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Agents of Data

Podcast af Agents of Data

engelsk

Business

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Inside the code, culture, and [often] chaos of Agentic AI. Agents of Data isn’t about AI theory; it’s about AI in action. Each episode brings you into the room with the engineers, architects, and leaders who are building agentic AI systems that deliver measurable results. Hosted by Matillion’s AI experts, the show breaks down practical use cases, lessons learned, and strategies for creating platforms that work today – and will still work tomorrow.

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7 episoder

episode 6: Becoming AI Native cover

6: Becoming AI Native

AI-native companies win on speed, scale, and resilience. This episode shows how leaders can transform their organisations by adopting agentic and generative AI across engineering, data and analytics.  Sam and Julian describe the move from early experimentation to agent-driven workflows - coding agents, automated research and context-aware copilots that materially expand output. They explain why CDOs must lead this shift, how knowledge curation becomes as important as code, and why strong context and testing frameworks separate real productivity from noise.  The conversation also outlines the risks of delaying adoption, the challenges of building in-house without constant model updates and the opportunity for every function - from engineering to operations - to augment human capability.  The guidance is clear: target high-value use cases, choose tools that learn your business, and build a culture that embraces continuous reinvention.

25. nov. 2025 - 39 min
episode 2: Semantic Layers: AI Only Knows What It Sees cover

2: Semantic Layers: AI Only Knows What It Sees

This episode of the Agents of Data podcast double-clicks into semantic layers, exploring their definition, function and the challenges associated with their implementation.  Frank Weigel, Chief Product Officer at Matillion, joins the discussion to address issues like stale data, ownership battles and the evolving roles of humans in the context of semantic layers and agentic AI.  The conversation explores how organizations currently store semantic information, the advantages of LLMs in handling inconsistent data, and the potential for a shift in responsibility towards maintaining semantic layers.  The guests also discuss the future of semantic layers, considering whether they will be centralized or fragmented, and the importance of visibility and explainability within these systems.

30. sept. 2025 - 39 min
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