Linear's COO argues that team size doesn't dictate business impact. By keeping its team intentionally lean (around 140 people for 25k+ customers), the company maintains a high talent bar and focuses on metrics like revenue and growth over headcount.
To truly assess collaboration and skill, Linear replaces traditional final interviews with a 2-5 day paid project. Candidates work on real, shippable tasks, allowing Linear to evaluate not just the final output but also the collaborative process and communication style.
Linear's COO argues that leaders cannot fully delegate AI exploration. To truly understand how new tools work and can be applied, executives must use them for their own tasks. This direct experience builds "native thinking" that is impossible to gain secondhand.
Linear's data reveals that non-engineering roles, particularly PMs, show the largest increase in using agentic AI features. AI empowers them to independently perform tasks like data analysis or competitive research that they previously had to delegate, increasing their autonomy and speed.
To attract enterprise buyers, Linear evolved its messaging from product features that appeal to individual contributors (e.g., keyboard shortcuts) to business value that resonates with CTOs (e.g., organization-wide efficiency gains). This shift is critical for any company moving upmarket.
To overcome the high switching costs for enterprise customers, Linear employs a three-part strategy. First, they prove value. Second, they run a pilot with a few teams to demonstrate success. Finally, they provide migration tooling and resources to ensure a seamless transition.
Linear COO Cristina Cordova uses a self-driving car analogy for AI adoption. Some users want to stay in control and approve suggestions ("Tesla mode"), while others prefer full automation ("Waymo mode"). Products must cater to this entire spectrum to succeed.
Instead of confining users to its app, Linear's first homegrown agent was built for Slack's interface. This user-centric strategy embeds workflows into existing habits—like summarizing a long Slack thread into tickets—acknowledging that work happens across an ecosystem of tools.