The Story of Sleuth: Building the Future of Engineering Efficiency

Some of the most enduring software companies start with an engineer scratching their own itch. In a recent episode of Category Visionaries, Sleuth CEO Dylan Etkin shared how a problem he encountered while scaling BitBucket at Atlassian grew into a mission to transform how engineering teams measure and improve their effectiveness.

The Atlassian Years

The story begins in 2005 when Dylan joined a then-small Australian software company called Atlassian. “I was fortunate enough to get involved in a small startup at 20 people called Atlassian,” he recalls. “That was a wild ride, which meant that I got to learn a lot of things and do a lot of different things over the years inside of Atlassian, starting with working on Jira as a developer, one of the first three developers, being the first architect on Jira.”

Over the next decade, Dylan watched Atlassian transform from a scrappy startup into a global enterprise software giant. “It was like working at seven different places,” he explains. “There was the 20 to 40 or 50, there was the 50 to 250. There was the next phase.”

The Lightning Bolt Moment

The seed for Sleuth was planted during Dylan’s time leading the BitBucket team. As the team grew from seven to forty people, he encountered a crucial insight about software deployment. “It kind of struck me like a lightning bolt that deploy, which is this thing that at the time, we treated almost like as a second class citizen, was the most important thing,” he shares.

This realization led Dylan to start building a tool, initially called Deploy Hub, around 2015. Even after returning to Atlassian through an acquisition, the idea persisted. “I gave the idea and the opportunity, a lot of opportunity, to just die on the vine and it refused. Every time I would talk to somebody about it, I’d get super animated and interested.”

The Evolution to Sleuth

When Sleuth officially launched in 2019, the company took an open development approach and quickly gained early adopters. However, they soon realized that their initial focus on deployment tracking wasn’t addressing the full scope of what organizations needed.

The breakthrough came with the adoption of DORA metrics – deployment frequency, lead time, failure rate, and mean time to recovery. “The Dora metrics have really allowed us to take the real information and glean some sense of usefulness out of them,” Dylan explains. “And so a market has grown up around that.”

The Vision: Salesforce for Engineering

Looking ahead, Dylan sees Sleuth playing a transformative role similar to what Salesforce did for sales teams. “The best sales teams back in the day before Salesforce were doing a lot of the things that Salesforce allows other teams to do,” he explains. “But what Salesforce did was sort of say to everybody, this is how you do it. You don’t have to be a top tier team in order to use these tools.”

This vision of democratizing engineering best practices drives Sleuth’s current direction. “Engineering has been ripe for that transformation for quite some time,” Dylan notes. While top engineering organizations might already have sophisticated processes for measuring and improving their effectiveness, Sleuth aims to make these practices accessible to all engineering teams.

The parallels to Salesforce’s impact on sales teams are striking. Just as Salesforce standardized sales processes and made best practices accessible to all sales teams, Sleuth aims to do the same for engineering effectiveness. It’s a vision that could fundamentally change how software teams operate and measure their success.

Like many great software companies before it, Sleuth’s story is one of persistence, evolution, and a clear vision for transforming an industry. From a side project born at Atlassian to a platform with ambitions of becoming the system of record for engineering teams, Sleuth’s journey shows how deep domain expertise combined with patient iteration can lead to breakthrough products.