Vanishing Gradients

Episode 46: Software Composition Is the New Vibe Coding

April 3rd, 2025  |  Season 1  |  1 hr 8 mins

ai, data science, genai, llms, machine learning, vibe coding

What if building software felt more like composing than coding?

In this episode, Hugo and Greg explore how LLMs are reshaping the way we think about software development—from deterministic programming to a more flexible, prompt-driven, and collaborative style of building. It’s not just hype or grift—it’s a real shift in how we express intent, reason about systems, and collaborate across roles.

Hugo speaks with Greg Ceccarelli—co-founder of SpecStory, former CPO at Pluralsight, and Director of Data Science at GitHub—about the rise of software composition and how it changes the way individuals and teams create with LLMs.

Episode 44: The Future of AI Coding Assistants: Who’s Really in Control?

February 4th, 2025  |  Season 1  |  1 hr 34 mins

ai, data science, llms, machine learning

AI coding assistants are reshaping how developers write, debug, and maintain code—but who’s really in control? In this episode, Hugo speaks with Tyler Dunn, CEO and co-founder of Continue, an open-source AI-powered code assistant that gives developers more customization and flexibility in their workflows.

Episode 43: Tales from 400+ LLM Deployments: Building Reliable AI Agents in Production

January 17th, 2025  |  Season 1  |  1 hr 1 min

ai, data science, llms, machine learning

Hugo speaks with Alex Strick van Linschoten, Machine Learning Engineer at ZenML and creator of a comprehensive LLMOps database documenting over 400 deployments. Alex's extensive research into real-world LLM implementations gives him unique insight into what actually works—and what doesn't—when deploying AI agents in production.

Episode 42: Learning, Teaching, and Building in the Age of AI

January 4th, 2025  |  Season 1  |  1 hr 20 mins

ai, data science, genai, llms, machine learning

The tables turn as Hugo sits down with Alex Andorra, host of Learning Bayesian Statistics. Hugo shares his journey from mathematics to AI, reflecting on how Bayesian inference shapes his approach to data science, teaching, and building AI-powered applications.

Episode 41: Beyond Prompt Engineering: Can AI Learn to Set Its Own Goals?

December 31st, 2024  |  Season 1  |  43 mins 51 secs

data science, genai, llms, machine learning

Hugo Bowne-Anderson hosts a panel discussion from the MLOps World and Generative AI Summit in Austin, exploring the long-term growth of AI by distinguishing real problem-solving from trend-based solutions. If you're navigating the evolving landscape of generative AI, productionizing models, or questioning the hype, this episode dives into the tough questions shaping the field.

Episode 40: What Every LLM Developer Needs to Know About GPUs

December 24th, 2024  |  Season 1  |  1 hr 43 mins

ai, data science, llms, machine learning

Hugo speaks with Charles Frye, Developer Advocate at Modal and someone who really knows GPUs inside and out. If you’re a data scientist, machine learning engineer, AI researcher, or just someone trying to make sense of hardware for LLMs and AI workflows, this episode is for you.

Charles and Hugo dive into the practical side of GPUs—from running inference on large models, to fine-tuning and even training from scratch.

Episode 39: From Models to Products: Bridging Research and Practice in Generative AI at Google Labs

November 26th, 2024  |  Season 1  |  1 hr 43 mins

ai, data science, llms, machine learning

From building rockets at SpaceX to advancing generative AI at Google Labs, Ravin Kumar has carved a unique path through the world of technology. In this episode, we explore how to build scalable, reliable AI systems, the skills needed to work across the AI/ML pipeline, and the real-world impact of tools like open-weight models such as Gemma. Ravin also shares insights into designing AI tools like Notebook LM with the user journey at the forefront.

Episode 38: The Art of Freelance AI Consulting and Products: Data, Dollars, and Deliverables

November 5th, 2024  |  Season 1  |  1 hr 23 mins

consulting, data science, genai, llms, machine learning

Hugo speaks with Jason Liu, an independent AI consultant with experience at Meta and Stitch Fix. At Stitch Fix, Jason developed impactful AI systems, like a $50 million product similarity search and the widely adopted Flight recommendation framework. Now, he helps startups and enterprises design and deploy production-level AI applications, with a focus on retrieval-augmented generation (RAG) and scalable solutions.

Episode 37: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 2

October 8th, 2024  |  Season 1  |  50 mins 36 secs

data science, genai, llms, machine learning, nlp, prompt engineering

Hugo speaks with three leading figures from the world of AI research: Sander Schulhoff, a recent University of Maryland graduate and lead contributor to the Learn Prompting initiative; Philip Resnik, professor at the University of Maryland, known for his pioneering work in computational linguistics; and Dennis Peskoff, a researcher from Princeton specializing in prompt engineering and its applications in the social sciences.

Episode 36: Prompt Engineering, Security in Generative AI, and the Future of AI Research Part 1

September 30th, 2024  |  Season 1  |  1 hr 3 mins

data science, genai, llms, machine learning, nlp, prompt engineering

Hugo speaks with three leading figures from the world of AI research: Sander Schulhoff, a recent University of Maryland graduate and lead contributor to the Learn Prompting initiative; Philip Resnik, professor at the University of Maryland, known for his pioneering work in computational linguistics; and Dennis Peskoff, a researcher from Princeton specializing in prompt engineering and its applications in the social sciences.