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Agent skills

5 Best Practices for Building AI Agent Skills

5 Best Practices for Building AI Agent Skills

This video outlines five essential best practices for developing reliable, secure, and effective AI agent skills. It covers optimizing skill triggering through descriptive metadata, leveraging real-world domain expertise over generic LLM output, managing context windows efficiently by writing lean skills and using progressive disclosure, implementing deterministic logic with scripts for fragile operations, and critically vetting all skills for security vulnerabilities before deployment. These practices are crucial for professionals building robust agentic systems.

Is Fine-Tuning Still Needed? LLMs, RAG, & LoRA

Is Fine-Tuning Still Needed? LLMs, RAG, & LoRA

This summary explores the evolving role of fine-tuning in modern AI workflows, comparing it with advanced techniques like RAG, LoRA, and enhanced generative AI capabilities. It discusses the historical benefits, current limitations due to rapidly advancing frontier models, and outlines a practical decision framework for customizing machine learning models and designing efficient AI systems.

Don't Ship Skills Without Evals — Philipp Schmid, Google DeepMind

Don't Ship Skills Without Evals — Philipp Schmid, Google DeepMind

Philipp Schmid from Google DeepMind emphasizes the critical, often-overlooked need for rigorous evaluation of AI agent skills. He argues that shipping skills without testing is akin to deploying code without unit tests, leading to unreliable agent behavior. The talk covers what defines an agent skill, strategies for writing effective and correctly triggering skills, and a practical guide to building lightweight evaluation harnesses to catch failures proactively.

Pair Programming with AI in Your Python Notebook — with Dr. Trevor Manz

Pair Programming with AI in Your Python Notebook — with Dr. Trevor Manz

Dr. Trevor Manz from Marimo introduces Marimo Pair, an open-source agent skill that enables coding agents like Claude Code to interact with and drive reactive Python notebooks. He discusses the mechanics of agent skills, the power of recursive language models for agentic reasoning, and his work on the AnyWidget project, which bridges the gap between Python's data ecosystem and interactive web technologies.

Skill Issue: How We Used AI to Make Agents Actually Good at Supabase — Pedro Rodrigues, Supabase

Skill Issue: How We Used AI to Make Agents Actually Good at Supabase — Pedro Rodrigues, Supabase

A deep dive into building, testing, and iterating on Agent Skills to improve AI agent performance. This workshop covers the core concepts of progressive disclosure, eval-driven development, and practical application using a real-world Supabase and PostgreSQL security scenario.

What AI Agent Skills Are and How They Work

What AI Agent Skills Are and How They Work

AI agents, powered by LLMs, excel at reasoning but lack the procedural knowledge required for real-world workflows. Martin Keen explains how the 'agent skills' open standard solves this by packaging step-by-step instructions, enabling agents to automate complex tasks efficiently and reliably.