Why did early multi-agent autonomous systems like AutoGen initially fail to meet the hype?
Multi-agent systems mapped well to our human understanding of how to organize work amongst ourselves (i.e. delegation, role responsibility, worker-to-worker communication).
But despite being amassing a ton of developer interest and producing some eye-opening demos, enterprises struggled deploying these implementations to production and opted for simpler single-agent approaches instead.
So why did they fail and what can we learn from the experience?
Watch Eric Zhu and I do a retrospective on AutoGen from our times at Microsoft and Microsoft Research in this clip from the latest episode of the Humans of AI Podcast.
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[ 2.8 ms ] story [ 14.0 ms ] threadMulti-agent systems mapped well to our human understanding of how to organize work amongst ourselves (i.e. delegation, role responsibility, worker-to-worker communication).
But despite being amassing a ton of developer interest and producing some eye-opening demos, enterprises struggled deploying these implementations to production and opted for simpler single-agent approaches instead.
So why did they fail and what can we learn from the experience?
Watch Eric Zhu and I do a retrospective on AutoGen from our times at Microsoft and Microsoft Research in this clip from the latest episode of the Humans of AI Podcast.
https://youtu.be/2cnxea3xkzM