Rovo Agents: How To Use and Transform Your Jira Workflows

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Jira has become the backbone of planning and delivery for software, business, and support teams alike.

As those teams scale and spread their work across many tools, the friction shows up in the same places: scattered information, slow hand-offs, and too much manual coordination. Rovo addressed those pain points by adding an AI layer across Atlassian products and connected apps, so teams can find what matters, learn from past work, and act without leaving their flow. At the center of this model are Rovo Agents -assistants that don’t just answer questions but also take action on your behalf.

This guide walks through the essential concepts behind Rovo, how Agents work, where they fit next to Jira automation, and pragmatic steps to design your own Agents in the Studio App - plus concrete examples and tips to make adoption smooth. Let's get into it.

Why scattered information slows decisions

Work now lives everywhere: Jira work items, Confluence pages, Slack threads, email, and third-party systems. Searching across all of that, re-creating context, and validating what’s current burns time and attention. As the team grows, those small frictions compound: less learning from prior work, more status chasing, and slower decisions.

Rovo as the smart layer across Atlassian

Rovo sits across Jira, Confluence, and connected tools to move teams from “hunting for answers” to “acting with context.”

• Find - ask in natural language and Rovo searches across Atlassian products and integrated platforms (e.g., SharePoint, Figma) to surface the exact work items, pages, or updates you need - respecting your existing permissions.
• Learn - knowledge cards, semantic search, and conversational chat make it easy to explore company context, onboard faster, and reason from prior work.
• Act - through automation, Agents, and deep Atlassian integrations, Rovo turns insights into actions - assigning work items, posting summaries, or triggering the next step.

Atlassian Intelligence vs Rovo

Both are Atlassian AI, but they operate at different layers.

• Atlassian Intelligence lives inside products (Jira, Confluence, Trello, Bitbucket). It speeds up micro-tasks—drafting, summarizing, suggesting child work items, and providing writing assistance.
• Rovo works across products. It unifies search and chat, and powers Agents that stitch together information and actions across systems.

Use Atlassian Intelligence when you need help within the current tool; use Rovo when you need to coordinate across tools and teams.

The components of Rovo

• Rovo Search - one semantic search across Atlassian and connected sources (e.g., Google Drive, Slack).
• Rovo Chat - ask questions naturally and receive answers with context - and, when appropriate - proposed next actions.

• Agents - task-oriented assistants that can automate workflow: analyze, summarize, route, update, and escalate.
• Studio App - a no-code builder to create, customize, and manage your own Agents - define their role, knowledge sources, and permitted actions.

Under the hood, these capabilities are powered by the Atlassian Teamwork Graph - a live map of people, content, and relationships across your system of work. Let's skip into it then.

Inside the Teamwork Graph

Think of the Teamwork Graph as a contextual fabric: it knows who collaborates with whom, which work items connect to which pages, and where artefacts live.

That’s why Rovo can answer questions like, “What’s the latest on our website redesign?” by pulling the relevant work items, Confluence pages, and even related discussions - rather than returning a list of loosely related documents. The result is fewer hops, better answers, and actions that respect the real relationships in your work.

Connectors: breaking down app silos

With Rovo Connectors, you bring external tools into view: Asana, ServiceNow, DocuSign, Zendesk, Google Docs, SharePoint, and more. Once connected, Rovo Search and Agents can discover and act across those sources. Instead of toggling between apps, your assistant becomes the single place to query, summarize, or move the next step forward - while observing the permissions of the person invoking it.

Rovo Agents ready to use and customize

Rovo comes with 20+ out-of-the-box Agents and supports custom ones via the Studio App. A few you’ll use early:

• Work Item Planner - breaks large initiatives (projects, epics, work streams) into actionable steps so planning turns into execution.
• Issue Organizer - curates and updates work items, moving items into sprints, linking to epics, cleaning stale entries, so backlogs stay healthy.
• Blocker Checker (for automations) - spots keywords that indicate a blockage and marks the work item as “Blocked,” or guides you to wire the rule if needed.
• Bug Report Assistant - coaches reporters to include the details triage actually needs, improving quality and speed to resolution.
• Readiness Checker - verifies if a work item meets your team’s “definition of ready” (clarity, completeness, estimate) and suggests what’s missing.

You’ll also find templates for OKRs, social posts, release notes (from work items), PRD drafting/review, and more. All of these can be adapted without code.

How to create Rovo Agent 

You don’t need to be technical to design an Agent.

1. Open the Studio App from the app switcher and go to Agents → Create.
2. Define the Agent’s purpose in plain language (its role and boundaries).
3. Click Generate Conversation Starters - starter prompts that appear when users open the Agent in chat.
4. Choose knowledge sources (toggle access to Jira, Confluence, Figma, etc.) to control what the Agent can “see.”
5. Select permitted actions (e.g., comment, summarize, notify, escalate) in Jira, Confluence, and Jira Service Management.
6. Name and describe the Agent clearly, then Create to publish.

You can share Agents via a profile link (users only see what they already have access to), duplicate them to branch into variants, and update instructions, sources, and actions as needs evolve.

Examples: using Agents inside Jira automation

Agents and Jira automation complement each other - rules handle predictable triggers; Agents bring context and guidance.

Example 1 — Readiness Checker
A rule invokes the Readiness Checker when a new work item is created or enters a pre-work state. The Agent evaluates completeness, clarity, auditability, and estimation (tailored for Task and Story), then leaves a comment with what’s missing so the team can fix it before the next step.

Example 2 — Bug Report Assistant
On creation or when a work item is labelled as a bug, the Agent prompts for reproduction steps, environment, and expected vs actual behavior, improving triage quality and shortening time to fix.

Both examples rely on out-of-the-box Agents and show how to extend rigid rules with intelligent checks and helpful guidance.

Tips for effective Rovo Agents

Before you build, decide the Agent’s job: notify, summarize, triage, automate, or analyze. Start small: one use case per Agent, then iterate.

• Write instructions in clear, natural language; specificity beats cleverness.
• Define inputs/outputs (what it needs, what it should produce: a comment, a summary, an alert).
• Test in a sandbox or low-risk project with realistic data.
• Tune schedules and notifications to avoid noise.
• Produce human-readable output: concise summaries, bullet points, or tables.
• Document what the Agent does, when it runs, and who owns it.
• Review usage and feedback regularly; refine or retire as needed.

Humans + AI: collaboration model

Remember that agents don’t replace the craft of engineering, product, or support - they remove friction.

With Agents in place, you spend less time digging through Jira to find the right work items, less time pushing status across tools, and more time making decisions with shared context. The system improves as you use it: instructions evolve, outputs get sharper, and hand-offs become routine rather than exceptional.

Wrap-up

Rovo ties together search, chat, and Agents on top of the Teamwork Graph and your connected apps. The result is a practical step beyond traditional, rule-only automation: faster answers with context and actions that move work forward. Start with one high-friction workflow - readiness checks, bug intake, release prep - and use the Studio App to stand up an Agent that proves the value quickly. Expand from there with confidence and governance.

What’s the first workflow where a Rovo Agent would save your team the most time? Happy to receive your insights!