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How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730

2025-05-06 · 67 min · episode 730 · 13 entities

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    How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730
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  • → hosted by TWIML company
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Entities found in this episode

concepts 5

  • mentioned Science concept
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    Feed category: Science
  • mentioned Tech News concept
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  • discusses Science concept
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    evidence rules-v4
    Feed category: Science
  • discusses News concept
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    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
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    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 Josh Tobin person
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    How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730
  • mentioned Sam Charrington person
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    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
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    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
Today, we're joined by Josh Tobin, member of technical staff at OpenAI, to discuss the company’s approach to building AI agents. We cover OpenAI's three agentic offerings—Deep Research for comprehensive web research, Operator for website navigation, and Codex CLI for local code execution. We explore OpenAI’s shift from simple LLM workflows to reasoning models specifically trained for multi-step tasks through reinforcement learning, and how that enables agents to more easily recover from failures while executing complex processes. Josh shares insights on the practical applications of these agents, including some unexpected use cases. We also discuss the future of human-AI collaboration in software development, such as with "vibe coding," the integration of tools through the Model Control Protocol (MCP), and the significance of context management in AI-enabled IDEs. Additionally, we highlight the challenges of ensuring trust and safety as AI agents become more powerful and autonomous. The complete show notes for this episode can be found at https://twimlai.com/go/730.