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AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718

2025-02-10 · 105 min · episode 718 · 13 entities

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    AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718
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  • → hosted by TWIML company
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Entities found in this episode

concepts 5

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  • mentioned Tech News concept
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    evidence rules-v4
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  • discusses Science concept
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    evidence rules-v4
    Feed category: Science
  • discusses News concept
    0.40
    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
    0.40
    evidence rules-v4
    Feed category: Tech News

companys 4

  • mentioned TWIML company
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    Feed author/publisher: TWIML
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  • hosted by TWIML company
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    Feed author/publisher: TWIML

persons 3

  • mentioned Victor Di person
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    AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718
  • mentioned Sam Charrington person
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    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
Today we’re joined by Victor Dibia, principal research software engineer at Microsoft Research, to explore the key trends and advancements in AI agents and multi-agent systems shaping 2025 and beyond. In this episode, we discuss the unique abilities that set AI agents apart from traditional software systems–reasoning, acting, communicating, and adapting. We also examine the rise of agentic foundation models, the emergence of interface agents like Claude with Computer Use and OpenAI Operator, the shift from simple task chains to complex workflows, and the growing range of enterprise use cases. Victor shares insights into emerging design patterns for autonomous multi-agent systems, including graph and message-driven architectures, the advantages of the “actor model” pattern as implemented in Microsoft’s AutoGen, and guidance on how users should approach the ”build vs. buy” decision when working with AI agent frameworks. We also address the challenges of evaluating end-to-end agent performance, the complexities of benchmarking agentic systems, and the implications of our reliance on LLMs as judges. Finally, we look ahead to the future of AI agents in 2025 and beyond, discuss emerging HCI challenges, their potential for impact on the workforce, and how they are poised to reshape fields like software engineering. The complete show notes for this episode can be found at https://twimlai.com/go/718.