AI Agents Research Twenty Blockchains in Parallel
A shared evidence search can fan out across many targets before separate agents pursue the most relevant lines in depth.
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Declarative pipelines reduce AI agent drift by fixing the path through functions, steps and data while leaving people responsible for direction and course correction. A shared evidence search can fan out across many targets before separate agents pursue the most relevant lines in depth.
With Pete Winn, Anthony and Andy David
7 ideas developed from this conversation
About this conversation
Declarative pipelines reduce AI agent drift by fixing the path through functions, steps and data while leaving people responsible for direction and course correction. A shared evidence search can fan out across many targets before separate agents pursue the most relevant lines in depth.
Ideas from Episode 60
Cheap Inference Squeezes Frontier AI Economics
Frontier labs must keep funding expensive model advances even as older capabilities become cheaper and harder to distinguish from the latest release.
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Code-Directed Workflows Keep AI Agents on Track
Declarative pipelines reduce AI agent drift by fixing the path through functions, steps and data while leaving people responsible for direction and course correction.
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How AI Doomerism Could Shape Regulation
Warnings that AI could wipe out jobs can make the technology feel like an urgent political crisis, giving leading labs more influence over the rules that follow.
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Mathematical AI Must Separate Discovery From Retrieval
A model can find an unexpected link between mathematical fields, but novelty depends on proving it hasn't merely recovered an overlooked result.
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Purpose-Built Robots Beat Humanoids at Home
The strongest case for household automation is a machine that reliably removes a defined chore, not a humanoid whose broad capabilities may never justify its cost.
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Why AI Agents Still Need Human Direction
An AI agent can check its progress only against a destination it understands, and defining that destination may require much of the original work.
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