Linear's Tom Moor on agent coordination

Tom Moor, co-founder of Linear, offers compelling insights into the company's journey to create a software platform that coordinates agents through a pragmatic, engineering-focused approach to AI. In a tech landscape enamored with the idea of "agentic" AI systems working in concert, Linear has quietly built practical foundations that could reshape how we conceptualize productivity tools. Their system, while still evolving, shows how thoughtful implementation rather than buzzword chasing can deliver genuine user value.

Linear's approach centers on creating a platform where multiple AI agents can work together within the constraints of a well-defined system, tackling complex tasks like software development coordination. Unlike many companies making grand promises about autonomous AI, Linear focuses on implementing functional, useful coordination patterns that solve real problems for developers and teams.

Key elements of Linear's approach:

• Building platforms, not just agents: Rather than creating standalone AI tools, Linear focuses on constructing a coherent ecosystem where multiple agents can communicate and collaborate through a shared context and standardized interface.

• Pragmatic engineering over AI hype: While the industry buzzes about fully autonomous systems, Linear emphasizes concrete implementation within a structured environment where the rules and limitations are clearly defined.

• Controlled autonomy: Linear constrains agent capabilities within their specific domain (software development tracking), creating a safer sandbox for experimentation while maintaining user trust.

The most insightful aspect of Linear's approach is their recognition that effective agent coordination requires strong platform fundamentals. While many companies rush to implement flashy AI features, Linear understands that without a solid infrastructure—with well-defined APIs, shared context, and clear communication channels—multi-agent systems become unpredictable and ineffective.

This insight matters tremendously as companies across industries race to implement AI agents. The distinction between creating individual smart agents versus building systems where multiple specialized agents can reliably collaborate represents the difference between incremental productivity gains and transformative workflows. Linear's platform-first approach demonstrates that the real value of AI may come less from sophisticated individual agents and more from thoughtful coordination between simpler, specialized ones.

The implications extend beyond project management software. Consider the healthcare sector, where the promise of AI has largely manifested as isolated diagnostic tools rather than coordinated systems. A platform approach similar to Linear's could connect specialized medical AI agents—