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Saleema Amershi is a Partner Research Manager at Microsoft Research AI Frontiers, where she leads the teams behind AutoGen and Magentic-One. She joins the AI Inside podcast to discuss what happens when AI agents stop working in isolation and start collaborating, transacting, and negotiating with each other at scale. We cover the challenges of multi-agent orchestration, why current frontier models show a dangerous first-proposal bias that favors speed over quality, and how her team built the Magentic Marketplace to simulate agent-to-agent commerce. We also dig into agent manipulation, the tension between walled gardens and open ecosystems, and what duty of care means when an AI is acting on your behalf.
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Chapters:
- 0:00 - Podcast Start
- 01:46 - Introduce Saleema Amershi
- 0:02:04 - Talk about the challenges surrounding the orchestration of these agents together. And what limits this collaboration today, is it a technical limitation or something deeper?
- 0:05:10 - OpenClaw perspectives
- 0:06:42 - From your research, why would these projects fall apart? And actually, are companies setting themselves up for failure by moving too fast?
- 0:07:53 - What IS Magentic AI
- 0:12:16 - Collaboration between humans, AI and the agents.
- 0:18:45 - Agents eliminate the scarcity of attention
- 0:20:04 - You found that these frontier models that we're often told are ready to handle complex tasks like these were getting stunted by too many choices. They were showing a strong bias toward whatever option showed up first regardless of the quality. So, what's going on there?
- 0:24:07 - The first-proposal bias
- 0:33:25 - You co-published 18 guidelines for human-AI interaction back in 2019. When you look at those original guidelines through the lens of what you're working on today, what still holds up and what could you not have anticipated back then?
- 0:36:58 - What are the lessons for marketers and sellers?
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