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From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731

2025-05-13 · 61 min · episode 731 · 16 entities

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    From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731
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Entities found in this episode

companys 7

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persons 3

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    From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731
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podcasts 1

Episode description as stored
Today, we're joined by Mahesh Sathiamoorthy, co-founder and CEO of Bespoke Labs, to discuss how reinforcement learning (RL) is reshaping the way we build custom agents on top of foundation models. Mahesh highlights the crucial role of data curation, evaluation, and error analysis in model performance, and explains why RL offers a more robust alternative to prompting, and how it can improve multi-step tool use capabilities. We also explore the limitations of supervised fine-tuning (SFT) for tool-augmented reasoning tasks, the reward-shaping strategies they’ve used, and Bespoke Labs’ open-source libraries like Curator. We also touch on the models MiniCheck for hallucination detection and MiniChart for chart-based QA. The complete show notes for this episode can be found at https://twimlai.com/go/731.