How we built Linear Agent

Linear describes building Linear Agent by allowing flexible, context-aware behavior within carefully designed boundaries rather than scripting fixed workflows. Its system prompt establishes communication standards, safety constraints, product-specific concepts, and default judgment rules, while its tools are designed to make appropriate actions intuitive and invalid ones difficult. Because Linear’s many specialized product operations require knowledge not inherent in general-purpose models, the agent uses “system skills” that package relevant instructions, metadata, and tools and are loaded selectively based on a task’s context. Linear intentionally avoids granting low-level SDK, CLI, or API access to reduce speculative or unsafe actions, accepting narrower capability in exchange for greater predictability. A custom underlying harness supports dynamic tool injection, context-sensitive approval for consequential actions, and asynchronous sub-agent work, giving the team control over efficiency, reliability, and emerging edge cases as agent capabilities evolve.

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