Burak Erol
Ambassador for AI & System of Work at XALT
While much was said about Rovo in Barcelona, the real magic is happening one level down: Forge and the Teamwork Graph are becoming the platform on which AI features become not just “nice to have” but business-critical. This article deliberately does not focus on the Rovo headlines already summarised elsewhere, but shows how teams can now quickly leverage robust value with Forge – from data integration to governance to reusable agent capabilities.
Atlassian Intelligence: AI in everyday life, not as an add-on
Rovo does not stand alone. Atlassian Intelligence runs through Jira, Confluence and Loom, and demonstrates its value in concrete everyday scenarios:
- Jira Task Breakdowns automatically break down complex initiatives into manageable work packages.
- Audio summaries in Confluence make content consumable on the go.
- Video-to-Issue in Loom turns screen recordings directly into structured Jira tickets – including acceptance criteria.
These are not gimmicks, but features that make a noticeable difference in day-to-day work. When a 10-minute Loom recording automatically becomes a complete issue, it changes the workflow.
Atlassian links knowledge, work and people in a shared data model: the Teamwork Graph. For developers, this means: apps can read and populate this model – which forms the basis for context-rich experiences, search results and AI automations beyond Jira, Confluence & Co.
Forge: The foundation for extensions
While Rovo receives much of the attention, Forge works quietly in the engine room. The platform provides, among other things, access to the Teamwork Graph – the connected data model across issues, people, projects and their relationships. On this, capabilities can be built that act context-aware across products.
What this means for organisations
- Custom Intelligence: Developers create custom Rovo Skills that access proprietary systems. This allows Rovo to answer questions about your CRM, access legacy data, or orchestrate workflows across multiple platforms.
- AI-Assisted Development: Rovo Studio and Forge enable a new development mode: describe requirements in natural language, generate scaffolding, and harden and extend the technical implementation.
- Cross-Product Automation: Forge drives processes across Jira, Confluence & Co. – with Reasoning over the Teamwork Graph for smarter, context-aware operations.
Rovo Studio + Forge: Low-Code meets “Production-Grade”
Rovo Studio unites the key building blocks for creating solutions (Agents, Automations, Assets, Hubs, Apps). This allows power users to quickly build working prototypes – and development teams make these production-ready with Forge (including policies, secure secrets, monitoring/observability, and audits).
Architecture patterns with quick impact
1. Bring in your own context (Teamwork Graph)
Integrates external systems such as CRM, PLM, Data Warehouse, or DMS. This makes their data available in search, chat, and agents – answers are based on your business reality, not just Atlassian data.
2. Skill library instead of chaos
Start with a few tested skills and clear permissions (e.g., issue creation with acceptance criteria, asset lookup, approvals). Version, monitor, roll out – and curate centrally.
3. From Studio prototype to Forge hardening
Transfer successful flows to Forge and add secrets management, rate limits/retry, audit trails, feature flags, and rollbacks. This makes prototypes robust and revision-safe.
4. Smart Links as UI glue
Use context-rich link previews to save clicks and increase adoption – particularly in Confluence collections and project overviews.
Assets as a platform building block
An important signal: Assets is no longer “just” a CMDB in the JSM context, but is designed as a platform-wide building block. This makes object data (configurations, devices, contracts, master data) searchable, automatable, and AI-capable – across products, usable via Forge and Rovo. For XALT customers with complex IT landscapes, CIs, or relationship models, new transparency and control options open up.
Conclusion: Treat “Assets” as an object layer for AI flows (e.g., “Find available laptops with M-Chip, location X, warranty < 3 months”). Agents can act on this basis, not just respond.
Operational readiness: Security, permissions, visibility
To move from prototype to production, these guardrails should be established to ensure security, access control, and operational transparency.
- Governance & permissions: Defines who can create agents and skills, which access rights (scopes) are required, and which actions require confirmation.
- Visibility & activation: Ensures that Rovo and Studio are visible and enabled for the right user groups – including verification of plans/editions.
- Monitoring & compliance: Sets up logging, metrics, audit events, and fallback/rollback early on, so you can trace processes and roll back quickly if needed.
The convergence: Lower barriers, faster innovation
The key is not a single feature, but the convergence:
- Non-developers build automations in natural language.
- Developers deliver deep integrations faster – on a shared AI context.
- Teams extend capabilities without waiting for vendor roadmaps.
This democratisation is crucial because every organisation functions differently. Winners adapt tools to their reality – not the other way around.
What this means for your organisation
If you are an XALT customer or considering our solutions, these developments enable the following:
- Immediate results: The general availability of Rovo means that AI features are accessible today, not in some distant future. We support you in enabling these features and integrating them into your workflows.
- Tailored solutions: With Forge and Rovo Studio, we can develop custom AI agents and automations that address your specific challenges, whether it is automating service requests, extracting insights from documents, or connecting distributed systems.
- Strategic advantage: Organisations that introduce AI-supported workflows early achieve cumulative benefits. Early adopters actively shape how these tools evolve, while competitors watch from the sidelines.
The XALT advantage
At XALT, we do not just implement Atlassian products; we design intelligent Systems of Work. As a partner for AI & System of Work, we support you in:
- assessing which AI capabilities deliver immediate ROI in your context,
- designing workflows that effectively leverage Rovo, Intelligence, and Forge,
- building bespoke solutions with our deep Forge development expertise, and
- empowering your teams to extract maximum value from these AI capabilities.
The convergence of Rovo, Atlassian Intelligence, and Forge is more than a minor update. It marks a fundamental shift in how work is done – from manual to intelligent, from isolated to connected, from reactive to proactive.
Ready to discover how Rovo, Atlassian Intelligence, and Forge can transform your organisation? Contact XALT to discuss your AI-augmented future. Our team of Atlassian consultants and Forge developers helps you move from possibility to reality.
