Mission-critical work deserves mission-ready tools. We returned to Washington, D.C. for the next chapter of RAMP it up! Atlassian Government Cloud helps teams collaborate securely, move work faster, and stay aligned—all on a FedRAMP Moderate authorized platform.
Atlassian
Software Development
Sydney, NSW 2,567,656 followers
Our mission is to help unleash the potential of every team.
About us
Atlassian powers the collaboration that helps teams accomplish what would otherwise be impossible alone. From space missions and motor racing to bugs in code and IT requests, no task is too large or too small with the right team, the right tools, and the right practices. Over 300,000 global companies and 80% of the Fortune 500 rely on Atlassian’s software, like Jira, Confluence, Loom, and Trello, to help their teams work better together and deliver quality results on time. With our 300,000+ customers and team of 10,000+ Atlassians, we are building the next generation of team collaboration and productivity software. We believe the power of teams has the potential to change the world — one that is more open, authentic, and inclusive.
- Website
-
https://atlassian.com/
External link for Atlassian
- Industry
- Software Development
- Company size
- 10,001+ employees
- Headquarters
- Sydney, NSW
- Type
- Public Company
- Founded
- 2002
- Specialties
- b2b enterprise software, bug tracker, issue tracker, enterprise wiki, corporate wiki, business wiki, team collaboration, project management, downtime communication, work management, teamwork, and personal productivity
Products
Employees at Atlassian
View 17k employees at Atlassian
or
Locations
Updates
-
Release day used to mean hours of manual overhead for KFC UK & Ireland. Now, a Rovo agent does 90% of the heavy lifting. 🍗 Their custom “Change Agent” is a true digital teammate, catching blind spots before they become blockers. See how the KFC team uses Rovo for their instant self-service.
-
Reddit, Inc. isn’t just using AI agents—they’re grounding them. The bottleneck in AI-native development is coordination. Without context, agents drift from requirements and disrupt engineering flow. Sean J. and the Reddit team use Jira as their source of truth to manage agentic workflows and keep them tied to business goals. We’re building the system for AI-native development to help you plan, orchestrate, and scale agent work in Jira. See what’s new below ↓
-
Atlassian reposted this
Today we're announcing new capabilities in Jira to advance AI-native software development for every engineering organization, including a brand new Jira Planner! The problem: AI writes code fast, but a coding agent working from a one-line prompt tends to solve the ticket too literally. It misses the architectural constraint nobody wrote down, ignores a dependency, and produces a plausible-looking PR that a senior engineer then spends an hour unwinding. Speed goes up, but rework goes up with it. Our fix is to give agents the same context our engineers already use, route the right task to the right agent, and keep the work visible. Three concrete pieces: 1 / Context grounding. Before an agent starts, our new "Jira Planner" turns a loose request into a technical spec, pulling in the requirements, relevant architecture, and decision history from the work the team has already done. Better input, fewer wrong turns. 2 / Right task, right agent. A vulnerability patch, a backend refactor, and an UX tweak are different shapes of work and need different agents. Jira lets teams assign work to Claude Code, Cursor, GitHub Copilot, or Jira's own Coding Agent from the same work item, with the same context, in the same workflow. The runtime changes, the workflow does not. That is what keeps orchestration from fragmenting into four parallel SDLCs. 3 / Observable sessions. Every agent run, local or in the cloud, is recorded in one place with a clear trail from request to review, so audit, review, and learning don't get lost in someone's local shell. Check it out now → jira.dev
-
An agent running without context is just a token disposal service. Today, we're announcing the new system for AI-native software development in Jira. 🔹 Turn ideas into agent-ready technical specs with Jira Planner. 🔹 Assign work to any agent, including Claude, Cursor, GitHub Copilot, and more. 🔹 Autonomously create ready-to-review pull requests with Jira Coding Agent. 🔹 Get full visibility into agent sessions, wherever you work. 🔹 Automate routine fixes by routing work to background coding agents. Plan, orchestrate, and scale agentic workflows in Jira → jira.dev
-
Atlassian + Gamma. Two AI leaders. Zero lukewarm takes. 🔥 Byron Jones (Head of Platform at Gamma) and Philip W. Braddock (Head of Atlassian for Startups) serve up their hot takes on the latest AI trends and share why Atlassian and Gamma are better together. 🤝
-
No decks. No scripts. Just deep dives. 🇬🇧 We gathered London’s top sales pros for Atlassian After Hours to talk AI-powered selling. The biggest takeaway? It’s not about the tool—it’s about the people. The highlights: ✨ AI is the ultimate "pre-game" for prep, but it can’t replace the energy of a room. ✨ Values come to life when we solve problems together, not just present them. Huge thanks to everyone who shared their perspective. We’re hiring for our Sales team and looking for leaders who bring both tech and heart. Join the journey. 🔗 in the comments.
-
-
Month-end shouldn’t mean chasing errors across systems. 📉 For Alex Auerbach and Atlassian’s Finance team, tracking issues used to take hours of manual work. Now, the Finance360 Rovo agent handles the search for them. What once took 16 hours now takes under 30 minutes. 🤯 ✅ Real-time visibility ✅ Proactive monitoring ✅ Way less stress Ditch the manual tracking and let Rovo do the work. Link in comments to watch the full video. 👇
-
The value of AI isn't in the tool itself—it’s in the context. Most AI isn’t really plug-and-play. It knows how to code, but it doesn't know your architecture. It knows how to write, but it doesn't know your customers. We're changing that. Connectors feed your toolchain into the Teamwork Graph. MCP pushes that organizational memory out to whatever AI your teams already use. The formula is simple: Information in. Intelligence out. Learn more 👇
-