Europe 2026
Full Walkthrough: Writing & Using Skills — Nick Nisi and Zack Proser
Overview
This workshop explores the concept and practical application of "skills" in AI agents, presenting them as discrete, composable units of work designed to enhance agentic workflows. The core thesis is that skills provide a structured way to encode essential context, instructions, and behaviors, preventing repetitive information input and ensuring consistent, predictable agent performance across various tasks and projects.
Who should watch
- AI Engineers
- Product Managers
- Developers building with AI agents
- Anyone looking to improve AI agent reliability and consistency
- Users struggling with LLMs forgetting context or deviating from instructions
Key takeaways
- Skills are composable units of work that can be as simple as markdown files or include scripts and other assets.
- They help overcome the stateless nature of LLM conversations by providing persistent, context-specific instructions and data.
- Skills improve agent performance by offering specific guidance, constraints, and executable logic, reducing LLM speculation.
- The description field within a skill is crucial for the LLM to determine when and how to route to that skill.
- Skills can be made more powerful through techniques like progressive disclosure, confidence scoring, and iterative refinement based on usage analysis.
- Skills are model-agnostic and can be shared across different platforms and technical skill levels, including non-technical users via tools like Claude Desktop.
- Skills can be extended with sub-agents for more complex, isolated tasks that require their own context.
- Evaluating skill performance is critical, using frameworks or manual analysis to ensure they improve, rather than degrade, agent capabilities.
Notable quotes
*Skills are that next step. It's a way to make things more portable and you can use scripts to inject real data.*
*You're teaching the LLM how to do something in the way that you expect it to be done and then it will follow that much more closely.*
*The description is not for humans. The description is really more for the LLM so that it knows when it should use the skill automatically.*
Unofficial community note. Prefer the recording for nuance.