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Sub-agents as a context boundary, not just a task decomposition — Intel — VibeLeaderboard

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Sub-agents as a context boundary, not just a task decomposition

From How we solved Context Management in Agents — Sally-Ann Delucia · ≈9:18

“one big realization that we also had is that not all context belongs in the same agent.”
AI Engineer

“we have the main conversation with the chat and light context only. We keep it pretty light. What it can do is it can delegate to the sub-agents.”
AI Engineer

“offload the heavy tasks. The main conversation can stay small.”
AI Engineer

“We've uh rolled out a lot of sub-agents now that we kind of figured out this is the right way to handle all the really, you know, data-intensive operations.”
AI Engineer

What’s in it

Search over hundreds of spans generates queries and intermediate reasoning that never need to reach the main thread — the sub-agent holds the heavy data and returns only the result.

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Clip transcript

here, um there is still, you know, too much data sometimes for for one agent. So, uh one big realization that we also had is that not all context belongs in the same agent. Um so, I'm going to give an example here, our search task. So, this is where Alex is trying to search over data in Arise. Um this happens within like our main chase or even when we're just looking at, you know, one trace stack, you know, there can be hundreds of spans within it and Alex needs to figure out what data it should look at. So, there's multiple queries happening, tons of data, lots of intermediate reasoning happening step-to-step. And we really came to the conclusion that not all this needs to live in the main conversation. So, once we had one kind of main agent uh for our traces uh skills and we decided that that was not really necessary. So, the solution that we had was sub-agents. And I think this is also something really important when you're talking about context and how we manage across uh these agents that need to have a lot of data, uh which is offload the heavy tasks. The main conversation can stay small. Um so, before we had the main conversation, we had chat history, heavy data, search all in one context. This was all handled in one agent. And then after basically what we have is these this main agent plus a sub-agent. So, we have the main conversation with the chat and light context only. We keep it pretty light. What it can do is it can delegate to the sub-agents. Um and that's where the heavy data stays. So, we can keep all of the heavy data context in our sub-agent. And then once it gets a result, we can kind of pass that over to the main uh main agent again and then the user can kind of share um or keep the conversation going. And of course, it can always retrieve from the memory store as well if it ever feels like it needs more context there. So, I think this is something that was a game-changer. We've uh rolled out a lot of sub-agents now that we kind of figured out this is the right way to handle all the really, you know, data-intensive operations.