Join our virtual meetup to hear talks from experts on cutting-edge topics across MCP and Skills. View more CV events here.

Discover how coding agents can run or support your fine-tuning experiments. From quick dataset validation and preprocessing, to optimal GPU hardware selection, to automated job submission based on metric tracking, to evaluation. Ben will demonstrate how Hugging Face skills can be used to define best practices for agents to support machine learning experiments. Bring Claude, Codex, or Mistral Vibes, and we’ll show you to get it training models with GRPO, SFT, and DPO.

Ben Burtenshaw is a Machine Learning Engineer at Hugging Face, focusing on building agents with fine-tuning and reinforcement learning. He led educational projects like the Agents Course, the MCP Course, and the LLM course, which bridge the gap between complex Reinforcement Learning (RL) techniques and practical application. Ben focuses on democratizing access to efficient AI, empowering the community to align, evaluate, and deploy transparent agentic systems.

This talk explores how to configure and align Claude Code agents using templates and custom components. I'll demonstrate practical configuration patterns that ensure your CLI agent executes exactly what you intend, covering Skills setup, hooks implementation, and template customization. Drawing from real-world examples building Claude Code Templates, attendees will learn how to structure their agent configurations for consistent, reliable behavior and create reusable components that maintain alignment across different use cases.

Daniel Avila is an AI Engineer at Hedgineer building agentic systems and creator of Claude Code Templates.

Computer vision teams spend too much time writing scripts just to find bad labels, blurry images, and edge cases. In this talk, I’ll show how to move that work to agents by using FiftyOne as a visual operating system. With Skills and MCP, agents can see inside your datasets, explore them visually, and handle common data cleanup tasks, so you can spend less time on data and more time shipping models.

Adonai Vera - Machine Learning Engineer & DevRel at Voxel51. With over 7 years of experience building computer vision and machine learning models using TensorFlow, Docker, and OpenCV.

Skills are self-contained recipes - each one a piece of a larger puzzle. Instead of trying to modify human-centric documentation to better fit agents, skills let us build capabilities into our agents directly. This talk will showcase how to think about leveraging skills to enhance how users interact with your software!

Chris Alexiuk is a deep learning developer advocate at NVIDIA, working on creating technical assets that help developers use the incredible suite of AI tools available at NVIDIA. Chris comes from a machine learning and data science background, and he is obsessed with everything and anything about large language models.