Atlassian Forge enables developers to build AI-powered apps with direct access to large language models (LLMs) through Amazon Bedrock. In this session, we'll take an in-depth look at how this integration works and what it means for developers building Runs on Atlassian apps.

Amazon Bedrock is AWS's fully managed service that provides access to high-performing foundation models from leading AI companies through a single API, with comprehensive data protection and privacy capabilities. We'll dive into how Forge's LLM API provides secure, managed access to these foundation models without requiring AWS credentials or infrastructure management.

Whether you're building your first AI-powered Forge app or exploring how managed AI services can accelerate development, you'll gain the technical insights and practical knowledge to leverage foundation models from Forge.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

In less than two quarters, SpotOn built an adoption flywheel, champions, automations, impact, and expansion to scale Atlassian Rovo across 1,000+ employees in Sales, R&D, Operations, and IT. Hear how SpotOn moved from early prototypes that automated Jira intake and knowledge summarization to a full enablement program with measurable productivity gains tied directly to their business impact. We will share the lessons learned, outcomes delivered, and the impact Rovo is driving across the business.

Key takeaways

• Learn how to structure an AI adoption flywheel to drive rapid scale
• See real-world AI workflows that deliver measurable efficiency
• Understand how to connect Rovo usage metrics to business outcomes

Your Assets data captures the unique domain of your business – people, services, systems, and more. In this session, learn how to use that data and Rovo Studio together to build smarter agents that understand and act on your organization’s objects. See how these agents can simplify and power flexible workflows and automations that help your teams move faster.

Key takeaways:

• Discover how to create custom Rovo agents that understand and act on your unique Assets data.
• Explore examples of how these agents can boost your team’s productivity and simplify complex workflows and automations.

AI has made every role on the product team faster—but speed alone hasn’t solved the harder problem of deciding what to build. When PMs, designers, and engineers each use disconnected AI tools, teams generate more output but less shared direction, leading to fragmentation and rework. In this talk, we'll explore how to preserve idea intent across surfaces, tools, and roles so teams don’t just move faster, but move together.

Key takeaways:

• Why AI-driven speed is increasing fragmentation—and how disconnected tools create more output but less alignment across PMs, designers, and engineers
• Why there’s no single starting point anymore—ideas can begin in a PRD, a Jira ticket, a prompt in Claude Code, or on the Figma canvas, and every context switch risks losing intent
• How to use Figma Make to go from a prompt or PRD to an interactive prototype built on your design system, then bring it onto the canvas to explore alternate paths and align on what to build
• How to make Connectors for Jira and Confluence keep product thinking and execution in sync, so context travels with the work instead of getting lost across tools
• How Figma MCP creates a live connection between code and design—bringing real UI code into Figma as editable layers and sending structured design context (components, tokens, variables) directly into engineering workflows
• Why round-tripping between design and code is critical to maintaining intent as ideas evolve into production

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Convincing your organization to standardize on a new way of working can feel like an uphill battle, especially when every team already has its favorite tools. But what if you had a clear, repeatable playbook to win over even the toughest skeptics?

We’ll introduce the SMART framework for how to internally sell Teamwork Collection across your company, whether you’re trying to gain executive buy-in, secure budget approval, or drive adoption among business teams. You’ll leave with practical language and examples to help your team adopt Teamwork Collection as the platform for AI-powered collaboration across Jira, Confluence, and Loom.

Key takeaways:

• A SMART framework for selling Teamwork Collection internally, from executive sponsorship and budget approval to broad team adoption
• Ready-to-use language, stories, and visuals to reframe objections like “we already have too many tools” into a compelling platform vision
• Concrete, successful plays so Teamwork Collection becomes the default way your org plans, communicates, and delivers work

Companies invest in strategic initiatives but lack visibility into both sides of the equation: what they’re spending on, and what they’re getting in return. Costs are scattered across systems, benefits live in assumptions, and neither connects to the actual work being delivered.

Funds in Strategy Collection closes that gap: forecast labor and non-labor costs, assign budgets, track actuals against your baseline, and plan and measure benefits alongside costs, all connected to real work in Jira. With Rovo AI surfacing financial insights, leaders get the full picture – cost, benefit, and ROI – live and connected to the work, not stale in a spreadsheet. See it live in this session.

What does work look like when Rovo agents and automation support every step of delivery? In this “day in the life” session, follow a business request from intake through planning, development, and delivery. See how Rovo agents improve requirement quality, assist with work breakdown, and keep teams aligned with intelligent automation.

From business users to project managers and developers, learn how AI-driven workflows streamline collaboration, tracking, and decision-making – helping teams move faster while staying focused on what matters most.

Key takeaways:

• See how Rovo agents support collaboration across roles and teams.
• Understand the end-to-end impact of agents and automation across delivery.
• Learn practical patterns for intelligent work breakdown, tracking, and communication.

Strategic portfolio management is evolving as organizations adopt hybrid, agentic workforces and execute work across an expanding set of execution platforms, including Jira. Portfolio managers spend hours in status meetings just to understand what’s happening across the portfolio. The planning struggle is real.

In this live demo, we introduce Loop, Tempo’s vision for the next evolution of SPM. Loop connects signals from systems of work and continuously evaluates whether initiatives remain aligned with strategy.

You’ll see how teams can surface portfolio risks earlier, explore what-if scenarios to test plan changes, and shift from manual reporting and updates to continuous portfolio orchestration—enabling faster, more confident decisions across the organization.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

As organizations work to bring humans, agents, and automation together, teamwork is getting even more complex. If your AI strategy feels like a collection of one-off experiments layered onto disconnected tools and siloed knowledge, join Atlassian leaders to see how Teamwork Collection brings together Jira, Confluence, Loom, and Rovo into a connected foundation for human-AI collaboration at scale.

Key takeaways:

• See new AI capabilities in Jira, Confluence and Loom in action – surfacing context, reducing friction, and accelerating outcomes, whether for cross-team initiatives or everyday project work.
• Master the human-AI workflows that reduce coordination tax and ensure your teams – and agents – are driving outcomes, not just adding noise.
• Explore how leading customers are using Teamwork Collection to operationalize AI, turning fragmented work into competitive advantage.

Modern IT teams are overwhelmed by alert noise, fragmented tools, and constant pressure to resolve incidents faster. In this session, you’ll see how Jira Service Management, integrated with Rovo and third-party observability partners like New Relic and Dynatrace, streamlines incident response by auto-enriching incidents with telemetry, AI recommendations, and Teamwork Graph context – so teams can investigate and resolve issues without tool-switching. We’ll also highlight 24 Hour Fitness’s IT operations story and how they use Jira Service Management to cut alert noise, speed up resolution, and improve post-incident learning. Join this session to learn concrete best practices for accelerating incident resolution through AIOps and integrated, third-party observability data. 

Key takeaways:

• Practical ways to cut alert noise, correlate related issues, and accelerate triage with AI-guided investigation and reduced tool-switching
• How to auto-enrich incidents with real-time telemetry, AI-driven recommendations, and Teamwork Graph context directly in Jira Service Management
• How 24 Hour Fitness is using Jira Service Management and Atlassian’s observability partnership with Dynatrace to accelerate root cause analysis

What happens when enterprises move beyond AI experiments and become an AI-native organization? Join some of the fastest-growing enterprises as they share how agentic AI is becoming part of everyday work for their teams. Hear how they’re using Atlassian Rovo to create autonomous agents that reduce operational overhead, improve data quality, and enable faster, more predictable decision-making while saving teams meaningful time and effort.

Key takeaways:

• See real customer use cases for agentic workflows across Jira, Confluence, and connected tools.
• Learn how teams measure adoption and prove value while keeping humans in the loop.
• Take away practical patterns for scaling agentic AI responsibly and predictably.

Migrating thousands of users and deeply embedded workflows to the cloud is no small feat — especially when strict compliance requirements are non-negotiable. In this session, Utpal Pandya, Director of Global Engineering Services at Qualcomm, shares a candid, firsthand account of how Qualcomm successfully migrated from Data Center to Cloud with the support of Atlassian's FastShift program.

Designed to help enterprises move faster and with greater confidence, Atlassian FastShift provided Qualcomm with the expert guidance, structured framework, and hands-on support needed to navigate this complex migration. From early planning and stakeholder alignment to large-scale execution, the FastShift team played a pivotal role in de-risking the migration, accelerating timelines, and ensuring continuity across deeply integrated workflows — all while meeting stringent compliance requirements.

Utpal walks through the real-world strategies that drove success, the obstacles encountered along the way, and the critical lessons learned that can help others navigate similar transformations.

Key takeaways:

•  Benefits of building a phased migration approach using FastShift’s structured framework, tooling, and hands‑on support to accelerate migration timelines and adoption.
• Establishing governance requirements and compliance controls to de-risk each migration phase.
• Driving change management tactics and post-migration support that sustains user adoption and confidence.

ITSM transformations are complex, and ServiceNow to Jira Service Management migrations often cost more than planned, take longer than expected, and feel hard to control, especially when organizations have tight timelines to get off of ServiceNow. But what if there was a way to mitigate complexity and risk, reduce cost, and speed up transformation?

Isos Technology has years of experience and expertise helping clients overcome blockers and make the switch to Atlassian. In this session, we’ll showcase how we’re accelerating the transition from SNOW to JSM for clients with a proprietary, purpose-built Forge app that uses AI-assisted mapping to transform data in flight.

Key takeaways:

• Learn best practices for migrating to Atlassian as your ITSM platform
• See a demo of our SNOW to JSM Migration Assistant app
• Hear pain points, wins, and outcomes from a real client use case

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

LPL Financial is undergoing a full‑scale transformation of how teams plan, execute, and report work – standardizing across Jira, Confluence, Focus, Talent, Rovo, Loom, and Jira Product Discovery as a connected system of work. Rather than “rolling out tools,” LPL has designed an integrated user lifecycle experience across the Atlassian suite that eliminates manual reporting, creates consistent habits, and keeps teams rowing in the same direction.

In this session, Camila Haselwood, VP, Delivery Enablement from LPL Financial will share how her team sold a cohesive platform vision to leadership, executed a phased transformation – layering on Focus, Talent, and Rovo as needs emerged while keeping teams inside a single Atlassian ecosystem. She’ll walk through concrete examples of what worked (and what didn’t) in their rollout and change‑management approach, including how they built an army of internal champions to multiply buy‑in across the business.

Attendees will leave with practical patterns for designing a system that can scale and evolve with your organization – without sacrificing user experience or team autonomy.

Key takeaways: 

• Learn how LPL designed an integrated, end-to-end Atlassian experience across Jira, Confluence, Loom, and Rovo.
• Leave with a concrete playbook for phased rollout and change management, including building internal champions and sustaining adoption.
• Learn practical patterns to create a scalable, flexible system of work that reduces manual reporting while preserving team autonomy.

Moving from Atlassian Data Center to cloud isn’t just a technical migration, it’s a strategic business decision. And in enterprise ecosystems, the real risk isn’t data volume. It’s identity fragmentation, app sprawl, custom scripting, compliance exposure, and mission-critical workflows that cannot break.

In this session, Seibert Solutions demonstrates why a structured cloud migration assessment is strategically essential. Drawing from real customer engagements, we’ll show how to evaluate your Data Center environment through three key lenses: business impact, risk, and cost and effort required. You’ll learn how to surface hidden complexity early and transform migration planning into a clear, leadership-ready decision framework.

With deep expertise in scripting, custom development, and Atlassian Forge app development, Seibert understands how apps are built, what rebuilding or rationalizing them in cloud truly requires, and where modernization creates long-term value.

Key takeaways:

• How to evaluate cloud readiness through business impact, risk, and cost
• Common blockers and best practices identified through real customer assessments
• A practical assessment framework that supports confident executive decision-making

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

Enterprise R&D teams are drowning in fragmented work scattered across Jira, Confluence, GitHub, and the rest of the toolchain - a challenge that is particularly acute for long-established global enterprises like Mazda, where decades of products, processes, and institutional knowledge must evolve without compromising safety, quality, or speed.

In this session, Mazda will showcase their Defect Context Hub: a custom defect management solution built on the Atlassian platform using Teamwork Graph and Rovo. You’ll learn how Mazda uses Atlassian’s platform to ship higher-quality, safer code faster—and how you can apply the same patterns in your own environment.

Key takeaways:

• The role of cloud in Mazda’s connected development transformation. Learn why cloud migration is critical for Mazda to adapt to automotive development trends, and the criteria they used to guide their decisions.
• Unify fragmented data with Teamwork Graph. See a real-world walkthrough of a custom connector Mazda built for Codebeamer—a requirements gathering tool—letting them consolidate data across Codebeamer, Confluence, Jira, and Bitbucket.
• Learn how to build custom Atlassian solutions with the Teamwork Graph API. Explore custom views Mazda created in Jira to give developers the full context for any defect—all in one place.
• Walk away knowing how Teamwork Graph makes agents context-aware. Learn how Mazda leverages Rovo and Teamwork Graph to deliver permission-aware insights directly into developer workflows, so teams can act faster and with confidence.

Ever wonder how the team behind Jira actually runs Jira for their own marketing? Learn how Jira’s Head of Marketing uses Jira and Trello to the limit every day to get sh*t done. No theory, no generic best practices—just the real boards, workflows, and rituals that keep campaigns moving, stakeholders aligned, and priorities crystal clear.

See how to structure work from big bets down to daily tasks, when to choose Jira vs. Trello, and when to leverage Confluence and Loom to keep everyone informed without drowning in meetings. We’ll walk through how to manage intake, approvals, launches, and retros in one connected system, plus where automation and AI help the team move faster without losing control.

You’ll leave with a concrete, copy‑and‑paste system you can adapt for your own team, whether you’re running scrappy experiments, global launches, or anything in between.

Key takeaways:

• A behind-the-scenes look at the actual Jira + Trello setup used by Jira’s own marketing team to plan, execute, and report on work
• Practical patterns for structuring campaigns, managing intake and approvals, and keeping stakeholders aligned using Jira, Trello, Confluence, and Loom
• Copy‑ready board layouts, workflows, and rituals you can duplicate to help your team move faster with more clarity and less chaos

Migrating from Data Center to cloud isn’t just a technical shift – it’s a transformation of how teams work. In this fast-paced theater session, hear the real-world story of how one enterprise customer successfully made the move to Atlassian Cloud while keeping their most critical apps, workflows, and business processes running smoothly.

We’ll walk through the challenges they faced, from complex environments and app dependencies to workflow continuity and how they tackled them head-on. Learn how a strategic partnership with Appfire helped streamline the migration, modernize workflows, and ensure their Atlassian ecosystem didn’t just survive the move, but improved because of it.

You’ll leave with practical insights, proven approaches, and a clear blueprint you can apply to your own cloud journey no matter where you’re starting from.

This is a sponsored session. Badge scanning is optional. By having your conference badge scanned, you are opting in to be contacted by the sponsor. You will be subject to the sponsor’s communications and privacy policies and must contact them directly if you later wish to change your preferences.

AI is rewriting the rules of employee service – is your team ready? Go beyond the hype and see how AI agents can deliver faster, more personal support while reducing load on your teams.

In this session, we'll deep dive into the art of the possible with Rovo Service, Service Collection's powerful AI agent for employee support, including how to unlock accelerated request resolution, seamless self-service, and intelligent employee onboarding workflows. We’ll demo top use cases and walk through practical, step‑by‑step ways to deploy AI agents for faster response times, less manual work, and better outcomes – so your team can focus on higher‑value work.

Whether you’re just starting your AI journey or looking to scale existing initiatives, you’ll leave with actionable patterns, guardrails, and next steps to navigate the evolving landscape of AI-powered employee service with confidence.

Key takeaways:

• Clear mental model of AI agents in service management: What AI agents are (and are not) good at in employee support scenarios
• Real Rovo Service use cases and pro tips: Get the wheels turning on ways your team can use AI and learn the ins and outs of how to take Rovo Service usage from pilot to best practice
• A practical deployment playbook: Step‑by‑step guidance to roll out AI agents, including data, configuration, and guardrails

Most teams know the feeling. A leader asks for the latest roadmap, and suddenly you're rebuilding in slides something that already lives in your planning tool — and by the time it lands in their inbox, it's stale. 

In this Atlassian-on-Atlassian theater session, Gosia Kowalska, Head of Product Data Center, at Atlassian, pulls back the curtain on how product teams inside Atlassian use Jira Product Discovery to plan, prioritize, and communicate their roadmaps across the organization. Drawing on real setups from teams including Atlassian's own AI group, the session shows how a single "control tower" board becomes the source of truth, and how tailored views for engineering, design, legal, and leadership are all derived from it — no duplication, no stale documents. Finally, the session looks at what comes next: how teams are beginning to use Rovo agents to automate JPD updates, surface customer insights for prioritization, and generate stakeholder-ready content on demand.

Key takeaways:

• How to build a control-tower board in JPD and create audience-specific views for leaders, engineers, designers, and legal from a single source of truth
• How Atlassian approaches capacity planning inside JPD, replacing spreadsheets with a live view that tracks engineer allocation as work evolves
• How Rovo agents can extend your JPD setup: generating roadmap pages on demand, surfacing insights for prioritization, and keeping your board current automatically