Generative AI in the Real World

BERTopic creator and Google DeepMind developer relations engineer Maarten Grootendorst has spent years helping practitioners build intuition for how AI systems actually work—not just how to prompt them. Maarten joined Ben Lorica to cover the enduring relevance of embeddings and topic models in an LLM-dominated world, his hot take that agents are essentially just an “LLM in a for loop with some too...

As a pandas core contributor and early Parquet adopter who built AI data pipelines at streaming company Tubi TV, Chang She saw firsthand why the traditional data stack breaks down for AI workloads—and founded LanceDB to fix it. Chang joined Ben Lorica to explain why vector databases are too narrow a solution for modern AI data needs, and what a true multimodal data infrastructure actually looks li...

As the founder and CEO of LevelUp Labs, Aishwarya Naresh Reganti helps organizations “really grapple with AI,” and through her teaching, she guides individuals who are doing the same. Aishwarya joined Ben to share her experience as a forward-deployed expert supporting companies that are putting AI into production. Listen in to learn the value  all  roles—from data folks and developers to SMEs like...

Post-training gets your model to behave the way you want it to. As AMD VP of AI Sharon Zhou explains to Ben on this episode, the frontier labs are convinced, but the average developer is still figuring out how post-training works under the hood and why they should care. In their focused discussion, Sharon and Ben get into the process and trade-offs, techniques like supervised fine-tuning, reinforc...

Synthetic data has been around for a long time, decades even. But as KPMG’s Fabiana Clemente points out, “That doesn’t mean there aren’t a lot of misconceptions.” Fabiana sat down with Ben to clarify some of the current applications of synthetic data and new directions the field is taking—working with offshore teams when privacy controls just don’t allow you to share actual datasets, improving fra...

SwirlAI founder Aurimas Griciūnas helps tech professionals transition into AI roles and works with organizations to create AI strategy and develop AI systems. Aurimas joins Ben to discuss the changes he’s seen over the past couple years with the rise of generative AI and where we’re headed with agents. Aurimas and Ben dive into some of the differences between ML-focused workloads and those impleme...

As the founder, editor, and lead writer of  Turing Post , Ksenia Se spends her days peering into the emerging future of artificial intelligence. She joined Ben to discuss the current state of adoption: what people are actually doing right now, the big topics that got the most traction this year, and the trends to look for in 2026. Find out why Ksenia thinks the real action next year will be in are...

MLOps is dead. Well, not really, but for many the job is evolving into LLMOps. In this episode, Abide AI founder and  LLMOps  author Abi Aryan joins Ben to discuss what LLMOps is and why it’s needed, particularly for agentic AI systems. Listen in to hear why LLMOps requires a new way of thinking about observability, why we should spend more time understanding human workflows before mimicking them...

In this episode, Laurence Moroney, director of AI at Arm, joins Ben Lorica to chat about the state of deep learning frameworks—and why you may be better off thinking a step higher, on the solution level. Listen in for Laurence’s thoughts about posttraining; the evolution of on-device AI (and how tools like ExecuTorch and LiteRT are helping make it possible); why culturally specific models will onl...

In this episode, Ben Lorica and Chris Butler, director of product operations for GitHub's Synapse team, chat about the experimentation Chris is doing to incorporate generative AI into the product development process—particularly with the goal of reducing toil for cross-functional teams. It isn’t just automating busywork (although there’s some of that). He and his team have created agents that...

In this episode, Ben Lorica and Drew Breunig, a strategist at the Overture Maps Foundation, talk all things context engineering: what’s working, where things are breaking down, and what comes next. Listen in to hear why huge context windows aren’t solving the problems we hoped they might, why companies shouldn’t discount evals and testing, and why we’re doing the field a disservice by leaning into...

In this episode, Ben Lorica and Anthropic interpretability researcher Emmanuel Ameisen get into the work Emmanuel’s team has been doing to better understand how LLMs like Claude work. Listen in to find out what they’ve uncovered by taking a microscopic look at how LLMs function—and just how far the analogy to the human brain holds.

Everyone is talking about agents: single agents and, increasingly, multi-agent systems. What kind of applications will we build with agents, and how will we build with them? How will agents communicate with each other effectively? Why do we need a protocol like A2A to specify how they communicate? Join Ben Lorica as he talks with Heiko Hotz and Sokratis Kartakis about A2A and our agentic future.

In this episode, Ben Lorica and AI Engineer Faye Zhang talk about discoverability: how to use AI to build search and recommendation engines that actually find what you want. Listen in to learn how AI goes way beyond simple collaborative filtering—pulling in many different kinds of data and metadata, including images and voice, to get a much better picture of what any object is and whether or not i...

Join Luke Wroblewski and Ben Lorica as they talk about the future of software development. What happens when we have databases that are designed to interact with agents and language models rather than humans? We’re starting to see what that world will look like. It’s an exciting time to be a software developer.

Jay Alammar, director and Engineering Fellow at Cohere, joins Ben Lorica to talk about building AI applications for the enterprise, using RAG effectively, and the evolution of RAG into agents. Listen in to find out what kinds of metadata you need when you’re onboarding a new model or agent; discover how an emphasis on evaluation helps an organization improve its processes; and learn how to take ad...

Phillip Carter, formerly of Honeycomb, and Ben Lorica talk about observability and AI—what observability means, how generative AI causes problems for observability, and how generative AI can be used as a tool to help SREs analyze telemetry data. There’s tremendous potential because AI is great at finding patterns in massive datasets, but it’s still a work in progress. About the  Generative AI in t...

Audio is being added to AI everywhere: both in multimodal models that can understand and generate audio and in applications that use audio for input. Now that we can work with spoken language, what does that mean for the applications that we can develop? How do we think about audio interfaces—how will people use them, and what will they want to do? Raiza Martin, who worked on Google’s groundbreaki...

How do you teach kids to use and build with AI? That’s what Stefania Druga works on. It’s important to be sensitive to their creativity, sense of fun, and desire to learn. When designing for kids, it’s important to design with them, not just for them. That’s a lesson that has important implications for adults, too. Join Stefania Druga and Ben Lorica to hear about AI for kids and what that has to s...

Join our host Ben Lorica and Douwe Kiela, cofounder of Contextual AI and author of the first paper on RAG, to find out why RAG remains as relevant as ever. Regardless of what you call it, retrieval is at the heart of generative AI. Find out why—and how to build effective RAG-based systems. Points of Interest 0:25 : Today’s topic is RAG. With frontier models advertising massive context windows, man...

Join Danielle Belgrave and Ben Lorica for a discussion of AI in healthcare. Danielle is VP of AI and machine learning at GSK (formerly GlaxoSmithKline). She and Ben discuss using AI and machine learning to get better diagnoses that reflect the differences between patients. Listen in to learn about the challenges of working with health data—a field where there’s both too much data and too little, a...

Ben Lorica and Gabriela de Queiroz, director of AI at Microsoft, talk about startups: specifically, AI startups. How do you get noticed? How do you generate real traction? What are startups doing with agents and with protocols like MCP and A2A? And which security issues should startups watch for, especially if they’re using open weights models? Points of Interest 0:30 : You work with a lot of star...

Join Steve Wilson and Ben Lorica for a discussion of AI security. We all know that AI brings new vulnerabilities into the software landscape. Steve and Ben talk about what makes AI different, what the big risks are, and how you can use AI safely. Find out how agents introduce their own vulnerabilities, and learn about resources such as OWASP that can help you understand them. Is there a light at t...

Businesses have a lot of data—but most of that data is unstructured textual data: reports, catalogs, emails, notes, and much more. Without structure, business analysts can’t make sense of the data; there is value in the data, but it can’t be put to use. AI can be a tool for finding and extracting the structure that’s hidden in textual data. In this episode, Ben and Shreya talk about a new generati...

Ever since Andrej Karpathy first tweeted it, “vibe coding” has been on every software developer’s mind. Join Ben Lorica and Steve Yegge to find out what vibe coding means, especially in a professional context. Going beyond the current memes, what will the future of software development look like when we have multiple agents? And how do you prepare for it? Don’t push back against AI now; lean into...