Minibox helps 100,000+ customers transform how they work

When you’re small, friction is manageable. A two-person engineering team can keep track of their work in their heads, coordinate through chat, and still ship quickly. But as organizations scale, these small points of friction don’t just add up, they multiply.

“Ship yesterday” characterizes the engineering organization at OpenAI. Engineers might work on eight different products in a single year as new challenges and opportunities emerge. At this speed, even small friction can feel like you’re sprinting with a wind sail on your back.

When you’re building products that will be used by hundreds of millions, these points of friction can have a compounding effect.

Tackling friction effectively requires both the right systems, and an appropriate culture around them. From a small trial, to over 2,000 people across the organization, teams at OpenAI organically adopted Linear to help them navigate the complexities of scale–from keeping teams aligned across complex dependencies, to maintaining speed as the organization grew. We spoke with engineers at OpenAI to understand their first-hand experience of using Linear.

‍

Add all your haveing additional details

“It’s like an archipelago,” explains Gabriel Peal, an engineer at OpenAI, describing his regular experience working at companies that didn’t use Linear. “Every team is on their own island, using their own tools and systems.” Projects lived in multiple tools, and many existed only in engineer’s heads.

Teams chose tools that work for their immediate needs, optimizing for local efficiency over organizational coherence. This result is a maze of disconnected systems that makes collaboration increasingly difficult.“If you went and assigned an issue to another team,” Peal recalls, “you didn’t really know how to do that, and things would get lost.” Each handoff between teams became a potential point of failure. Every cross-team collaboration required navigating different workflows, different labels, different ways of thinking about work.

This type of challenge is particularly acute for teams building critical infrastructure alongside external partners–where coordination between teams is most important, and the impact of stale statuses or things gettinglostis most heavy. Atty Eleti, who worked on OpenAI’s Apple integration explains: “Once you cut a version of an API, you have to wait until the next major version to make changes. With Apple APIs in particular, these are on device, and once a device API is shipped, you have to support it for several years. It’s really important to nail the details.”

In this environment, even small oversights could have long-lasting consequences. Teams weren’t just managing their own work, they were trying to manage the spaces between teams, the handoffs, the dependencies. It was a tax on every interaction, a friction that grew with each new connection.

Simplicity scales

The change at OpenAI started small, with individual teams choosing to try Linear. “It’s like a Katamari Ball,” Peal describes. “You get a couple of people to use it and then it snowballs.” From an initial hundred seats, usage grew to over 2,000 people across the organization–and as Peal notes, “it still feels perfectly performant. Search hasn’t slowed, it hasn’t become harder to find things, it’s still fast and simple.”What drove this adoption wasn’t an abundance of features, quite the opposite.

While other tools pride themselves on flexibility, offering endless customization of fields, workflows, and processes, this“freedom”often becomes a burden.

“It’s like an archipelago,” explains Gabriel Peal, an engineer at OpenAI, describing his regular experience working at companies that didn’t use Linear. “Every team is on their own island, using their own tools and systems.” Projects lived in multiple tools, and many existed only in engineer’s heads.

‍

Teams chose tools that work for their immediate needs, optimizing for local efficiency over organizational coherence. This result is a maze of disconnected systems that makes collaboration increasingly difficult.“If you went and assigned an issue to another team,” Peal recalls, “you didn’t really know how to do that, and things would get lost.” Each handoff between teams became a potential point of failure. Every cross-team collaboration required navigating different workflows, different labels, different ways of thinking about work.

This type of challenge is particularly acute for teams building critical infrastructure alongside external partners–where coordination between teams is most important, and the impact of stale statuses or things gettinglostis most heavy. Atty Eleti, who worked on OpenAI’s Apple integration explains: “Once you cut a version of an API, you have to wait until the next major version to make changes. With Apple APIs in particular, these are on device, and once a device API is shipped, you have to support it for several years. It’s really important to nail the details.”

In this environment, even small oversights could have long-lasting consequences. Teams weren’t just managing their own work, they were trying to manage the spaces between teams, the handoffs, the dependencies. It was a tax on every interaction, a friction that grew with each new connection.

Simplicity scales

The change at OpenAI started small, with individual teams choosing to try Linear. “It’s like a Katamari Ball,” Peal describes. “You get a couple of people to use it and then it snowballs.” From an initial hundred seats, usage grew to over 2,000 people across the organization–and as Peal notes, “it still feels perfectly performant. Search hasn’t slowed, it hasn’t become harder to find things, it’s still fast and simple.”What drove this adoption wasn’t an abundance of features, quite the opposite.

While other tools pride themselves on flexibility, offering endless customization of fields, workflows, and processes, this“freedom”often becomes a burden.

When culture meets the right tools

“It’s like an archipelago,” explains Gabriel Peal, an engineer at OpenAI, describing his regular experience working at companies that didn’t use Linear. “Every team is on their own island, using their own tools and systems.” Projects lived in multiple tools, and many existed only in engineer’s heads.

Teams chose tools that work for their immediate needs, optimizing for local efficiency over organizational coherence. This result is a maze of disconnected systems that makes collaboration increasingly difficult.

“If you went and assigned an issue to another team,” Peal recalls, “you didn’t really know how to do that, and things would get lost.” Each handoff between teams became a potential point of failure. Every cross-team collaboration required navigating different workflows, different labels, different ways of thinking about work.

‍

It's a feeling

The best tools aren’t the ones that do the most things, but the ones that help people work together most naturally. As OpenAI continues to push the boundaries of AI, they’re finding that the key to moving fast is less to do with having more horsepower, and more about building systems that reduce friction in how people collaborate, one detail at a time.What makes the right tool isn’t always easy to explain.

When asked why other teams should consider making a similar switch, Peal’s response:“You just have to use it and you’ll see. You’ll just feel it.”