Why Atlassian Chose Not to Rush Through LLMs

Last week, Atlassian’s CTO Rajeev Rajan sat down with AIM to list down the company’s technological priorities
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Less than a year ago, when Microsoft-backed OpenAI popularised the GPT technology through its AI chatbot, a majority of companies rushed to embrace it. However, despite the huge attention, not all tech firms jumped to adopt the tool — one of them being Atlassian.  

Last week, the software company’s chief technology officer Rajeev Rajan sat down with AIM to list down the company’s technological priorities and why Atlassian chose not to join the LLM race. During the conversation at their Bengaluru office, Rajan emphasised at certain instances that the cloud remains a top priority for Atlassian. He stated, “The value proposition of cloud is pretty clear both for customers as well as for providers like us. For the overall ecosystem, we continue to invest a lot in it as 99% of our customer base is on cloud.”

“Our primary focus is to innovate and deliver features that enhance our customers’ experience. We want to harness the data already available to us to unlock value for our customers, leveraging existing developments. Building our own model is not our highest priority at this juncture,” he added.

Atlassian cares about security and privacy first and foremost, asserts Rajan. “Our chief trust officer looks at these things holistically. We are still learning the game and will constantly evaluate different elements and providers to get the best of breed and then maybe end up in a combination,” he said, elaborating on why the company chose OpenAI’s ChatGPT over other enterprise-specific models provided by Cohere and others.

In April, the company unveiled Atlassian Intelligence, an AI-driven “virtual teammate” that harnesses the company’s proprietary models in conjunction with OpenAI’s technology. This synergy enables the creation of customised teamwork graphs and facilitates features such as AI-generated summaries in Confluence and test plans in Jira Software, as well as rewriting customer responses in Jira Service Management.

A Year at Glance

A little over a year ago, Rajan joined the Sydney-based software company as its CTO. Reflecting on his stint at the company, he shared, “I was really attracted to Atlassian for the values of the company as well as the story of the founders and how the company started a really strong position with JIRA for engineers. I’m an engineer, I’ve always been one. To me, building software that is used by every inch of the world, to learn because some companies use our software in the cloud, is really empowering”.

He recounted his inaugural year, stating, “The first year has been about trying to take what we have to get to the next level of growth.” “We have a goal of getting to really being the best in class — world class engineering. What does it take to have what we call, developer joy? We spend a lot of time with that programme, getting it up and running for the company and then building that into products so that we can influence every other tech company out there,” he continued. 

Rajan, who has also served as Meta’s engineering lead, delved further into the technical aspect of Atlassian, explaining, “When you write code to build a software, you end up with legacy code also called monoliths. One of the things we have been doing last year is to decompose the monolithic software into micro services so that you have more scalar architecture, and it’s easier for engineers to go and make changes as opposed to legacy code. We have done a lot of reengineering of our code bases to commit engineers.” 

Prior to joining Atlassian, Rajan had served as vice president and head of engineering at Meta, with a distinguished career spanning over two decades at Microsoft, where he played pivotal roles, including leading the team responsible for Office 365’s Cloud Infrastructure.

Developing, Responsibly

Discussing the responsible adoption of AI, at several instances during the interview, Rajan emphasised that Atlassian is crystal clear about its role in ensuring responsible technology practices, particularly in AI adoption. “We have established a working group that meets every month that looks at a bunch of questions around the responsibilities of AI. That’s one example of a responsible AI workstream. Secondly, when we have any new technology like AI, we have a whole set of objectives or questions that equals whenever we use any AI technology or develop something ourselves. We have a checklist to make sure it is adhering to these practices in terms of ethics,” he revealed.

“This is really ingrained into our development process. We are totally aligned with those efforts as well to make sure that in the end, humanity gets the advances in technology without the ill-effects that everyone’s worried about,” Rajan concluded. 

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Tasmia Ansari
Tasmia is a tech journalist at AIM, looking to bring a fresh perspective to emerging technologies and trends in data science, analytics, and artificial intelligence.

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