint dialog is where you ask AI Backlog for Jira to produce a sprint draft.
  
  Think of it as a fast way to get to a good starting point for your planning session. You can still review, adjust, and finalize everything before starting the sprint.
  
  Describe Your Sprint
  This text box lets you give the AI lightweight context for this specific sprint, beyond your general strategy and templates. It’s ideal for short-term constraints and goals, like:
  - “Prioritize stability and production incidents.”
  - “Keep items under 5 points and avoid risky work.”
  - “Include at least one customer-facing improvement.”
  - “Balance frontend and backend work.”
  - “Focus on onboarding and billing this sprint.”
  
  The goal isn’t to write a long spec, just the kind of guidance you’d normally say out loud during planning.
  
  Use the fields you selected in Fields Selection
  The AI can reliably apply rules based on fields you previously chose to analyze (priority, issue type, story points, labels/components, and any custom fields you selected in the settings).
  This makes your prompt much more powerful, because you can reference your team’s real planning signals.Examples:
  - Customer / Account (dropdown/custom field): “Prioritize work items for customer Foo Inc.”
  - Component: “Focus on Billing and Authentication components.”
  - Labels: “Prioritize items labeled security and regression.”
  - Issue type: “Pull bugs first, then small stories.”
  - Story points: “Prefer items ≤ 5 points.”
  
  

Review sprint balance in seconds