AI Automation with Forge and Rovo

Imagine building not just one, but two fully functional software apps in a single afternoon. Recently, at a hands-on workshop, dozens of developers managed exactly that using Atlassian’s latest platforms: Forge and Rovo. These new tools are transforming how teams create custom automations and integrate artificial intelligence (AI) into their Atlassian workflows. In this blog post, we’ll explore what Forge and Rovo are, why they’re generating so much excitement, real examples of what you can build with them, and best practices for getting started.

Understanding Atlassian Forge

Atlassian Forge is a cloud-based app development platform designed to simplify building extensions and custom apps for products like Jira and Confluence. Forge takes care of the heavy lifting: it handles server infrastructure, authentication, and scaling. This frees developers to focus on writing their app’s logic and features. In the past, creating a custom integration for Atlassian often meant deploying your own servers or managing AWS instances. Forge eliminates that burden by providing a secure, serverless environment where your code runs safely inside Atlassian’s cloud.

From a developer’s perspective, Forge offers a streamlined experience. It comes with a Command Line Interface (CLI) toolkit that makes it easy to create, test, and deploy apps right from your terminal. Forge also provides pre-built templates for common app scenarios. For example, if you want to build a new Jira issue panel or a Confluence content action, you can start with an official template and have a basic app structure in seconds. This means you can get a “Hello World” app up and running almost immediately, then gradually add functionality from there. Because Forge handles all the backend concerns, the apps you build are by default secure and compliant with Atlassian’s standards. In short, Forge dramatically lowers the barrier to extending Atlassian products, letting teams innovate faster without worrying about infrastructure.

Introducing Atlassian Rovo

The second half of the equation is Atlassian Rovo, a new AI-powered automation platform that brings artificial intelligence capabilities into the Atlassian ecosystem. Rovo is like having an AI teammate embedded in your tools. It enables features such as intelligent search, AI chat assistants, and proactive agents that can take action on your behalf. With Rovo, you can ask questions in natural language and get answers or insights drawn from your organization’s data in Jira, Confluence, and other connected apps. It can even present information as “knowledge cards,” which are bite-sized summaries of topics or projects, so you don’t have to dig through multiple pages to find what you need.

One of Rovo’s most powerful aspects is its ability to execute actions through AI agents. Imagine opening your Jira Service Management queue and having an AI agent that can automatically categorize or prioritize incoming tickets, or a chatbot that can pull up relevant knowledge base articles when you ask a question in Confluence. Rovo’s agents can interact with Atlassian products using built-in intelligence and your own custom prompts or logic. All of this happens without you leaving your normal workflow; the AI comes to you where you’re working, whether that’s in a chat, a search bar, or a side panel inside Jira. By leveraging Rovo, teams can reduce manual effort and let the AI surface what’s important or even perform certain tasks automatically. In essence, Rovo injects a layer of smart automation into everyday work, turning raw data into actionable knowledge and freeing up humans to focus on higher-level problem solving.

Real-World Examples and Use Cases

What kinds of things can you actually build when you combine Forge’s development ease with Rovo’s AI capabilities? Here are a few examples that demonstrate the potential:

• Quick Jira Extension in Minutes: With Forge, it’s feasible to create a simple Jira app in a very short time. For instance, developers at a recent workshop were able to write and deploy a “Hello World” Jira issue panel within minutes. This basic app might just display a custom message or field, but the key point is how little effort it takes to go from idea to a live extension running in Jira Cloud. It shows that even those new to Forge can start delivering value almost immediately.

• AI-Powered Issue Analysis: Going a step further, you can build an intelligent Jira assistant by combining Forge and Rovo. One team project involved creating a custom “issue analyzer” agent. Using Forge, they built a backend service that pulls data from Jira. They then used Rovo’s AI capabilities to analyze that data in real time. The result was an AI agent that could scan through Jira tickets and automatically highlight trends and insights. For example, it might detect that many issues in the last sprint were related to a specific component or suggest which types of tasks consistently cause delays. This kind of agent acts like a smart project analyst living inside Jira, giving managers and team leads instant answers to questions they might otherwise spend hours investigating.

• Intelligent Knowledge Base Helper: Rovo isn’t limited to Jira. Another potential use case is enhancing a Confluence knowledge base with AI. Imagine a Confluence page where users can ask a question in plain English and get an answer synthesized from various pages and updates. By writing a Forge app that embeds a Rovo-powered chat or search widget into Confluence, you could create an intelligent knowledge base assistant. Ask something like “How do I onboard a new developer?” and the assistant could pull information from onboarding checklists, HR policies, and training pages to give you a concise, helpful answer. This saves time and ensures employees find the right information when they need it.

These examples barely scratch the surface. The combination of Forge and Rovo unlocks countless possibilities for custom AI automation within Atlassian’s products. Whether it’s automating support ticket triage, generating reports and summaries, or building conversational helpers for your documentation, if you have a repetitive task or a question that eats up time, chances are a Forge app plus a Rovo agent could tackle it.

Best Practices for Building with Forge and Rovo

Diving into a new development platform can be daunting, but there are proven strategies to make your journey smoother. Here are some best practices our experts recommend when starting out with Forge and Rovo:

• Start with simple projects: It’s best to begin with a minimal use case to familiarize yourself with the basics. For example, create a small Forge app that adds a button or displays “Hello World” in Jira, or try a basic Rovo search query in Confluence. Getting that first success, no matter how simple, will build your confidence. Once the basic functionality is working, you can gradually add more complex features or logic on top of it.

• Leverage Forge templates and samples: Don’t reinvent the wheel. Atlassian provides ready-made Forge app templates and example code for common scenarios. Using these templates as your starting point can save you a lot of setup time. You’ll have a working base that follows best practices, allowing you to focus on the unique parts of your idea rather than boilerplate setup. Similarly, look at Atlassian’s sample Rovo use cases to understand how to structure prompts or integrate an AI agent. It’s often easier to modify an example than to start from nothing.

• Utilize serverless and built-in features: Forge is inherently a serverless platform, and it’s wise to fully embrace that model. Whenever possible, use the out-of-the-box Forge features for things like storage, functions (compute), and API calls instead of spinning up external services. The more you rely on Atlassian’s managed infrastructure, the less you have to worry about maintenance, security, or scalability. This also holds true for Rovo: take advantage of Atlassian’s built-in AI and data connections rather than trying to build your own AI from scratch. By leaning on what’s provided, you reduce complexity and points of failure in your app.

Following these practices can help you avoid common pitfalls and accelerate your development process. The Atlassian developer community is also a great place to learn from others’ experiences. In fact, the tips above come directly from those who have already built successful Forge and Rovo apps.

Getting Started and Next Steps

Excited to try Forge and Rovo for yourself? You don’t need to attend a special event to start exploring these tools. Atlassian offers plenty of resources to help you on your way:

• Forge Learning Path: Atlassian’s official guided tutorial series that walks you through building your first Forge app, step by step. It’s a perfect place to start if you’re new to cloud app development.

• Rovo Documentation and Demos: Atlassian has published documentation and demo videos showing how to create AI agents, use Rovo Search, and integrate chat into your workflows. These resources will help you grasp the art of prompting Rovo and connecting it with your data.

• Community and Events: Consider joining the Atlassian Community online forums or attending Atlassian Community Events focused on Forge and Rovo. These communities are full of developers and Atlassian Solution Partners eager to share knowledge, answer questions, and showcase what they’ve built. It’s a fantastic way to learn from real examples and get help when you’re stuck.

• Hands-on Help from Experts: For personalized guidance, consider working with an Atlassian Solution Partner like Atlas Bench. Our experts have extensive experience with Forge and Rovo, and can help identify high-impact automation opportunities in your specific environment, setting you on the right path with a tailored workshop or hands-on session.

Each of these steps can bring you closer to mastering AI automation on Atlassian’s platform. The key is to start experimenting. Even a small proof-of-concept can demonstrate the value and spark ideas for what to tackle next.

Wrapping Up

Forge and Rovo represent a significant leap forward in how Atlassian users can streamline their work. By combining a plug-and-play development platform with powerful AI capabilities, Atlassian has empowered teams to solve problems in ways that simply weren’t possible a couple of years ago. Custom apps and intelligent agents that used to require extensive resources to build are now within reach for even small developer teams.