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Many Leaders are Under Pressure to Have a Solid AI Strategy and Assess the ROI of Their AI

Atlassian’s Rajeev Rajan believes when leadership embraces experimentation and motivates employees to learn AI without fear of failure or productivity loss, the rewards will pay off in dividends.

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Shrikanth
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Rajeev Rajan is the Chief Technology Officer at Atlassian

Rajeev Rajan is the Chief Technology Officer at Atlassian where he oversees Atlassian Engineering, IT, Security and Trust, and the Engineering Operations teams. As CTO, he is focused on Cloud transformation and continuing to grow Atlassian into a world-class engineering organization. Rajeev previously acted as the Vice President and Head of Engineering for Meta and spent over two decades at Microsoft, where he held several roles, including building and leading the team responsible for Office 365's Cloud Infrastructure. Rajeev is an alumnus of BITS, Pilani.

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 In an exclusive interview to CIOL, he walks through the company’s R&D facility in India and how it has scaled since its inception in 2018 and the critical role it plays for Atlassian’s worldwide product development. He also talks about the impact of AI. Excerpts.

Since India has the fastest growth in Atlassian and an important R&D facility was set up in Bangalore, what role did this region play in Atlassian’s worldwide product development and innovation process?

Since establishing our presence in India in 2018 with just 60 employees in Bengaluru, we have experienced remarkable growth, expanding to over 2,000 employees across the country in just seven years. India has become our fastest-growing location, with our headcount nearly doubling in the past two years, and approximately 75% of our local team dedicated to research and development.

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The work our team is doing in India has a significant global impact on our business. Our IT service management tools and Atlassian Marketplace are both largely driven out of India. In fact, our Marketplace recently surpassed $4 billion in lifetime sales, highlighting the vital role India plays in our overall strategy. In less than a year, we expanded data residency to eight new regions, including India, another project that was driven entirely by our Indian operations.

Last year we released Rovo - our AI powered offering that helps teams quickly discover knowledge across Atlassian and third-party SaaS apps with less time and effort. Critical parts of Rovo were developed right here in India, which showcases our commitment to innovation.

We recognize India as a powerhouse for tech talent, which is why growing our team here remains a top priority.

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You gave a presentation on ‘developer joy’. You talked about the joy of getting benefits as a fundamental principle in enhancing the well-being of developers. What comes to mind when you think about the products built by Atlassian joyfully?

Our goal is to build a world-class engineering team at Atlassian, which means our developers should be in a constant flow of creation. However, we found that our developers were experiencing friction in their daily work, whether caused by long cycle wait times or lack of documentation. That’s why investing in improving the developer experience, or what we call developer joy, has always been a top priority for me since joining Atlassian.

Not only have we seen a 50% increase in developer satisfaction scores since we started this journey a few years ago, but our engineers are delivering more software than ever. We saw a 66% increase in pull requests per engineer and our teams 10x'ed the number of experiments conducted. This has led to a lot of product innovation, including the ability to ship more than 1,000 customer features in the span of a year.

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Inspired by our own developer joy journey, we built a developer platform called Compass. Compass helps software teams eliminate friction, reduce risk, and improve their overall engineering culture. With Compass, development teams can centralize and track all services, libraries, APIs, and more in one unified software catalog. Compass also helps software teams implement standards at scale and build "golden paths" for their teams, which are predefined, standardized workflows that reduce friction in software deployments and ensure consistent best practices. We hope that Compass helps other development teams spend less time searching and managing so they can stay in the flow.

What is the strategy of Atlassian when it comes to using AI for overcoming the most pressing problems of the developers? Can you provide instances of AI-assisted tools that are improving the way developers work and think? (Can you also talk about the caveats of AI here, mainly GenAI, does it diminish natural creativity and intelligence and how important is humanizing AI and human-in-the-loop?)

We believe that AI should handle the mundane aspects of development work, allowing developers to focus on more creative and strategic tasks. Currently, developers lose over eight hours each week due to inefficiencies in processes and collaboration, as highlighted in our State of Developer Experience report.

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To address this challenge, we are excited to introduce our new dev-focused AI agents. Our AutoDev AI agent can automatically generate code plans, recommendations, and pull requests based on task descriptions, requirements, and context directly within Jira. Additionally, our AutoReview agent can instantly analyze code, provide recommendations for improvement, and suggest code edits within pull requests.

Most importantly, developers maintain control throughout this process. They can review and accept suggested changes while understanding the reasoning behind the agent's recommendations.

We have already rolled out these AI agents to our engineering teams internally. Some of the top use cases include cleaning up feature flags, updating configurations, and removing dead code.

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Outside of agents, Rovo Search has made a huge difference in developer documentation discoverability within Atlassian, and we see this reflected in our internal satisfaction survey results. This is important as we know one of the top pain points for developers is finding relevant documentation. Rovo’s enterprise search capabilities bring all documentation from Confluence, Jira, and other connected SaaS apps into a single set of results. Rovo Chat makes it easier for developers to ask questions and get answers in a conversational interface, breaking information silos. By having AI take care of these "chores," our developers can dedicate more time to strategic and creative work, ultimately enhancing productivity and innovation within our teams.

What pieces of advice will you impart to leaders of companies who are relatively cautious about implementing AI on how to help develop a culture of problem solving and self-AI solutions and navigating challenges like hallucinations and bias?

Many leaders are under pressure to have a solid AI strategy and assess the ROI of their AI investments, but none of that matters if their employees don’t feel empowered to use it. Atlassian’s AI Collaboration Index shows that if leadership embraces experimentation and motivates employees to learn AI without fear of failure or productivity loss, the rewards will pay off in dividends. Employees who have leadership support can save 55% more time a day than those who don’t. With this in mind, I like to remind leaders that we’re still in the early phases of AI. We need to get these tools in the hands of teams, provide them with a secure test environment, and encourage them to iterate and learn.

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A good first step is to encourage teams to identify challenges in their workflow and assign AI a role to help solve them. At Atlassian, our employees have created over 600 custom agents to complete specific tasks based on their needs. Our most popular AI agent is our Customer 360 agent, which can pull up customer insights, generate a strategy page, spar on questions, and perform a competitive analysis. It’s already used across 80 departments, including our leadership, customer support, and sales teams.

Of course, implementing such a powerful technology requires checks and balances. Humans should remain at the center of AI-based decisions and the tools should provide controls for that. Teams need to be able to trust but verify the output of AI, ensuring that they are accountable for the quality of their work.

You have clearly stated that you have faith that India would lead AI innovation globally. What makes India stand out in this race, and how does Atlassian align with this objective?

India has a tremendous opportunity to lead the world in AI innovation and adoption. Our recent State of Teams report highlights that Indian workers are using AI more frequently in their workplaces compared to their counterparts in other countries. Impressively, nearly 90% of these workers recognize the transformative impact AI will have on their jobs within the next five years. Not only are they using it at a higher rate, but our AI Collaboration Index found that nearly half (46%) of Indian knowledge workers are advanced AI users, surpassing teams in other nations.

This strong engagement with AI is a testament to the country's robust tech talent, visionary leadership, and supportive business infrastructure, aligning perfectly with our goal of becoming a 100-year-old company.

Being at the forefront of team collaboration software, what change do you expect the new trends like generative AI and machine learning will bring to the future of Jira, Confluence, Trello?

For the last twenty-plus years, our products have been helping teams work better together and achieve the impossible. From large enterprises to nimble startups, companies are looking to us as strategic partners to guide them in this next era of human-AI collaboration.

We approached our gen AI product development in waves. In our first wave, we introduced Atlassian Intelligence, a suite of AI-powered capabilities across our portfolio of products, including Jira and Confluence. These features include generating summaries, defining acronyms, improving writing, and similar basic functionalities.

In our second wave, we launched Atlassian Rovo, our first standalone AI product. Rovo helps teams find, learn, and act on new information to make better decisions faster. It includes enterprise search, chat, and agents. Rovo is our most important and ambitious product yet, and thanks to our strong R&D engine, we were able to ship Rovo in just 6 months.

All of this is powered by our Teamwork Graph, which we consider our secret sauce that makes our AI so special. Our Teamwork Graph draws on connections from every new tool connection, team action, and project event to deliver increasingly relevant results to users.

Our customers are seeing remarkable results with our AI, having increased their usage 10x since the start of 2024. The technical program management team at Procore has cut time creating quarterly roadmaps by 75% with our AI and customers like OVO Energy are calling our enterprise search a game-changer. We’re motivated by all the positive feedback from customers and the greater opportunities ahead.

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