Multiple agents working in separate contexts can improve how distinct or competing requirements are met. Different contexts can surface different assumptions and reduce shared framing, but they also create more outputs to evaluate and layers to coordinate. The practical question is how much analytical separation a task warrants.

My own model-agnostic ‘Company Desk’ framework is designed around that trade-off. Its R1, R2 and R3 routes provide increasing degrees of analytical separation, selected according to what the decision actually requires.

• R1, single-context analysis, is for bounded work that benefits from focus and a clear line of responsibility. One attended agent completes the task directly.
• R2, multi-perspective analysis, is useful when materially different professional criteria apply to the same question. An agent examines the task through the smallest relevant set of distinct role-based perspectives, such as operations and research, then compares and synthesises them within a shared context.
• R3, multi-context analysis, is for tasks where separate analytical contexts could materially affect the recommendation. Separate agents produce reports on operational feasibility, evidence and assumptions, and risk and constraints. An attended coordinator evaluates their reports and produces a non-voting synthesis.

R2 and R3 separate the analysis in different ways. R2 makes competing criteria visible within a shared context. R3 reduces shared framing by giving analysts fresh contexts of their own.

The three routes provide a practical escalation rule. A bounded task remains within one context. A cross-functional question can receive explicit multi-perspective scrutiny. A consequential decision can use context-separated analysis when the expected improvement justifies the additional coordination and control.

The distinctive feature is proportionality. Each additional context is justified through expected decision value.

This creates a useful continuum between direct single-agent work and context-separated analysis. Delegation becomes an adjustable and governed property of the workflow, allowing richer coordination while keeping evidence, accountability and human authority visible.