Is your instance ready for Rovo Max Mode? Our Team '26 AI debrief

[#1]

The biggest talking point out of Team '26 was autonomous execution. With Rovo’s new Max Mode, AI agents can now execute multi-step action plans across your apps, like building Jira epics and drafting Confluence pages.

But there’s a catch: Rovo relies entirely on your Teamwork Graph. If your company context is cluttered, unclassified, or stuck in bottlenecks, what then?

At AppFox, we’ve rebuilt our suite to provide the clean, secure infrastructure your instance needs to thrive with Rovo at the helm. 

1. Tackling Jira performance issues & migration technical debt

Max Mode requires an optimized database. If you are experiencing Jira performance issues or navigating Jira scaling, a cluttered instance will break down Rovo's autonomous execution plans.

With Optimizer for Jira, we’ve moved to continuous Goal-Based Tracking to address technical debt in Jira and keep an eye on the work Rovo is out doing for you. By setting automated instance health targets and using Custom Field Merging tools, you can easily clean up issues in bulk like needing to delete unused labels. If you are building a Jira cloud migration plan, Optimizer DC lets you execute necessary Jira maintenance so you don't migrate legacy clutter into Rovo's new workspace.

2. Automating and integrating Confluence data classification for audit

Atlassian has opened up the Teamwork Graph to external AI agents. This makes instant confluence data classification critical - AI must be restricted from surfacing sensitive or protected information, in order to keep you audit-ready.

To strip away the manual toil of trying to add labels to multiple pages or in bulk, we’ve added REST API support and extensible Rovo skills into Compliance for Confluence. These are designed to help you automatically roll out page classification at enterprise scale via integrations, and provide third party tools with the information they need when deciding if a given user should be able to see the data classified in a given page.

3. Quality-assuring your documentation to maximum effect

If AI agents pull data from technical documentation that is perpetually stuck in manual, out-of-date review loops, your automated project momentum completely stalls.

As a comprehensive document lifecycle management platform, Workflows for Confluence uses a drag-and-drop builder alongside templates to map highly custom approval paths and flag document expiry. Whether managing a knowledge system or an SOP process in Confluence, it auto-applies clear version control to ensure your content is accurate, your metadata is clean and that Rovo is only pulling verified, up-to-date context.

The Bottom Line

AI agents can only remove our administrative toil if we feed them trustworthy data. Whether you are streamlining your Confluence audit log or polishing instance health, make sure the context you're providing to Rovo is representative of the work you want it to perform!