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Bob Seiner has spent decades in data governance, and in this episode he joins Juan and Tim to unpacks his new framework, Data Catalyst Cubed, which multiplies data governance by change management and data fluency. Miss any one of them, and you get zero. The problem is that leadership has never treated behavior change as part of the governance mandate, and most data programs have never connected with the change management expertise that already exists inside their organizations. See omnystudio.com/listener for privacy information.
Takeaway episode with Bob Seiner where he unpacks his new framework, Data Catalyst Cubed: multiplies data governance by change management and data fluency. Miss any one of them, and you get zero. See omnystudio.com/listener for privacy information.
Day One Ready: What New Engineers Actually Need to Know About AI | Engineering Now Unlocked Starting your first engineering role — or coming back for a return offer — and wondering what AI actually changes about the job? This episode gives you the real answer, from two engineers living it every day. Jordan Shelton and Cynthia Mathenge sit down with Ian Thurlow (Senior Manager, Data Platform Software Engineering) and Andrew Yan (Software Engineer, Data Foundations) to talk about what day one looks like now, what AI tools actually do for early-career engineers, and what fundamentals still separate good engineers from great ones. If you’re about to start an internship, just got your return offer, or you’re a manager thinking about how to set new engineers up for success — this is the conversation you need before day one. What you’ll learn✔ What AI actually changes about day-to-day engineering work (and what it doesn’t) ✔ Why the fundamentals matter more than ever — not less ✔ How to build a network at a company like ServiceNow, even if you start remotely ✔ How to use AI as a sounding board, not a crutch Chapters 00:00 Introduction — Engineering Now Unlocked 02:08 Meet Ian Thurlow and Andrew Yan 03:03 How AI is changing day-to-day engineering work 04:47 AI as an accelerator, not a replacement 09:04 AI as a sounding board 12:38 Leadership mindset in an AI-first team 13:46 Raising the bar for early-in-career talent 15:41 What your first 30 days should look like 17:43 This or That 19:16 Code reviews: the fastest way to learn that nobody talks about 20:57 Building your network — even fully remote 24:24 Ian and Andrew’s Work Advice 27:43 Outro Guests Ian Thurlow Senior Manager, Data Platform Software Engineering — ServiceNow Andrew Yan Software Engineer, Data Foundations — ServiceNow Hosts Jorden Shelton Technical Program Manager, AI Engineering & Delivery — ServiceNow Cynthia Mathenge Business Operations Manager, AI Engineering & Delivery — ServiceNow Bobby Brill ServiceNow Insights Links & Resources Learn more about ServiceNow Engineering → https://www.servicenow.com/company/careers/engineering.html ServiceNow Docs → https://docs.servicenow.com New to the channel? Subscribe so you never miss an episode of ServiceNow Insights.See omnystudio.com/listener for privacy information.
Most organizations are treating AI governance as a compliance checkbox. Victoria Gamerman argues it's the gateway that finally forces organizations to confront the human side of AI adoption. In this episode, Victoria breaks down why the POC-to-operationalization gap is so hard to close, why people, process, and data each carry more human weight than most leaders acknowledge, and what "AI-ready data" actually means and a reminder that AI isn't a technology problem. It never was.See omnystudio.com/listener for privacy information.
This is the takeaway episode with Victoria Gamerman who argues that AI Governance is the gateway that finally forces organizations to confront the human side of AI adoption. See omnystudio.com/listener for privacy information.
Everybody wants AI. AI adoption conversations are dominated by tools, models, and metrics. Far fewer organizations have figured out what to do with it once it's inside the building. The harder question, one that most leaders are avoiding, is what happens to the humans? Diana Wu David, Director of Futures at ServiceNow joins Juan and Tim to unpack what leaders should and should not be doing. See omnystudio.com/listener for privacy information.
This is the takeaway episode with Diana Wu David, Director of Futures at ServiceNow where we discuss AI adoption, the metrics and how far fewer organizations have figured out what to do with AI once it's inside the building.See omnystudio.com/listener for privacy information.
Voice AI agent evaluation — why it's fundamentally harder than text, how cascade failures derail conversations invisibly, and ServiceNow's open-source framework to establish industry evaluation standards. Featuring real audio examples showing authentication failures, leaked reasoning, and latency problems. WHAT WE COVER TARA BOGAVELLI — Research Engineer, ServiceNow Leading the open-source voice agent evaluation framework. Explains why existing benchmarks don't measure what matters and what ServiceNow is releasing to establish industry standards. KATRINA STANKIEWICZ — Staff Machine Learning Engineer, ServiceNow Cascade model architecture expert. Breaks down STT → LLM → TTS failure modes, named entity transcription challenges, and real audio example analysis. GABRIELLE GAUTHIER MELANÇON — Staff Applied Research Scientist, ServiceNow Multi-language evaluation specialist. Reveals why Large Audio Language Models lag behind, the native speaker requirement, and bot-to-bot simulation methodology. CHAPTERS0:00 Introduction — The evaluation gap 1:11 ServiceNow's Open-Source Framework Announcement — Tara Bogavelli 2:43 Meet the Researchers 3:43 Voice-Specific Challenges — Tara Bogavelli 5:03 Cascade Architecture: STT → LLM → TTS — Katrina Stankiewicz 7:57 The Named Entity Problem — Katrina Stankiewicz 10:06 Evaluation Metrics: Accuracy vs Experience — Gabrielle Gauthier Melançon 11:23 Bot-to-Bot Testing at Scale — Gabrielle Gauthier Melançon 14:30 The LALM Gap: Why Audio AI Judges Struggle — Tara Bogavelli16:57 Real Audio Example: Flight Rebooking Gone Wrong 21:58 Breaking Down the Failures — Katrina Stankiewicz 28:30 Wrap-Up & Resources KEY INSIGHTS The Cascade Failure Problem: STT → LLM → TTS errors propagate invisibly Named Entity Transcription: The #1 enterprise blocker—names, confirmation codes, emails break authentication Accuracy vs Experience: Perfect task completion means nothing if users hang up due to poor experience LALM Gap: Large Audio Language Models lag behind text LLMs—human evaluators remain essential Latency Kills Conversations: Five-second pauses make users think the call dropped, breaking the experience even when tasks complete Open-Source Framework: ServiceNow releasing evaluation tools, metrics, and bot-to-bot simulation methodology for the industry. LEARN MORE Website: https://servicenow.github.io/eva/ GitHub: https://github.com/servicenow/eva Blog Post: https://huggingface.co/blog/ServiceNow-AI/eva Dataset: https://huggingface.co/datasets/ServiceNow-AI/eva ABOUT Hosted by Bobby Brill. ServiceNow Insights podcast explores AI research, real-world applications, and the people building the future of work. #VoiceAI #AIEvaluation #ServiceNow #MachineLearning #OpenSource #ConversationalAI #STT #TTS #LLM #VoiceAgents #AIResearch #PodcastSee omnystudio.com/listener for privacy information.
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