Linear has introduced an AI agent and plans to add AI coding assistance, with CEO and co-founder Karri Saarinen declaring that issue tracking is dead. For a company built on the premise of elegant task management, this is a remarkable pivot.
Coding agents are already installed in 75 percent of Linear enterprise workspaces, and the volume of work done by agents has increased five times in the last three months. 25% of issues are now created by agents, not humans. These numbers matter because they suggest the shift from human-managed workflows to agent-driven systems is not a theoretical possibility—it is already underway inside paying customers.
The Linear Agent works in the online, mobile, or desktop app, and as a plug-in for products including Slack, Teams, and Zendesk. It has a chat user interface and examples of usage include making issues based on discussions and assigning them automatically. Future features will include a coding agent to write code and fix bugs, as well as the ability to answer questions about a codebase and to present code diffs.
This repositioning exposes a real tension in software development tooling. If agents are now doing the work that issue tracking systems were designed to coordinate, what purpose does the tracking system serve? Saarinen's answer is blunt: Linear becomes a tool for capturing context while agents do most of the engineering work. The vendor moves from task manager to context keeper.
The broader market believes this bet is credible. The global market value of agentic AI was 5.1 billion US dollars in 2024 and is anticipated to surpass 47 billion US dollars, with a compound annual growth rate of over 44 percent. But adoption curves are not growth guarantees. Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls. Early enthusiasm has not translated to mature deployment patterns.
The competitive landscape is moving fast. AI agents now investigate issues, generate code, run tests, and execute multi-step workflows. As this work scales, software development extends beyond individual tools or sessions into a distributed system of agents, environments, and workflows that operate across IDEs, CLIs, pipelines, and collaboration tools. Basecamp from 37signals, another project management tool, is also planning to reposition itself as agent first, agent native with access from any AI agent via a command line interface.
There is also a legitimate worry about governance. The original source notes that security was barely discussed in Linear's announcement: "Linear Agent operates within your existing permissions" is the extent of the public security statement. As agents gain the ability to write code and interact with external systems, this casual approach to risk becomes harder to defend.
Strip away the marketing language and two things become clear. First, Linear has achieved real agent adoption inside its paying customers. That is not hype; that is traction. Second, the company is gambling that it can remain central to a workflow that is fundamentally changing. If coding continues to travel towards more agentic workflows, customers may shift away toward tools designed specifically for agent management. Linear is trying to move first, but it cannot be certain it will move fast enough to stay relevant.
For business leaders evaluating these tools, the message is simple: agentic AI is not coming in 2027 or 2028. It is here now, working inside production systems, creating thousands of tasks and pulling code. The question is not whether to adopt it, but whether your current tools can evolve to manage it.