Why a People Search Agent needs its own harness

I have been experimenting with People Search Agents for recruiting workflows. One thing became clear: general-purpose agent harnesses are not enough for this vertical task. When using general agents for people search, I repeatedly run into these issues: 1. Retrieved profiles quickly blow up the context window 2. Search strategies often loop back to already failed paths 3. Reflection does not reliably produce useful “aha moments” 4. The agent struggles to distinguish hard requirements from nice-to-have signals 5. Human-in-the-loop clarification happens too late For people search, the harness needs to do more than tool calling. It should manage context compression, candidate summarization, task graphs, search branch pruning, workflow execution outside the agent loop, and reusable search memory across similar roles. My current view: for vertical agents, the real product moat is often not the model itself, but the harness around it. Curious how others here think about this: for vertical AI agents, where do you draw the line between “model capability” and “harness/product design”?