Let AI Agents Load the Context They Need, Says Linear Engineer Jacob

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Jacob, an engineer at Linear, argues for giving agents a clear goal and tools to load relevant skills and guidance instead of putting every possible detail into the initial instruction.

1Keep the initial instruction focusedJacob favors giving an agent fewer instructions when it can retrieve context itself.
2Define the goalHe says a clear objective helps the agent determine what information it needs.
3Load guidance on demandTools for retrieving skills and guidance let the agent assemble context for the task.

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Start with a clearly defined goal for the agent.
Give the agent tools to find relevant skills and guidance as needed.
Avoid flooding the initial instruction with context that may distract from the task.

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Clear goals and on-demand context

Jacob explains his approach to agent instructions.

Linear engineer Jacob recommends giving an AI agent a well-defined goal and access to tools for loading relevant skills and guidance, rather than packing every detail into its initial instruction. His concern is that too much supplied context can cause the agent to emphasize information that is not important to the task. Peter Yang notes that an agent can search for what it needs; Jacob agrees that this lets it assemble its own task-specific context.