Coordination rules age, and I do not want a new model trapped inside a workaround for an old problem. Writing instructions takes effort, but that does not give them a permanent claim on every assignment that follows. Each mandatory detour needs to keep justifying the time it consumes.
In July 2026, I suspected that rules created to organize models were constraining newer ones. In my own agent setup, I was questioning the number of agents and the sharing of every project's context between them.
The Agents API entered public beta on September 10, with durable sessions and managed execution. With the announcement, I have a concrete reason to review what I would put around the executor. A responsibility handled by the service can make an earlier workaround unnecessary. Before carrying my configuration over, I want to check which rules the service now covers.
Splitting a large task can help it move forward. Forcing every small request through the same sequence adds handoffs, explanations, and waiting. One model receives a part, returns it to the coordinator, and another agent reconstructs the context. If the answer fit within one execution, I have built a queue to organize something that could already be finished.
Deleting instructions because the file became long would be lazy too. A preference about task division serves a different purpose from an access boundary. I want to understand what problem each rule prevents before changing it.
The comparison I care about is small: one organizational rule, one representative assignment, and a clear expected result. An execution with fewer steps still needs to deliver the requested behavior. I have not measured it yet, so I have no improvement to report. The result should show whether the rule helps or merely repeats an older limitation.
I will start the next coordination review with instructions that force work to change hands. Before adding another agent or another exception, I want to identify why the current route exists. Access boundaries stay; organizational routines have to show evidence. The first candidate is sharing every project's context between agents.