Scale AI is laying the foundation for AI innovation, serving as the hub for building, deploying, and evaluating AI. As the company grew, it needed a project management tool to grow with it. Product and engineering leaders banded together to propose Linear and launch it across the organization, seeing an immediate impact.
In the rapidly changing space of AI, Scale has evolved and grown to lead the space. As the company expanded, adding hundreds of new employees, their existing project management tools were unable to keep up with their needs.
The need for new tooling became apparent and leaders across different teams independently sought better solutions. A grassroots movement within the company, guided by leaders from different teams, converged on the same solution: Linear.
Before migrating employees to Linear, Scale was using a combination of other tooling across their teams. Pitching and coordinating a tooling switch of this scale can be difficult, but Sam Sipe, Head of Engineering for Public Sector at Scale, knew he wanted to switch to Linear.
Before, they had difficulty reassigning issues, sharing context, and seeing progress. To get clarity, members of each team bookmarked different views and periodically audited other teams’ boards for issues that weren’t appropriately tagged to their team.
Theoretically, we were agile, but it was difficult to find tickets. We had a backlog that wasn’t in service of our products or the engineers working on them. Things got lost if end users didn’t use workflows properly.
Having used Linear at a previous company, Sam was confident it was the right tool to organize and engage his teams.
Having used Linear previously, I realized how much better it would be to have purpose-built tools that do the right thing. Linear’s easy-to-follow workflows would be incredibly useful to our engineers.
Over the past year, Scale’s business product offerings expanded rapidly, and so did its team. The expanding team looked to Linear to support its growth.
Engineers hate issue tracking in general, so you need to make the barrier as low as possible and set incentives for them to use it. One way to do that is to have a tool that people enjoy using.
Over time, engineers did what they could to avoid logging tickets, like resolving issues outside of the tracking tools already in place. The broken issue tracking process caused complications downstream.
Though Clemens Viernickel, a Staff Product Manager at Scale, had never used Linear before, he knew of it from peers and made an independent decision to pilot it on his team. Conversations outside their previous tool unearthed new tickets that needed to be created. They needed a bridge for a disconnected workflow. There was no initiative to roll Linear out to Joshua’s team. But when he caught wind of it, he thought his team should convert, too.
When other teams caught wind of a potential shift to Linear, they also wanted licenses.
We planned for 50 seats initially, but suddenly, 200 more people signed up. It was a classic grassroots story – other teams heard we were using Linear and wanted to use it, too. Now, we’ve switched all teams over.
My advice for anyone curious about Linear is to do a pilot. The product sells itself. My team instantly thought Linear was great. There were no grumblings. The only conversations we had were about getting enough seats to give people access.
The first team that used Linear chose their optimal workspace and team settings. That foundation made it easy to onboard remaining teams. Eager to get moving in Linear, the group decided to leave their old tool behind and go into the transition with a clean slate.
Joshua’s smaller team imported all of their issues to Linear, archived the ones they weren’t working on, and adjusted Linear settings to their way of working. By the time Linear was approved across the org, they were fully up to speed.
The larger teams took a similar approach but extended rollout to ensure smooth change management. They established a cutover date where all issues would be imported to Linear, and all work would take place in Linear moving forward.
Quick adoption of Linear led to impressive outcomes for Scale. Scale improved bug resolution time by 52%, resolving problems for customers and building data products faster than ever before.
In Linear, Scale found the infrastructure it needed to continue fueling the most exciting advancements in AI.
I often get asked, ‘Why Linear?’ While I could talk about all of its incredible features, the switch to Linear was really fueled by one thing: velocity.
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