← All IntelClip / AI AgentsWhere verification fails, shared context substitutes
From Perception Agents — Antje Barth, Amazon AGI Lab · ≈7:06
Argues the bottleneck for messy knowledge work is not model capability but giving the agent the same view of the screen a human collaborator would have.
What’s in it
- Argues the bottleneck for messy knowledge work is not model capability but giving the agent the same view of the screen a human collaborator would have.
Clip transcript
right where most of our work lives. It's living in the seams of all of those applications we're using on a day-by-day basis. And nobody really has corrected this part yet. How do you make an agent reliable when there's no way to verify the answer that easily? And that's a field that is still wide open. So, how can we solve this? Well, so how do humans handle messy work? I mean, we're successful at it, right? Each of us like every day we work across different systems. We manage out how to onboard a new colleague. We do this. Well, we're doing it by figuring things out together. You grab a colleague, you jump on a Zoom meeting, you're discussing things, you're looking at the problem to solve, you're discussing p pointing at systems, and maybe two minutes later, you solved it. You're done. But none of this work is actually directly verifiable. And we do this all day. So one of the things is we're looking mostly at the same screen, right? If you're jumping on a meeting with a colleague, you see the same screen, both of you, and you can actually like figure out really quickly what needs to be done. So this is what the agent these days is missing. You don't necessarily need a bigger brain. What you need is this shared context. Because if we're looking the agent and myself at the same screen, I probably have much less explanating to do.
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