Reading this discussion about unnecessary subagents prompted me to revisit how I ask AI agents to work. I had been encouraging delegation whenever it might help. Looking at that, I realized how easily "might help" could become a reason to split almost anything.
I've tightened that default. I want the lead agent to stay involved in doing the work, with delegation serving a clear purpose.
For me, the useful question is what a separate agent adds. Independent research can benefit from parallel exploration. A fresh reviewer can catch something the original agent missed. But when several steps depend on the same evolving context, handing them around can mean more explanation, lost details, and coordination.
The Anthropic article behind this discussion gave me a practical way to think about it: keep useful knowledge available through skills and tools, and test whether an extra agent improves the whole task.
I haven't measured the impact of my changes yet. My aim is clearer ownership, fewer unnecessary handoffs, and better use of the context already available.
If you're building a similar workflow, I'd start with one task and compare the results before adding another agent. Keep the delegation that earns its place in practice.
https://t.co/YmhYdAKYkj