Human bandwidth and context switching definitely seems to be a major bottleneck at the moment, but if scheduling several tasks concurrently to batch questions I imagine there is an upper limit on how many tasks can be run in parallel, especially if there are dependencies between them. I think we need to start charging employers per token of human attention if you optimise the mental throughput. I'm going to miss doomscrolling while claude writes the plan though :(
"upper limit on how many tasks can be run in parallel" - definitely, however at the moment codinig workflows like Claude Code will spawn around 5 agents in parallel at max, but we can hope that dynamic workflows provides a better solution however the intial reports on the coherency of the their multi-agent system seems to be sub-optimal
There are some great ideas in this post, namely the focus on human attention as the limited resource and the recursive decomposition of tasks. There were also a few points which I found unclear. You describe recursive decomposition as a "tree of DAGs ...". What do you mean by this? Is each node in the tree a DAG? Secondly, I agree that the tree is exponentially faster than one agent scanning a flat list, but are you not running exponentially more "scanning" agents? If human attention is the only limiting factor this is fine, but is this not a problem if you have limited compute?
Running more scanning agents exponentially is an interesting proposition as we scale to massive, continuously growing tasks. In my initial experimentations with well-defined tasks, the overhead has not been worth diving into yet, since latency has been low enough.
It would turn a slow search into a highly parallelised "MapReduce" problem. You trade a brief, massive burst of machine execution to keep wall-clock latency incredibly low for the human waiting at the top.
A tree structure means these scanning agents don’t just run wild. High-level nodes could aggressively prune entire branches the moment a scanning agent reports a dead end.
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[ 1389 ms ] story [ 474 ms ] threadIt would turn a slow search into a highly parallelised "MapReduce" problem. You trade a brief, massive burst of machine execution to keep wall-clock latency incredibly low for the human waiting at the top.
A tree structure means these scanning agents don’t just run wild. High-level nodes could aggressively prune entire branches the moment a scanning agent reports a dead end.