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About this Podcast
Intended for architects and senior developers.
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Building a More Appealing CLI for Agentic LLMs Based on Learnings from the Textual Framework
Will McGugan, the maker of Textual and Rich frameworks, speaks about the reasoning of developing the two two libraries and the lesson learned. Also, he shares light on Toad, his current project, which he envisions being a more visually appealing way of interacting with agentic LLMs through command line.
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Platform Engineering for AI: Scaling Agents and MCP at LinkedIn
QCon AI New York Chair Wes Reisz talks with LinkedIn’s Karthik Ramgopal and Prince Valluri about enabling AI agents at enterprise scale. They discuss how platform teams orchestrate secure, multi-agentic systems, the role of MCP, the use of foreground and background agents, improving developer experience, and reducing toil.
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Elena Samuylova on Large Language Model (LLM)-Based Application Evaluation and LLM as a Judge
In this podcast, InfoQ spoke with Elena Samuylova from Evidently AI, on best practices in evaluating Large Language Model (LLM)-based applications. She also discussed the tools for evaluating, testing and monitoring applications powered by AI technologies.
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AI, ML, and Data Engineering InfoQ Trends Report 2025
In this episode, members of the InfoQ editorial staff and friends of InfoQ discuss the current trends in the domain of AI, ML and Data Engineering. One of the regular features of InfoQ are the trends reports, which each focus on a different aspect of software development. These reports provide the InfoQ readers and listeners with a high-level overview of the topics to pay attention to this year.
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Mandy Gu on Generative AI (GenAI) Implementation, User Profiles and Adoption of LLMs
In this podcast, Mandy Gu from Wealthsimple discusses how to establish AI programs in organizations and implement Generative AI (GenAI) initiatives, and the relationship between user profiles and adoption of LLMs.
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