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Half a year has passed, and it feels like a long time in the field of AI. I read this article repeatedly a few months ago, but now I think the development of Agent has obviously reached a bottleneck. Even the latest gemini seems to have regressed.


(1) Running multiple agents is expensive, decreasing RoI. My DeepSearch agent for stocks uses 6 agents, and each query costs about 2 USD.

(2) Multi-agent orchestration is difficult to control.

(3) The more capable the model, the lower the need for multi-agents.

(4) The less capable the model, the higher the business case for narrow AI.


What exactly makes them regress?

Why can’t they just fork swarms of themselves, work 24/7 in parallel, check work and keep advancing?


Because they are not intelligent. (And this is a good definition of it).


How is that a regression?


They have hard time solving prompt issues injection and that’s a one of the bottle necks




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